DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
An information disclosure statement has not been received. If the Applicant is aware of any prior art or any other co-pending applications not already of record, he/she is reminded of his/her duty under 37 CFR 1.56 to disclose the same.
Drawings
The drawings are objected to because unlabeled non-descriptive representations are impermissible under 37 CFR 1.83(a) which states (bold for emphasis):
(a) The drawing in a nonprovisional application must show every feature of the invention specified in the claims. However, conventional features disclosed in the description and claims, where their detailed illustration is not essential for a proper understanding of the invention, should be illustrated in the drawing in the form of a graphical drawing symbol or a labeled representation (e.g., a labeled rectangular box). In addition, tables that are included in the specification and sequences that are included in sequence listings should not be duplicated in the drawings.
Element(s) 10-15 & 20-28 in fig. 1 (Examiner notes that a single instance for each therein is sufficient) and 20 in figs. 2-3 (Examiner likewise notes sufficiency of labeling a single iteration of 20 for each figure) need appropriate legends in the form of descriptive text labels in addition to any reference characters already present. Empty or not labeled rectangular boxes and non-descriptive representations of features are not descriptive, and therefore incomplete. The descriptive text labels should contain as few words as possible. See also 37 CFR 1.84(n) (conventional symbols), 1.84(o) (required descriptive legends), & 1.84(p) (standards for the text labels), and MPEP § 608.02(b)(II)(¶ 6.22) (“descriptive text label”). Appropriate Correction is required.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Claim Interpretation
The Examiner acknowledges the definition(s) in/on [0049], [0182]-[0186], & [0192] of the originally filed specification. MPEP § 2111 states that “the specification must provide a clear and intentional use of a special definition for the claim term to be treated as having a special definition”. Where Applicant’s definitions are optional or non-limiting the definitions are not considered special definitions and claim terms referencing such definitions will instead be considered under the broadest reasonable interpretation in view of the specification. If Applicant wishes to provide further explanation or to identify missed definitions, Applicant should clearly identify the special definitions and corresponding structure with reference to the specification by page and line number, and to the drawing, if any, by reference characters in response to this Office action. Examples should be clearly delineated from required features.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
MPEP § 2173.02(I) states in part: “if the language of a claim, given its broadest reasonable interpretation, is such that a person of ordinary skill in the relevant art would read it with more than one reasonable interpretation, then a rejection under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph is appropriate”.
Claim(s) 12 is/are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claim 12,
the limitation “wherein the inertial measurement unit comprises at least two of an accelerometer, a gyroscope, and a magnetometer” could be reasonably interpreted as requiring at least two of each of an accelerometer, a gyroscope, and a magnetometer, or could alternatively be reasonably interpreted as at least two members selected from the group consisting of an accelerometer, a gyroscope, and a magnetometer. While the latter interpretation appears to be the most appropriate, for compact prosecution the Examiner has endeavored to provide analysis for the narrower interpretation. Applicant clarification and appropriate correction is respectfully requested.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-10 and 18-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over newly cited Marques et al (WO 2020249514 A1; hereafter “Marques”) in view of newly cited Miller et al (US 20190069245 A1;hereafter “Miller”).
Regarding independent claim 1,
Marques teaches a method for a motion tracking system (Title “DETERMINATION OF CAUSE OF DISCONNECTION OF SENSORS OF A MOTION TRACKING SYSTEM”; Abstract “computing device of a motion tracking system and one or more sensors of a plurality of sensors of the motion tracking system”), the motion tracking system (fig. 1, motion tracking system 10) comprising a computing device (figs. 1-3, computing device 40) and a plurality of motion trackers (figs. 1-3, sensors 20) in communication with the computing device (figs. 1-3, computing device 40) (page 14, ll. 35-37 “wireless communications connections 50a-50n established between each sensor 20a-20n and the computing device 40 by means of the respective communications modules 38, 46”), and the method comprising:
using a user interface (not fully shown; means for providing at least one user perceptible signal) provided by the computing device (figs. 1-3, computing device 40) to instruct a subject (figs. 2-3, person 1) to perform a movement of one or more body members (body members of person 1) of the subject (figs. 2-3, person 1) (page 13, ll. 21-25 “the motion tracking system or the computing device comprises means for providing at least one user perceptible signal, whereas in some other embodiments, the computing device wirelessly communicates with means for providing at least one user perceptible signal that are not part of the motion tracking system. The means may be, for example, a screen, audio output means such as loudspeakers, etc.”; page 15 line 27 through page 16 line 7 “The computing device 40 may provide or command the provision of examples and guidance on which movements/exercises are to be performed by the person 1 when activity thereof is to be tracked with the motion tracking system”); and
tracking the subject (figs. 2-3, person 1) using the plurality of motion trackers (figs. 1-3, sensors 20) of the motion tracking system (fig. 1, motion tracking system 10), wherein, during the tracking of the subject (figs. 2-3, person 1), one or more of the plurality of motion trackers (figs. 1-3, sensors 20) is disposed on or adjacent to the one or more body members (body members of person 1) of the subject (figs. 2-3, person 1) (page 15, ll. 22-26 “The sensors 20a-20e track the motion of the body members having a sensor 20a-20e arranged thereon; they transmit the orientation measurements to the computing device 40, which in turn determines and provides a movement sequence of said body members and, possibly, of other body members with no sensors arranged thereon by means of digital processing of the measurements”).
Marques does not teach adjustment of (sampling) frequencies of motion trackers including: performing an adjustment of one or more frequencies of one or more of the plurality of motion trackers to reduce a power consumption of at least one of the plurality of motion tracker to thereby reduce the power consumption of the motion tracking system, wherein the one or more frequencies is adjusted based at least in part on the movement which the subject is instructed to perform, and during or subsequent to performing the adjustment of the one or more frequencies, tracking the subject using the plurality of motion trackers of the motion tracking system.
Miller teaches a method for reducing a power consumption of a motion tracking system (Title “POWER MANAGEMENT FOR WEARABLE DEVICES”; Abstract “A method, system, apparatus, and/or device for adjusting a power consumption level of a device”), the motion tracking system (fig. 11, user measurement device 1100) comprising a computing device (computing portion of UMD 1100 comprising processor 1106 with memory device 1108 with display 1112) and a plurality of motion trackers (fig. 11, physiological sensors 1102 and activity sensors 1104) in communication with the computing device (computing portion of UMD 1100 comprising processor 1106 with memory device 1108 with display 1112) ([0162] “measurement related to a living body, such as a human's body or an animal's body. The physiological measurement is a measurement made to assess body functions. Physiological measurements may be very simple, such as the measurement of body or ambient temperature, or they may be more complicated, for example measuring how well the heart is functioning by taking an ECG (electrocardiograph). Physiological measurements may also include motion and/or movement of the body. In some cases, these physiological measurements may be taken to determine an activity level”; [0125], [0163]-[0164] extensive lists of sensors), and the method comprising: using a user interface (sensory devices comprising display 112) provided by the computing device (computing portion of UMD 1100 comprising processor 1106 with memory device 1108 with display 1112) to recommend a subject (user) to perform an activity which comprises movement of one or more body members of the subject (user) ([0145] “the UMD can include sensor devices to provide sensory indications to a user. In one example, the sensory device can be a visual sensory device, such as a display. The UMD can display information to a user using the visual sensory device. In another example, the sensory device can be an auditory sensory device, such as a speaker. The UMD can communicate information to a user using the auditory sensory device, such as communicating information to the user via the speaker. In another example, the sensory device can be a touch sensory device, such as a vibrator. The UMD can communicate information to a user using the touch sensory device. For example, the vibrator can vibrate for different periods of time or at different intervals to indicate different information to a user”; [0066] “communicate information to a display of the UMD. The information can include diagnosis information, recommended actions”; [0100] “The analysis tool can determine a change in the activity (e.g., a suggested or recommended course of action) of the user based on the measurements” and “when the analysis tool determines that an injury risk level has increased above a threshold level, the analysis tool can determine a change in user activities to decrease the injury risk level. For example, when the analysis tool determines an increased injury risk level, the analysis tool can determine that the user can decrease an amount of physical activity” and “determine a recommended course of action based on one or more measurements of the sensors of the UMD”; [0101] “analysis tool can identify an activity from multiple activities that may increase a heart rate of a user while not increasing a blood pressure level and dehydration level of the user. The analysis tool can communicate the identified activity to the user via a sensory indicator of the UMD or another computing device (such as a display)”; [0104] “activity (such as running)”; [0200] “type of activity can be a sports or athletic activity, such as running, football, basketball, soccer, baseball, hockey, and so forth”; [0080] “different activities can be different types of actions. The different types of actions can include: sleeping, sitting, walking, jogging, running, climbing, laying, standing, stepping, and so forth”); performing an adjustment of one or more frequencies (sample rates/frequencies) of one or more of the plurality of motion trackers (fig. 11, physiological sensors 1102 and activity sensors 1104) to reduce a power consumption of at least one of the plurality of motion trackers (fig. 11, physiological sensors 1102 and activity sensors 1104) to thereby reduce the power consumption of the motion tracking system (fig. 11, user measurement device 1100), wherein the one or more frequencies is adjusted based at least in part on the movement which the subject (user) is performing ([0033] “adjusting a frequency of taking physiological measurement”; [0165] “the PMM 1120 can determine an activity level based on an activity level (e.g., an activity-based PMM) and can adjust the default pattern in various ways as described in more detail below” and “sensor module 1122 can be programmed to measure a set of physiological measurement according to a default pattern. The default pattern may be the frequency, granularity, and power used for measurements by the physiological sensors” and “adjusting a frequency or granularity of taking physiological measurements; turning off one or more systems of the apparatus”; [0170] “the activity-based PMM 1120 determines a second sample rate for at least one of the multiple sensors (1102, 1104) using the determined amount of activity and instructs the sensor module 1125 to adjust the at least one of the multiple sensors to the second sample rate for a second set of physiological measurements. In some cases, the second sample rate is less than the corresponding one of the default sample rates. A lower sampling rate may cause the wearable UMD 1100 to consume less power when taking the second set of physiological measurements than when using the default sample rates to take the first set of physiological measurements”; [0171] “the activity-based PMM can instruct the sensor module 1122 to adjust the default sample rates to a second combination of different rates for the different ones of the multiple sensors”); and during or subsequent to performing the adjustment of the one or more frequencies, tracking the subject (user) using the plurality of motion trackers (fig. 11, physiological sensors 1102 and activity sensors 1104) of the motion tracking system (fig. 11, user measurement device 1100), wherein, during the tracking of the subject (user), one or more of the plurality of motion trackers (fig. 11, physiological sensors 1102 and activity sensors 1104) is disposed on or adjacent to the one or more body members of the subject (user) ([0146] “the UMD can be attached to different locations on a user's body using different UMD holders. For example, the UMD can be coupled with a wristband UMD holder to attach the UMD to a wrist position on the user. In another example, the UMD can be coupled with a headband UMD holder to attach the UMD to a head position (such as the forehead) on the user”; [0148] “The different UMD holders can position or align the UMD to engage the body differently based on the location of the UMD”; [0172] “the multiple sensors include a hardware motion sensor to measure at least one of movement or motion of the wearable UMD 1100. The activity-based PMM 1120 can determine the amount of activity based at least in part on the at least one of the movement or motion of the wearable UMD”; [0210] “a user can use multiple portable devices at the same time or substantially the same time. For example, the portable device can be a monitoring device that can be coupled to different locations of the body of the use”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Miller’s power management module and associated method of sampling rate/frequency adjustments for a motion tracking system with Marques motion tracking system for the expected advantages of saving power by both adjusting the default sampling pattern in accordance with the instructed to perform activity type and by dynamically reducing sampling rate/frequency and/or increasing accuracy/precision by increasing sampling rate/frequency based upon motion measured activity need. Complimentarily, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Marques’ body movement instruction via user interface with Miller’s motion tracking system thereby providing the expected advantages of providing physical exercise instruction and feedback including for therapy and/or rehabilitation and thus improving the physical condition of the user and/or reducing risk of further injury and/or improving the guidance including appropriate level of difficulty, as well as providing default activity identification for Miller’s activity-based power management and thus resulting in appropriate default values including default sampling rate/frequency from onset of the activity and thus providing proper measurements while balancing power consumption at said onset of the activity. The Examiner additionally notes that the Courts have ruled an obviousness analysis based on the collective teachings of the references does not depend on the order in which the references are listed in the statement of the rejection. See In re Bush, 296 F.2d 491, 496 (CCPA 1961): “In a case of this type where a rejection is predicated on two references each containing pertinent disclosure which has been pointed out to the applicant, we deem it to be of no significance, but merely a matter of exposition, that the rejection is stated to be on A in view of B instead of on B in view of A, or to term one reference primary and the other secondary.”
Regarding independent claim 19,
Marques teaches a motion tracking system (fig. 1, motion tracking system 10) comprising at least one computing device (figs. 1-3, computing device 40) and a plurality of motion trackers (figs. 1-3, sensors 20) in communication with the at least one computing device (figs. 1-3, computing device 40) (Title “DETERMINATION OF CAUSE OF DISCONNECTION OF SENSORS OF A MOTION TRACKING SYSTEM”; Abstract “computing device of a motion tracking system and one or more sensors of a plurality of sensors of the motion tracking system”; page 14, ll. 35-37 “wireless communications connections 50a-50n established between each sensor 20a-20n and the computing device 40 by means of the respective communications modules 38, 46”), and configured to perform operations comprising:
using a user interface (not fully shown; means for providing at least one user perceptible signal) provided by the computing device (figs. 1-3, computing device 40) to instruct a subject (figs. 2-3, person 1) to perform a movement of one or more body members (body members of person 1) of the subject (figs. 2-3, person 1) (page 13, ll. 21-25 “the motion tracking system or the computing device comprises means for providing at least one user perceptible signal, whereas in some other embodiments, the computing device wirelessly communicates with means for providing at least one user perceptible signal that are not part of the motion tracking system. The means may be, for example, a screen, audio output means such as loudspeakers, etc.”; page 15 line 27 through page 16 line 7 “The computing device 40 may provide or command the provision of examples and guidance on which movements/exercises are to be performed by the person 1 when activity thereof is to be tracked with the motion tracking system”); and
tracking the subject (figs. 2-3, person 1) using the plurality of motion trackers (figs. 1-3, sensors 20) of the motion tracking system (fig. 1, motion tracking system 10), wherein, during the tracking of the subject (figs. 2-3, person 1), one or more of the plurality of motion trackers (figs. 1-3, sensors 20) is disposed on or adjacent to the one or more body members (body members of person 1) of the subject (figs. 2-3, person 1) (page 15, ll. 22-26 “The sensors 20a-20e track the motion of the body members having a sensor 20a-20e arranged thereon; they transmit the orientation measurements to the computing device 40, which in turn determines and provides a movement sequence of said body members and, possibly, of other body members with no sensors arranged thereon by means of digital processing of the measurements”).
Marques does not teach adjustment of (sampling) frequencies of motion trackers including: performing an adjustment of one or more frequencies of one or more of the plurality of motion trackers to reduce a power consumption of at least one of the plurality of motion tracker to thereby reduce the power consumption of the motion tracking system, wherein the one or more frequencies is adjusted based at least in part on the movement which the subject is instructed to perform, and during or subsequent to performing the adjustment of the one or more frequencies, tracking the subject using the plurality of motion trackers of the motion tracking system.
Miller teaches a motion tracking system (fig. 11, user measurement device 1100) comprising at least one computing device (computing portion of UMD 1100 comprising processor 1106 with memory device 1108 with display 1112) and a plurality of motion trackers (fig. 11, physiological sensors 1102 and activity sensors 1104) in communication with the at least one computing device (computing portion of UMD 1100 comprising processor 1106 with memory device 1108 with display 1112) (Title “POWER MANAGEMENT FOR WEARABLE DEVICES”; Abstract “A method, system, apparatus, and/or device for adjusting a power consumption level of a device”; [0162] “measurement related to a living body, such as a human's body or an animal's body. The physiological measurement is a measurement made to assess body functions. Physiological measurements may be very simple, such as the measurement of body or ambient temperature, or they may be more complicated, for example measuring how well the heart is functioning by taking an ECG (electrocardiograph). Physiological measurements may also include motion and/or movement of the body. In some cases, these physiological measurements may be taken to determine an activity level”; [0125], [0163]-[0164] extensive lists of sensors), and configured to perform operations comprising: using a user interface (sensory devices comprising display 112) provided by the computing device (computing portion of UMD 1100 comprising processor 1106 with memory device 1108 with display 1112) to recommend a subject (user) to perform an activity which comprises movement of one or more body members of the subject (user) ([0145] “the UMD can include sensor devices to provide sensory indications to a user. In one example, the sensory device can be a visual sensory device, such as a display. The UMD can display information to a user using the visual sensory device. In another example, the sensory device can be an auditory sensory device, such as a speaker. The UMD can communicate information to a user using the auditory sensory device, such as communicating information to the user via the speaker. In another example, the sensory device can be a touch sensory device, such as a vibrator. The UMD can communicate information to a user using the touch sensory device. For example, the vibrator can vibrate for different periods of time or at different intervals to indicate different information to a user”; [0066] “communicate information to a display of the UMD. The information can include diagnosis information, recommended actions”; [0100] “The analysis tool can determine a change in the activity (e.g., a suggested or recommended course of action) of the user based on the measurements” and “when the analysis tool determines that an injury risk level has increased above a threshold level, the analysis tool can determine a change in user activities to decrease the injury risk level. For example, when the analysis tool determines an increased injury risk level, the analysis tool can determine that the user can decrease an amount of physical activity” and “determine a recommended course of action based on one or more measurements of the sensors of the UMD”; [0101] “analysis tool can identify an activity from multiple activities that may increase a heart rate of a user while not increasing a blood pressure level and dehydration level of the user. The analysis tool can communicate the identified activity to the user via a sensory indicator of the UMD or another computing device (such as a display)”; [0104] “activity (such as running)”; [0200] “type of activity can be a sports or athletic activity, such as running, football, basketball, soccer, baseball, hockey, and so forth”; [0080] “different activities can be different types of actions. The different types of actions can include: sleeping, sitting, walking, jogging, running, climbing, laying, standing, stepping, and so forth”); performing an adjustment of one or more frequencies (sample rates/frequencies) of one or more of the plurality of motion trackers (fig. 11, physiological sensors 1102 and activity sensors 1104) to reduce a power consumption of at least one of the plurality of motion trackers (fig. 11, physiological sensors 1102 and activity sensors 1104) to thereby reduce the power consumption of the motion tracking system (fig. 11, user measurement device 1100), wherein the one or more frequencies is adjusted based at least in part on the movement which the subject (user) is performing ([0033] “adjusting a frequency of taking physiological measurement”; [0165] “the PMM 1120 can determine an activity level based on an activity level (e.g., an activity-based PMM) and can adjust the default pattern in various ways as described in more detail below” and “sensor module 1122 can be programmed to measure a set of physiological measurement according to a default pattern. The default pattern may be the frequency, granularity, and power used for measurements by the physiological sensors” and “adjusting a frequency or granularity of taking physiological measurements; turning off one or more systems of the apparatus”; [0170] “the activity-based PMM 1120 determines a second sample rate for at least one of the multiple sensors (1102, 1104) using the determined amount of activity and instructs the sensor module 1125 to adjust the at least one of the multiple sensors to the second sample rate for a second set of physiological measurements. In some cases, the second sample rate is less than the corresponding one of the default sample rates. A lower sampling rate may cause the wearable UMD 1100 to consume less power when taking the second set of physiological measurements than when using the default sample rates to take the first set of physiological measurements”; [0171] “the activity-based PMM can instruct the sensor module 1122 to adjust the default sample rates to a second combination of different rates for the different ones of the multiple sensors”); and during or subsequent to performing the adjustment of the one or more frequencies, tracking the subject (user) using the plurality of motion trackers (fig. 11, physiological sensors 1102 and activity sensors 1104) of the motion tracking system (fig. 11, user measurement device 1100), wherein, during the tracking of the subject (user), one or more of the plurality of motion trackers (fig. 11, physiological sensors 1102 and activity sensors 1104) is disposed on or adjacent to the one or more body members of the subject (user) ([0146] “the UMD can be attached to different locations on a user's body using different UMD holders. For example, the UMD can be coupled with a wristband UMD holder to attach the UMD to a wrist position on the user. In another example, the UMD can be coupled with a headband UMD holder to attach the UMD to a head position (such as the forehead) on the user”; [0148] “The different UMD holders can position or align the UMD to engage the body differently based on the location of the UMD”; [0172] “the multiple sensors include a hardware motion sensor to measure at least one of movement or motion of the wearable UMD 1100. The activity-based PMM 1120 can determine the amount of activity based at least in part on the at least one of the movement or motion of the wearable UMD”; [0210] “a user can use multiple portable devices at the same time or substantially the same time. For example, the portable device can be a monitoring device that can be coupled to different locations of the body of the use”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Miller’s power management module and associated method of sampling rate/frequency adjustments for a motion tracking system with Marques motion tracking system for the expected advantages of saving power by both adjusting the default sampling pattern in accordance with the instructed to perform activity type and by dynamically reducing sampling rate/frequency and/or increasing accuracy/precision by increasing sampling rate/frequency based upon motion measured activity need. Complimentarily, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Marques’ body movement instruction via user interface with Miller’s motion tracking system thereby providing the expected advantages of providing physical exercise instruction and feedback including for therapy and/or rehabilitation and thus improving the physical condition of the user and/or reducing risk of further injury and/or improving the guidance including appropriate level of difficulty, as well as providing default activity identification for Miller’s activity-based power management and thus resulting in appropriate default values including default sampling rate/frequency from onset of the activity and thus providing proper measurements while balancing power consumption at said onset of the activity. The Examiner additionally notes that the Courts have ruled an obviousness analysis based on the collective teachings of the references does not depend on the order in which the references are listed in the statement of the rejection. See In re Bush, 296 F.2d 491, 496 (CCPA 1961): “In a case of this type where a rejection is predicated on two references each containing pertinent disclosure which has been pointed out to the applicant, we deem it to be of no significance, but merely a matter of exposition, that the rejection is stated to be on A in view of B instead of on B in view of A, or to term one reference primary and the other secondary.”
Regarding independent claim 20,
Marques teaches a non-transitory computer readable medium (fig. 1, memory 44) comprising instructions that, when executed by at least one computer processor (fig. 1, processor 42) (Title “DETERMINATION OF CAUSE OF DISCONNECTION OF SENSORS OF A MOTION TRACKING SYSTEM”; Abstract “computing device of a motion tracking system and one or more sensors of a plurality of sensors of the motion tracking system”; page 13, ll. 32-35 “a computer-readable storage medium comprising instructions which, when executed by a computing device, cause the computing device to carry out steps of a method”; page 14, ll. 31-34 “The computing device 40 includes at least one processor 42, at least one memory 44”), cause the at least one computer processor (fig. 1, processor 42) to perform operations comprising:
in a motion tracking system (fig. 1, motion tracking system 10) comprising a computing device (figs. 1-3, computing device 40) and a plurality of motion trackers (figs. 1-3, sensors 20) in communication with the computing device (figs. 1-3, computing device 40) (page 14, ll. 35-37 “wireless communications connections 50a-50n established between each sensor 20a-20n and the computing device 40 by means of the respective communications modules 38, 46”), using a user interface (not fully shown; means for providing at least one user perceptible signal) provided by the computing device (figs. 1-3, computing device 40) to instruct a subject (figs. 2-3, person 1) to perform a movement of one or more body members (body members of person 1) of the subject (figs. 2-3, person 1) (page 13, ll. 21-25 “the motion tracking system or the computing device comprises means for providing at least one user perceptible signal, whereas in some other embodiments, the computing device wirelessly communicates with means for providing at least one user perceptible signal that are not part of the motion tracking system. The means may be, for example, a screen, audio output means such as loudspeakers, etc.”; page 15 line 27 through page 16 line 7 “The computing device 40 may provide or command the provision of examples and guidance on which movements/exercises are to be performed by the person 1 when activity thereof is to be tracked with the motion tracking system”); and
tracking the subject (figs. 2-3, person 1) using the plurality of motion trackers (figs. 1-3, sensors 20) of the motion tracking system (fig. 1, motion tracking system 10), wherein, during the tracking of the subject (figs. 2-3, person 1), one or more of the plurality of motion trackers (figs. 1-3, sensors 20) is disposed on or adjacent to the one or more body members (body members of person 1) of the subject (figs. 2-3, person 1) (page 15, ll. 22-26 “The sensors 20a-20e track the motion of the body members having a sensor 20a-20e arranged thereon; they transmit the orientation measurements to the computing device 40, which in turn determines and provides a movement sequence of said body members and, possibly, of other body members with no sensors arranged thereon by means of digital processing of the measurements”).
Marques does not teach adjustment of (sampling) frequencies of motion trackers including: performing an adjustment of one or more frequencies of one or more of the plurality of motion trackers to reduce a power consumption of at least one of the plurality of motion tracker to thereby reduce the power consumption of the motion tracking system, wherein the one or more frequencies is adjusted based at least in part on the movement which the subject is instructed to perform, and during or subsequent to performing the adjustment of the one or more frequencies, tracking the subject using the plurality of motion trackers of the motion tracking system.
Miller teaches a non-transitory computer readable medium (non-transitory computer readable storage medium) comprising instructions that, when executed by at least one computer processor (computer), cause the at least one computer processor (computer) to perform operations (Title “POWER MANAGEMENT FOR WEARABLE DEVICES”; Abstract “A method, system, apparatus, and/or device for adjusting a power consumption level of a device”; [0230] “Various techniques, or certain aspects or portions thereof, may take the form of program code (i.e., instructions) embodied in tangible media, such as floppy diskettes, CD-ROMs, hard drives, non-transitory computer readable storage medium, or any other machine-readable storage medium wherein, when the program code is loaded into and executed by a machine, such as a computer, the machine becomes an apparatus for practicing the various techniques”) comprising: in a motion tracking system (fig. 11, user measurement device 1100) comprising a computing device (computing portion of UMD 1100 comprising processor 1106 with memory device 1108 with display 1112) and a plurality of motion trackers (fig. 11, physiological sensors 1102 and activity sensors 1104) in communication with the computing device (computing portion of UMD 1100 comprising processor 1106 with memory device 1108 with display 1112) ([0162] “measurement related to a living body, such as a human's body or an animal's body. The physiological measurement is a measurement made to assess body functions. Physiological measurements may be very simple, such as the measurement of body or ambient temperature, or they may be more complicated, for example measuring how well the heart is functioning by taking an ECG (electrocardiograph). Physiological measurements may also include motion and/or movement of the body. In some cases, these physiological measurements may be taken to determine an activity level”; [0125], [0163]-[0164] extensive lists of sensors), using a user interface (sensory devices comprising display 112) provided by the computing device (computing portion of UMD 1100 comprising processor 1106 with memory device 1108 with display 1112) to recommend a subject (user) to perform an activity which comprises movement of one or more body members of the subject (user) ([0145] “the UMD can include sensor devices to provide sensory indications to a user. In one example, the sensory device can be a visual sensory device, such as a display. The UMD can display information to a user using the visual sensory device. In another example, the sensory device can be an auditory sensory device, such as a speaker. The UMD can communicate information to a user using the auditory sensory device, such as communicating information to the user via the speaker. In another example, the sensory device can be a touch sensory device, such as a vibrator. The UMD can communicate information to a user using the touch sensory device. For example, the vibrator can vibrate for different periods of time or at different intervals to indicate different information to a user”; [0066] “communicate information to a display of the UMD. The information can include diagnosis information, recommended actions”; [0100] “The analysis tool can determine a change in the activity (e.g., a suggested or recommended course of action) of the user based on the measurements” and “when the analysis tool determines that an injury risk level has increased above a threshold level, the analysis tool can determine a change in user activities to decrease the injury risk level. For example, when the analysis tool determines an increased injury risk level, the analysis tool can determine that the user can decrease an amount of physical activity” and “determine a recommended course of action based on one or more measurements of the sensors of the UMD”; [0101] “analysis tool can identify an activity from multiple activities that may increase a heart rate of a user while not increasing a blood pressure level and dehydration level of the user. The analysis tool can communicate the identified activity to the user via a sensory indicator of the UMD or another computing device (such as a display)”; [0104] “activity (such as running)”; [0200] “type of activity can be a sports or athletic activity, such as running, football, basketball, soccer, baseball, hockey, and so forth”; [0080] “different activities can be different types of actions. The different types of actions can include: sleeping, sitting, walking, jogging, running, climbing, laying, standing, stepping, and so forth”); performing an adjustment of one or more frequencies (sample rates/frequencies) of one or more of the plurality of motion trackers (fig. 11, physiological sensors 1102 and activity sensors 1104) to reduce a power consumption of at least one of the plurality of motion trackers (fig. 11, physiological sensors 1102 and activity sensors 1104) to thereby reduce the power consumption of the motion tracking system (fig. 11, user measurement device 1100), wherein the one or more frequencies is adjusted based at least in part on the movement which the subject (user) is performing ([0033] “adjusting a frequency of taking physiological measurement”; [0165] “the PMM 1120 can determine an activity level based on an activity level (e.g., an activity-based PMM) and can adjust the default pattern in various ways as described in more detail below” and “sensor module 1122 can be programmed to measure a set of physiological measurement according to a default pattern. The default pattern may be the frequency, granularity, and power used for measurements by the physiological sensors” and “adjusting a frequency or granularity of taking physiological measurements; turning off one or more systems of the apparatus”; [0170] “the activity-based PMM 1120 determines a second sample rate for at least one of the multiple sensors (1102, 1104) using the determined amount of activity and instructs the sensor module 1125 to adjust the at least one of the multiple sensors to the second sample rate for a second set of physiological measurements. In some cases, the second sample rate is less than the corresponding one of the default sample rates. A lower sampling rate may cause the wearable UMD 1100 to consume less power when taking the second set of physiological measurements than when using the default sample rates to take the first set of physiological measurements”; [0171] “the activity-based PMM can instruct the sensor module 1122 to adjust the default sample rates to a second combination of different rates for the different ones of the multiple sensors”); and during or subsequent to performing the adjustment of the one or more frequencies, tracking the subject (user) using the plurality of motion trackers (fig. 11, physiological sensors 1102 and activity sensors 1104) of the motion tracking system (fig. 11, user measurement device 1100), wherein, during the tracking of the subject (user), one or more of the plurality of motion trackers (fig. 11, physiological sensors 1102 and activity sensors 1104) is disposed on or adjacent to the one or more body members of the subject (user) ([0146] “the UMD can be attached to different locations on a user's body using different UMD holders. For example, the UMD can be coupled with a wristband UMD holder to attach the UMD to a wrist position on the user. In another example, the UMD can be coupled with a headband UMD holder to attach the UMD to a head position (such as the forehead) on the user”; [0148] “The different UMD holders can position or align the UMD to engage the body differently based on the location of the UMD”; [0172] “the multiple sensors include a hardware motion sensor to measure at least one of movement or motion of the wearable UMD 1100. The activity-based PMM 1120 can determine the amount of activity based at least in part on the at least one of the movement or motion of the wearable UMD”; [0210] “a user can use multiple portable devices at the same time or substantially the same time. For example, the portable device can be a monitoring device that can be coupled to different locations of the body of the use”).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Miller’s power management module and associated method of sampling rate/frequency adjustments for a motion tracking system with Marques motion tracking system for the expected advantages of saving power by both adjusting the default sampling pattern in accordance with the instructed to perform activity type and by dynamically reducing sampling rate/frequency and/or increasing accuracy/precision by increasing sampling rate/frequency based upon motion measured activity need. Complimentarily, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Marques’ body movement instruction via user interface with Miller’s motion tracking system thereby providing the expected advantages of providing physical exercise instruction and feedback including for therapy and/or rehabilitation and thus improving the physical condition of the user and/or reducing risk of further injury and/or improving the guidance including appropriate level of difficulty, as well as providing default activity identification for Miller’s activity-based power management and thus resulting in appropriate default values including default sampling rate/frequency from onset of the activity and thus providing proper measurements while balancing power consumption at said onset of the activity. The Examiner additionally notes that the Courts have ruled an obviousness analysis based on the collective teachings of the references does not depend on the order in which the references are listed in the statement of the rejection. See In re Bush, 296 F.2d 491, 496 (CCPA 1961): “In a case of this type where a rejection is predicated on two references each containing pertinent disclosure which has been pointed out to the applicant, we deem it to be of no significance, but merely a matter of exposition, that the rejection is stated to be on A in view of B instead of on B in view of A, or to term one reference primary and the other secondary.”
Regarding claim 2, which depends on claim 1,
the previous combination (see analysis of independent claim) of Marques and (especially) Miller suggests wherein the one or more frequencies (Miller: sampling rate/frequencies) is adjusted by one or more corresponding adjustment values based at least in part on a body member (location on the user) of the one or more body members (body members of person/user) associated with the one or more motion trackers (Marques: figs. 1-3, sensors 20. Miller: fig. 11 sensors 1102 & 1104) (Miller: [0210] “portable device can be a monitoring device that can be coupled to different locations of the body of the user. In one example, the multiple portable devices can communicate with each other. In one example, the power management system can adjust the power consumption level of one or more of the portable device in view of the number of devices being used at the same time”; [0146] “the UMD can be attached to different locations on a user's body using different UMD holders. For example, the UMD can be coupled with a wristband UMD holder to attach the UMD to a wrist position on the user. In another example, the UMD can be coupled with a headband UMD holder to attach the UMD to a head position (such as the forehead) on the user”; [0147] “positioning the UMD at different locations on a user can be to enable optimal measurement taking for different types of measurements. For example, when a user desires to take a hydration measurement, the wrist may be an optimal location and the UMD can be coupled to the user with a wristband UMD holder. In this example, when a user desires to take an impact measurement, the forehead may be an optimal location and the UMD can be coupled to the user with a forehead UMD holder”; [0155] “When a UMD engages the body and takes a measurement at different locations, the measurements may be calibrated for the different locations” and “For example, when a first UMD takes measurements at a first location on the wrist and a second UMD takes measurements at a second location on the wrist, the first and second UMD may be calibrated differently based on the different locations and may provide different measurement information”; [0165] “For example, the sensor module 1122 can be programmed to measure a set of physiological measurement according to a default pattern. The default pattern may be the frequency, granularity, and power used for measurements by the physiological sensors”; [0168] “For example, when the user wants a hydration measurement, the device may only use a certain subset or may adjust a sample rate of one sensor to have higher granularity when measuring hydration”; [0221] “the activity levels can be separated by multiple thresholds and depending on the measured activity level, corresponding patterns may be selected. In one embodiment, the different patterns are different sampling rates used to take physiological measurements. Alternatively, the different patterns can have any combination of the following: different numbers of sensors being used to take physiological measurements; different number of different physiological measurements to take; different frequency or different granularity of taking physiological measurements”. The Examiner emphasizes that the sampling rate is calibrated & optimally adjusted to the particular location of the particular sensor and particular measurement type; see also citations provided for independent claim for additional details.).
Regarding claim 3, which depends on claim 1,
the previous combination (see analysis of independent claim) of Marques and (especially) Miller suggests wherein the adjustment of the one or more frequencies (Miller: sampling rate/frequencies) comprises adjusting the one or more frequencies (Miller: sampling rate/frequencies) of each of the plurality of motion trackers (Marques: figs. 1-3, sensors 20. Miller: fig. 11, sensors 1102 & 1104) (Miller: [0211] “the power management system can adjust the power consumption level of each of the multiple devices to different power consumption levels based on device criteria” and “each of the multiple devices can have different device criteria”; [0167] “To perform the power adjustment activity when appropriate, the PMM 1120 adjusts the first sampling rate”; [0168] “the PMM 1120 adjust a sampling rate of at least one of the first set of sensors that is not in the subset in order to reduce power consumption”; [0170] “the PMM 1120 is considered an activity-based PMM where the activity-based PMM, when executed by the processor 1106, identifies default sample rates at which the sensor module 1125 takes a first set of physiological measurements with multiple sensors” and “the activity-based PMM 1120 determines a second sample rate for at least one of the multiple sensors (1102, 1104) using the determined amount of activity and instructs the sensor module 1125 to adjust the at least one of the multiple sensors to the second sample rate for a second set of physiological measurements”; [0171] “the default sample rates is a first combination of different rates for different ones of the multiple sensors and the activity-based PMM can instruct the sensor module 1122 to adjust the default sample rates to a second combination of different rates for the different ones of the multiple sensor”. See also citations provided for independent claim for additional details.).
Regarding claim 4, which depends on claim 1,
the previous combination (see analysis of independent claim) of Marques and (especially) Miller suggests wherein the adjustment of the one or more frequencies (Miller: sampling rate/frequencies) comprises adjusting the one or more frequencies (Miller: sampling rate/frequencies) based at least in part on a level of motion associated with the subject (person/user), as determined by a previously recorded (recorded via memory device 1108) measurement of the subject (person/user) by the motion tracking system (fig. 1, motion tracking system 10) (Miller: [0061] “can store the historical information on a memory device of the UMD”; [0165] “memory device 1108 may also store activity data 1124. The activity data 1124 may be current and past measurements, as well as predictive data for predictive modeling of the activity level”; [0166] “The amount of activity could be movement or motion of the wearable UMD 1100” and “the physiological measurements may be stored in the memory device 1108 as physiological data and the activity measurements (indicative of the activity level) may be stored in the memory device 1108 as the activity data 1124. When determining the activity level, the processing element (or PMM 1120) may process the activity data 1124 to determine an activity level and the appropriate power adjustment activity”; [0172] “measure at least one of movement or motion of the wearable UMD 1100. The activity-based PMM 1120 can determine the amount of activity based at least in part on the at least one of the movement or motion of the wearable UMD 110”; [0170] “The activity-based PMM determines an amount of activity of the wearable UMD 1100 based on at least one of the first set of physiological measurements. For example, the first set of physiological measurements may include measurements from the activity sensor(s) 1104 that are primarily used to determine an activity level. The activity-based PMM 1120 may compare the determined activity level against one or more threshold levels to determine an activity level and corresponding power adjustment activity. In one embodiment, the activity-based PMM 1120 determines a second sample rate for at least one of the multiple sensors (1102, 1104) using the determined amount of activity and instructs the sensor module 1125 to adjust the at least one of the multiple sensors to the second sample rate for a second set of physiological measurements”; [0175] “the wearable device can use the activity sensor to measure an amount of activity (such as movement or motion) of the wearable device and communicate the amount of activity of the wearable device to the power management system. The power management system can adjust an amount of power used by the wearable device in view of the amount of activity measured by the activity sensor. For example, when the power management system determines that an activity rate of the user is relatively low (such as the user sitting down or resting), the power management system can reduce a sample rate duty cycle to provide a low power “sleep mode” during the lower activity level periods. An advantage of adjusting the sample rate duty cycle based on an activity level of the user can be to reduce a power consumption of the device during lower activity periods while maintaining high fidelity measurements during periods of relatively high activity”; [0197] “the measurement granularity level (which correlates with the power consumption level) can be adjusted in view of the fitness level of the individual using the portable device”. See also citations provided for independent claim for additional details.).
Regarding claim 5, which depends on claim 1,
the previous combination (see analysis of independent claim) of Marques and (especially) Miller suggests wherein the tracking of the subject (person/user) is performed during the adjustment of the one or more frequencies (Miller: sampling rate/frequencies) (Miller: [0075] “real-time input data of a user”; [0114] “input data in real-time”; [0161] “real-time data”; [0175] “the power management system can reduce a sample rate duty cycle to provide a low power “sleep mode” during the lower activity level periods. An advantage of adjusting the sample rate duty cycle based on an activity level of the user can be to reduce a power consumption of the device during lower activity periods while maintaining high fidelity measurements during periods of relatively high activity”; [0202] “continuously adjust the power consumption level” and “the power management system can perform a power adjustment activity automatically (such as reducing a sample rate of one or more sensors)”; [0175] “The power management system can adjust an amount of power used by the wearable device in view of the amount of activity measured by the activity sensor. For example, when the power management system determines that an activity rate of the user is relatively low (such as the user sitting down or resting), the power management system can reduce a sample rate duty cycle to provide a low power “sleep mode” during the lower activity level periods. An advantage of adjusting the sample rate duty cycle based on an activity level of the user can be to reduce a power consumption of the device during lower activity periods while maintaining high fidelity measurements during periods of relatively high activity”. See also citations provided for independent claim for additional details.).
Regarding claim 6, which depends on claim 5,
the previous combination (see analysis of independent claim) of Marques and (especially) Miller suggests further comprising, subsequent to the adjustment of the one or more frequencies (Miller: sampling rate/frequencies), performing an additional adjustment of the one or more frequencies (Miller: sampling rate/frequencies) of one or more of the plurality of motion trackers (Marques: figs. 1-3, sensors 20. Miller: fig. 11, sensors 1102 & 1104) during the performance of the movement by the subject (person/user) to further reduce the power consumption of the at least one of the plurality of motion trackers (Marques: figs. 1-3, sensors 20. Miller: fig. 11, sensors 1102 & 1104) (Miller: Abstract “for adjusting a power consumption level of a device”; [0075]; [0114]; [0161]; [0175] “the power management system can reduce a sample rate duty cycle to provide a low power “sleep mode” during the lower activity level periods. An advantage of adjusting the sample rate duty cycle based on an activity level of the user can be to reduce a power consumption of the device during lower activity periods while maintaining high fidelity measurements during periods of relatively high activity”; [0202] “continuously adjust the power consumption level” and “the power management system can perform a power adjustment activity automatically (such as reducing a sample rate of one or more sensors)”; [0175] “The power management system can adjust an amount of power used by the wearable device in view of the amount of activity measured by the activity sensor. For example, when the power management system determines that an activity rate of the user is relatively low (such as the user sitting down or resting), the power management system can reduce a sample rate duty cycle to provide a low power “sleep mode” during the lower activity level periods. An advantage of adjusting the sample rate duty cycle based on an activity level of the user can be to reduce a power consumption of the device during lower activity periods while maintaining high fidelity measurements during periods of relatively high activity”; [0164] “power management activities may be performed to reduce the power consumption of the wearable UMD 1100 in response to the determination of the activity level. In other cases, the power management activities may be performed to increase measurement granularity or increase accuracy, precision, or resolution of the measurements by the wearable UMD 1100”; [0168] “further reduce power consumption by the wearable UMD 1100”; [0221] “the activity levels can be separated by multiple thresholds and depending on the measured activity level, corresponding patterns may be selected. In one embodiment, the different patterns are different sampling rates used to take physiological measurements”; [0136] “measurement data threshold ranges, measurement data threshold values, measurement event triggering values, and so forth”. See also citations provided for preceding claims for additional details.).
Regarding claim 7, which depends on claim 6,
the previous combination (see analysis of independent claim) of Marques and (especially) Miller suggests wherein the additional adjustment is based at least in part on a measured level of motion of the one or more motion trackers (Marques: figs. 1-3, sensors 20. Miller: fig. 11, sensors 1102 & 1104) (Miller: Abstract “for adjusting a power consumption level of a device”; [0075]; [0114]; [0161]; [0175] “the power management system can reduce a sample rate duty cycle to provide a low power “sleep mode” during the lower activity level periods. An advantage of adjusting the sample rate duty cycle based on an activity level of the user can be to reduce a power consumption of the device during lower activity periods while maintaining high fidelity measurements during periods of relatively high activity”; [0202] “continuously adjust the power consumption level” and “the power management system can perform a power adjustment activity automatically (such as reducing a sample rate of one or more sensors)”; [0175] “can use the activity sensor to measure an amount of activity (such as movement or motion) of the wearable device and communicate the amount of activity of the wearable device to the power management system. The power management system can adjust an amount of power used by the wearable device in view of the amount of activity measured by the activity sensor. For example, when the power management system determines that an activity rate of the user is relatively low (such as the user sitting down or resting), the power management system can reduce a sample rate duty cycle to provide a low power “sleep mode” during the lower activity level periods. An advantage of adjusting the sample rate duty cycle based on an activity level of the user can be to reduce a power consumption of the device during lower activity periods while maintaining high fidelity measurements during periods of relatively high activity”; [0164] “power management activities may be performed to reduce the power consumption of the wearable UMD 1100 in response to the determination of the activity level. In other cases, the power management activities may be performed to increase measurement granularity or increase accuracy, precision, or resolution of the measurements by the wearable UMD 1100”; [0168] “further reduce power consumption by the wearable UMD 1100”; [0221] “the activity levels can be separated by multiple thresholds and depending on the measured activity level, corresponding patterns may be selected. In one embodiment, the different patterns are different sampling rates used to take physiological measurements”; [0136] “measurement data threshold ranges, measurement data threshold values, measurement event triggering values, and so forth”; [0033] “Physiological measurements may also include motion and/or movement of the body, including measures of speed, acceleration, position, absolute or relative location, or the like. In some cases, these physiological measurements may be taken to determine an activity level for power management”; [0162] “Physiological measurements may also include motion and/or movement of the body. In some cases, these physiological measurements may be taken to determine an activity level for power management”; [0166] “amount of activity could be movement or motion of the wearable UMD 1100, as well as other measurements indicative of the activity level of a user”; [0172] “activity-based PMM 1120 can determine the amount of activity based at least in part on the at least one of the movement or motion of the wearable UMD 110. The hardware motion sensor may be an accelerometer sensor, a gyroscope sensor, a magnetometer”. See also citations provided for preceding claims for additional details.).
Regarding claim 8, which depends on claim 7,
the previous combination (see analysis of independent claim) of Marques and (especially) Miller suggests wherein a magnitude of the additional adjustment is based on the measured level of motion and a range of motion (e.g., jumping height, lateral movement measurement, range of activity indicating sleep/awake or other action) associated with the movement which the subject (person/user) is instructed to perform (Miller: Abstract; [0075]; [0114]; [0161]; [0175]; [0202]; [0175]; [0164]; [0168]; [0221]; [0136]; [0033]; [0162]; [0166]; [0172]; [0065] “activity intensity can be measured based on acceleration during a run, deceleration during the run, speed of the run, jumping height, lateral movement”; [0077] “determine a baseline range measurement of a user by determining a reoccurring or repetitive range of measurements of the user over a period of time”; [0078] “can correlate different measurement ranges for different measurements and/or different diagnoses”; [0125] “selected threshold measurement range”; [0136] “measurement data threshold ranges, measurement data threshold values, measurement event triggering values, and so forth”; [0088] “activity level” and “can use predefined ranges or levels to determine when the user enters each sleep stage”; [0080] “different activities can be different types of actions. The different types of actions can include: sleeping, sitting, walking, jogging, running, climbing, laying, standing, stepping, and so forth”. See also citations provided for preceding claims for additional details.).
Regarding claim 9, which depends on claim 1,
the previous combination (see analysis of independent claim) of Marques and (especially) Miller suggests further comprising adjusting a transmission frequency of at least one of the plurality of motion trackers (Marques: figs. 1-3, sensors 20. Miller: fig. 11, sensors 1102 & 1104) such that substantially no transmission occurs (e.g., turning off and/or adjusting transceiving) when the at least one of the plurality of motion trackers (Marques: figs. 1-3, sensors 20. Miller: fig. 11 sensors, 1102 & 1104) is motionless (e.g., recognized activity actions such as sleeping, resting, sitting, laying, standing) (Miller: Abstract; [0075]; [0114]; [0161]; [0175]; [0202]; [0175]; [0164]; [0168]; [0221]; [0136]; [0033]; [0162]; [0166]; [0172]; [0065]; [0077]; [0078]; [0125]; [0136]; [0088]; [0080]; [0165] “power management module (PMM) 1120, which perform various operations described herein. In particular, the sensor module 1122 can perform operations to control the physiological sensors 1102 and activity sensors 1104, such as when to turn them on and off, when to take a measurement, how many measurements to take, how often to perform measurements, etc.” and “adjusted by adjusting a sampling rate; adjusting a number of sensors to take physiological measurements; adjusting a number of different physiological measurements to take; adjusting a frequency or granularity of taking physiological measurements; turning off one or more systems of the apparatus; adjusting a type of communication channel to transmit or receive data; adjusting a frequency at which to transmit or receive data; adjusting a power level to transmit or receive data; adjusting a data rate to transmit or receive data; adjusting a number of different channels to transmit or receive data, or the like”; [0168] “the PMM 1120 turns off at least one of the first set of sensors that is not in the subset to further reduce power consumption by the wearable UMD 1100”; [0169] “the PMM 1120 is able to turn off other components of the wearable UMD 1100, such as an RF circuit Ill 0 used to communicate data via antenna 1116 or display 1112. Alternatively, the PMM 1120 may activate, de-activate, turn on, turn-off, enable, or disable other components of the wearable UMD 1100 according to the measurement pattern defined for the activity level”; [0175] “when the power management system determines that an activity rate of the user is relatively low (such as the user sitting down or resting), the power management system can reduce a sample rate duty cycle to provide a low power “sleep mode” during the lower activity level periods. An advantage of adjusting the sample rate duty cycle based on an activity level of the user can be to reduce a power consumption of the device during lower activity periods while maintaining high fidelity measurements during periods of relatively high activity”; [0177] “turning on or off one or more systems of the wearable device (such as a display or communications system), and so forth. The portable device (such as a wearable device) can include a communication module to transceive data (e.g., send and receive data). In another example, the power adjustment activities can include: adjusting a type of communication channel used to transceive data, such as via the Bluetooth®, Wi-Fi®, cellular technologies and so forth; a frequency in time or rate that the portable device sends or receives data; an amount of power used to send or receive data, such as adjusting a broadcast power used, an amount of power used to receive a signal, a data rate that data can be sent or received; a number of different channels or communication types the portable device may use, such as dual-band or multi-band communications; and so forth”; [0178] “determine that an activity level of the user of the wearable device is below a threshold level (such as when the user is resting or sitting down)” and “when a user is inactive (e.g. the activity level of the user is below a threshold level) then a rate of change in the one or more measurements taken by the wearable device is lower relative to when the user is active (e.g. the activity level of the user exceeds a threshold level)”; [0181] “determine when a user may switch from sleeping to awake” and “determine a transition or change in activity level can be to reduce or eliminate using background monitoring (e.g., a full sleep mode)”; [0208] “the power management system can use a non-communication setting to turn off the communications or data transfer”; [0209] “put the sensors in sleep mode or turn the sensors oft”; [0213] “power consumption options can include: a power off mode, where the device is turned off; a heartbeat mode, where the device runs on minimal power and wakes up to take measurements at selected periods of time or at selected events; a minimum power mode, where the portable device can continue to monitor the user but turn on one or more options on the portable device (such as a display screen, a speaker) and/or reduce the measurement granularity of the sensor measurements; a full power mode”; [0217] “power management system can decrease the measurement granularity of that sensor of the portable device or turn the sensor of the portable device off”; [0221], [0226] “components being turned on or off during a period; different combinations of permitted communication types, frequencies, power levels, data rates, communication channels to transmit or receive data using one or more RF circuits components of the system”. See also citations provided for preceding claims for additional details.).
Regarding claim 10, which depends on claim 9,
Marques reasonably teaches (additional obviousness analysis for narrower interpretation follows) further comprising:
detecting, by the motion tracking system (Marques: fig. 1, motion tracking system 10), that the at least one of the plurality of motion trackers (Marques: figs. 1-3, sensors 20) is motionless (no motion signal / signal lost) (the Examiner’s position is that a detected malfunction/failure/error of an expected motion tracker signal is a detection of motionlessness or at least at once so envisaged therefrom);
determining that the at least one of the plurality of motion trackers (Marques: figs. 1-3, sensors 20) is not expected to be motionless (no motion signal / signal lost) within a tracked motion range (range of properly performing the movement/exercise) associated with the movement which the subject (person/user) is instructed to perform (guidance, such as from therapist or fitness instructor) (the Examiner’s position is that determining a malfunction/failure/error of an expected motion tracker signal is a determination that the motion tracker is unexpectedly motionless or at least at once so envisaged therefrom);
halting tracking of the movement (halting the provision of the movement sequence) (the Examiner’s position is that halting the provision of the movement is halting the tracking of the movement or at least at once so envisaged therefrom); and
providing an alert (warning/notification) of a fault condition (malfunction/failure/error) of the motion tracking system (fig. 1, motion tracking system 10) (page 1, ll. 28-31 “As the person is wearing the sensors, i.e. has the sensors arranged on a body thereof, the person may for example inadvertently move away from the computing device and lose connection between the computing device and one, some or all sensors due to the limited range of the communications, thereby halting the provision of the movement sequence”; page 15 line 26 through page 16 line 7 “The computing device 40 is capable of digitally comparing the movement sequences with the prescribed movements and/or physical exercises that the person 1 is to reproduce, and provide feedback to the person and/or the therapist or fitness instructor so as to inform whether the same are being correctly performed by the person, or whether the person has not moved one or more body members in accordance with the prescribed movements or exercises. Also, the feedback provided by the computing device 40 may indicate which body members have not been moved correctly and/or provide guidance on how to properly perform the movement or exercise. The motion tracking, the processing by the computing device 40 and the feedback provision are important for the correct rehabilitation and/or improvement of the physical condition of the person because, otherwise, the injury or physical condition of the person 1 may worsen” and “computing device 40 may provide or command the provision of examples and guidance on which movements/exercises are to be performed by the person 1 when activity thereof is to be tracked with the motion tracking system”; page 3 line 35 through page 4 line 10 “In the event that it is determined that one or some sensors, but fewer than the predetermined sensors threshold, have lost connection for this reason, it is considered that the disconnection is due to another phenomenon, e.g. due to a hardware failure, a software error, interferences, etc.”; page 4, ll. 17-21 “provision of at least one user perceptible signal indicative of: a warning that one or more sensors have lost connection with the computing device, a cause of disconnection being an interference or a malfunction of the motion tracking system, or an indication that the person should attempt a connection reestablishment”; page 4, ll. 24-33 “transmitting a notification to a computing apparatus remote from the computing device that is indicative of: a warning that one or more sensors have lost connection with the computing device, or a cause of disconnection being an interference or a malfunction of the motion tracking system. The person is notified of the existence of a problem in the wireless communications connections so that she/he may attempt to perform a corrective action”).
The Examiner acknowledges that Marques does not explicitly state a narrower interpretation: determining that a motion tracker is motionless—beyond a suspected disconnection type error—and halting tracking of movement while providing an alert of the fault condition.
However, choosing from a finite number of identified, predictable solutions, with a reasonable expectation of success is obvious to try, see MPEP § 2143(I)(E). The Examiner also notes that MPEP § 2145(III)(X)(B) states “An “obvious to try” rationale may support a conclusion that a claim would have been obvious where one skilled in the art is choosing from a finite number of identified, predictable solutions, with a reasonable expectation of success. “[A] person of ordinary skill has good reason to pursue the known options within his or her technical grasp. If this leads to the anticipated success, it is likely that product [was] not of innovation but of ordinary skill and common sense. In that instance the fact that a combination was obvious to try might show that it was obvious under § 103.” KSR Int'l Co. v. Teleflex Inc., 550 U.S. 538, 421,82 USPQ2d 1385, 1397 (2007).” In the present case, Marques explicitly teaches that the feedback provision are important for the correct rehabilitation and/or improvement of the physical condition of the person because, otherwise, the injury or physical condition of the person may worsen, and therefore it nevertheless would have further been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to so halt tracking and provide a fault alert when an expected motion from a motion tracker is motionless—even when a disconnection is not the reason--thereby providing the commonsense and reasonable expectation of preventing injury or physical condition to worsen from failure to detect proper motion and provide important feedback thereto for correct rehabilitation &/or improvement of a physical condition.
Regarding claim 18, which depends on claim 1,
Marques is silent to wherein each of the plurality of motion trackers is powered by a battery.
However:
The Examiner takes Official Notice that batteries for powering portable sensors is conventional in the art.
Furthermore, and as supporting factual evidence of the aforementioned assertion, Miller teaches wherein a plurality of motion trackers (fig. 11, physiological sensors 1102 and activity sensors 1104) are each powered by a battery ([0211] “battery power”; [0212] “the portable device can include a swappable battery pack” and “portable device can have an internal battery”).
In view of the above, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine a conventional battery—as factually supported by Miller’s battery powered devices—with each of Marques’ motion trackers for the expected purpose(s) of providing power without requiring wiring which could be cumbersome, without requiring power generation/scavenging which can be expensive and/or undependable, and/or for being more convenient to replace/recharge with minimal effort/expertise. With respect to each/all trackers being powered by a battery, it further would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to standardize battery usage for the expected purpose of providing consistent manufacturing standards and/or use of all such trackers including for commercial reasons such as consumer expectations.
Claim(s) 11-12 is/are rejected under 35 U.S.C. 103 as being unpatentable over newly cited Marques in view of newly cited Miller and in further view of newly cited Ramalho et al (WO 2021048022 A1; hereafter “Ramalho”).
Regarding claim 11 and claim 12, where claim 11 depends on claim 1 and where claim 12 depends on claim 11, as best understood,
Marques reasonably teaches wherein the plurality of motion trackers (figs. 1-3, sensors 20) each comprises an inertial measurement unit (at once so envisaged; additional obviousness analysis follows), (claim 12 limitation follows) wherein the inertial measurement unit comprises at least two of an accelerometer, a gyroscope, and a magnetometer (page 1, ll. 15-19 “sensors for motion tracking a target may include one or more sensing devices such as gyroscopes, accelerometers, magnetometers, etc. A computing device that is connected to the sensors processes the measurements of one or several of these sensing devices, and determines the movement sequence of the target, at least the movement sequence of the tracked parts of the target (i.e. those with a sensor arranged thereon)”; page 9, ll. 13-15 “each sensor of the plurality of sensors at least comprises a gyroscope. In some embodiments, each sensor of the plurality of sensors further comprises 15 an accelerometer and/or a magnetometer"; page 19 line 31 through page 20 line 11 “The computing device evaluates the time evolution of the heading of the sensors by processing the orientation measurements (from which the computing devices gathers or derives the heading angle, as known in the art for different types of sensing devices, e.g. gyroscopes, accelerometers, magnetometers, etc.)”; Examiner emphasizes with respect to IMU, that an ordinary artisan would at once envisage that a motion tracker comprising a plurality of accelerometers, gyroscopes, and magnetometers is reasonably nomenclaturally equivalent to an IMU; likewise an ordinary artisan would at once envisage the at least two of each of the aforementioned sensors).
The Examiner acknowledges that Marques (and likewise Miller who also teaches accelerometers/ gyroscopes/magnetometers) does not explicitly state wherein the plurality of motion trackers each comprises an inertial measurement unit (IMU), wherein the inertial measurement unit comprises at least two of each of an accelerometer, a gyroscope, and a magnetometer.
However:
The Examiner takes Official Notice that it is conventional to implement a motion tracker that comprises gyroscopes, accelerometers, & magnetometers as an IMU.
Furthermore, and as supporting factual evidence of the aforementioned assertion, Ramalho teaches wherein the plurality of motion trackers each comprises an inertial measurement unit, wherein the inertial measurement unit comprises at least two of each of an accelerometer, a gyroscope, and a magnetometer (Title “DETECTION OF INCORRECT ARRANGEMENT OF INERTIAL MEASUREMENTS UNITS OF A MOTION TRACKING SYSTEM”; Abstract “A method for physical exercise of a person using a motion tracking system, the motion tracking system comprising a computing device and a plurality of inertial measurement units adapted to be arranged on body members of the person”; page 1, ll. 19-27 “The motion tracking system may include inertial measurements units, i.e. IMUs, for motion tracking of a target; the IMUs are adapted to be arranged on the target and may include one or more sensing devices such as gyroscopes, accelerometers, magnetometers, etc. The computing device is connected to the IMUs and processes the measurements of one or several of these sensing devices, and by processing said measurements the computing device determines the movement sequence of the target, at least the movement sequence of the tracked parts of the target (i.e. those with an IMU arranged thereon)”; page 3, ll. 8-19 “measurements includes e.g. orientations and/or accelerations of respective units, which can be provided by e.g. a gyroscope, an accelerometer, a magnetometer, or a combination thereof”; page 3 line 20 through page 4 line 4 “IMUs for determining the movement sequence of the person or at least the tracked parts thereof.”).
In view of the above, either one of ordinary skill in the art at the time the invention was effectively filed would at once envisaged that Marques reasonably teaches an IMU, or nevertheless, or in the alternative, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine a conventional IMU configuration—as factually supported by Ramalho’s IMU for motion tracking—with Marques’ inertial measuring motion tracking sensors comprising gyroscopes, accelerometers, & magnetometers thereby providing the expected advantage of combining the measurements of the aforementioned sensors to accurately measure linear acceleration, angular velocity, and magnetic field orientation, wherein the integration allows for a single unit to perform multiple functions, simplifying the design and implementation of devices that require precise motion tracking and orientation detection. With further respect to the number of each of the accelerometer, gyroscopes, and magnetometers, the Examiner notes that it has been held that mere duplication of the essential working parts of a device involves only routine skill in the art, see MPEP § 2144.04(VI)(B), St. Regis Paper Co. v. Bemis Co., 193 USPQ 8 (7th Cir. 1977), and In re Harza, 274 F.2d 669, 124 USPQ 378 (CCPA 1960). In the present case it is the Examiner's position that only ordinary skill in the art is required to provide a plurality of each of the aforementioned sensors, the Examiner noting that it further would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to provide each of said sensors for each degree of freedom thereby providing dedicated sensors for said degrees of freedom and thus leading to more accurate/precise measurements for each tracker.
Claim(s) 13-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over newly cited Marques in view of newly cited Miller and in further view of newly cited Husheer et al (US 20180049653 A1; hereafter “Husheer”).
Regarding claim 13 and claim 14, where claim 13 depends on claim 1 and where claim 14 depends on claim 13,
Marques does not teach wherein at least one of the plurality of motion trackers comprises a vital sign sensor, and wherein the vital sign sensor comprises a respiration rate sensor, a body temperature sensor, a pulse rate sensor, or a combination of two or more thereof.
Miller teaches wherein at least one of the plurality of motion trackers (fig. 11, physiological sensors 1102 and activity sensors 1104) comprises a vital sign sensor (at once so envisaged; additional obviousness analysis provided), wherein the vital sign sensor comprises a respiration rate sensor, a body temperature sensor, a pulse rate sensor, or a combination of two or more thereof ([0032] “monitor, collect, and/or analyze various aspects of the fitness routine (such as their heart rate, workout intensity, workout duration, and so forth)”; [0033] “Physiological measurements may be very simple, such as the measurement of body or ambient temperature, or they may be more complicated, for example measuring how well the heart is functioning by taking an ECG (electrocardiograph)” and “The physiological measurements can be medical measurements, such as heart rate measurement data”; [0039] “the one or more sensors 120 can be a bio-impedance sensor, an accelerometer, a three dimensional (3D) accelerometer, a gyroscope, a light sensor, an optical sensor, a spectroscopy sensor, a heart rate monitor, a blood pressure sensor, a pulse oximeter sensor, and so forth” and “physiological information and/or medical information, such as a hydration level of the user, cardiac information of the user (e.g., blood pressure or heart rate), an blood oxygen level of the user, and so forth”; [0040] “The sensor array 178 can include: a bio-impedance spectroscopy sensor 168, an optical sensor 170, an electrocardiogram (ECG) sensor 172, a temperature sensor 174 (such as a thermostat or thermistor), an accelerometer 176, and so forth”; [0048] “physiological measurement data (such as heart rate measurement data, hydration level measurement data, blood pressure measurement data, and so forth)”; [0050] “heart rate data, skin temperature data, and hydration level data of a user”; [0055] “heart rate measurement” and “respiration sensor measurement”; [0125] “can include: an optical sensor, an impedance sensor, a bioimpedance sensor, an electrocardiogram (ECG) sensor, an accelerometer, an altimeter, a pulse oximeter sensor, a fluid level sensor, an oxygen saturation sensor, a body temperature sensor (e.g., a skin temperature sensor), a plethysmograph sensor, a respiration sensor, a breath sensor”; [0163]-[0164]; [0172] “one or more of the following types of sensors: a pulse oximeter sensor, an ECG sensor, a fluid level sensor, an oxygen saturation sensor, a body temperature sensor, an ambient temperature sensor, a plethysmograph sensor, a respiration sensor, a breath sensor, a cardiac sensor, a heart rate sensor”; Examiner emphasizes with respect to vital sign sensor, that an ordinary artisan would at once envisage that motion tracker sensing comprising respiration rate, body temperature, and pulse rate is reasonably nomenclaturally equivalent to a vital sign sensor, and likewise an ordinary artisan would at once envisage the combination of two or more of the aforementioned sensors).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Miller’s physiological (vital) sensors for wearable devices with Marques wearable motion tracking system thereby providing measurements to determine when the user may be experiencing stress/injury and/or to monitor recovery, relaxation, and/or physical exercise state, including to determine risk levels and/or if a diet of the user requires a change.
The Examiner acknowledges that Miller does not explicitly state wherein the respiration rate sensor, the body temperature sensor, the pulse rate sensor are comprised by a nomenclaturally defined vital sign sensor.
However:
It has been held that forming in one piece an article which has formerly been formed in two pieces and put together involves only routine skill in the art, see MPEP § 2144.04(V)(B), Howard v. Detroit Stove Works, 150 U.S. 164 (1893), and In re Larson, 340 F.2d 965, 968, 144 USPQ 347, 349 (CCPA 1965). In the present case, it is the Examiner's position that only ordinary skill in the art is required to integrate a respiration rate sensor, body temperature, and pulse rate sensor into a so-called vital sign sensor.
Furthermore, and as supporting factual evidence of the aforementioned assertion, Husheer teaches a vital signs sensor comprising a respiration rate sensor, a body temperature sensor, and a pulse rate sensor (Title “MONITORING VITAL SIGNS”; Abstract “A vital signs monitor for attachment to a human or animal thorax, the monitor having a low power mode and a high accuracy mode and comprising: a motion sensor configured to, in the low power mode, sample movement at a first frequency and, in the high accuracy mode, sample movement at a second frequency, the second frequency being greater than the first frequency”; [0001] “This invention relates to monitoring vital signs in humans and animals, in particular one or more of heart rate, respiration rate and temperature”; [0064] “select an energy-efficient sampling rate”; [0065] “If the monitor cannot identify the respiratory rate from the data, the monitor may be configured to increase the sampling frequency so as to capture a second set of coarse measurements from which to repeat the determination of the respiratory rate—this could be necessary in cases where the respiratory rate is very high”; [0073] “Operating the accelerometer at a sampling frequency which is sufficient to capture even very high possible heart rates consumes a substantial amount of energy. Using this two-step approach minimises energy usage since it avoids operating the accelerometer at a sampling frequency which is higher than required to accurately capture the likely heart rate of the wearer”; [0009], [0015]-[0016], [0060], [0094] “predefined or dynamic threshold”; [0065] “in order to achieve sufficient accuracy”; [0073] “sampling frequency which is sufficient”).
In view of the above, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Husheer’s explicit vital sign sensor design with Marques’ wearable motion tracking system thereby providing a compact integrated design in which the energy usage by sampling frequency of vital sensing elements are likewise dynamically reduced when convenient and/or dynamically increased for accuracy when necessary in addition to the aforementioned reasons including for measurements to determine when the user may be experiencing stress/injury and/or to monitor recovery, relaxation, and/or physical exercise state, including to determine risk levels and/or if a diet of the user requires a change.
Regarding claim 15, which depends on claim 14,
Marques as previously modified (see analysis of preceding claims) suggests wherein the one or more frequencies (Miller: sampling rate/frequencies; Husheer sampling rate/frequencies) are repeatedly adjusted during operation of the motion tracking system (Marques: fig. 1, motion tracking system 10) (Miller: [0033] “adjusting a frequency of taking physiological measurement”; and [0165] “activity-based PMM”. Husheer: [0064] “energy-efficient sampling rate”; [0065] “configured to increase the sampling frequency”; and [0073] “Operating the accelerometer at a sampling frequency which is sufficient”. See previously provided citations for full details).
Regarding claim 16, which depends on claim 15,
Marques is silent to item 1): the plurality of motion trackers each having a battery. Marques does not teach items: 2a) adjusting (sampling) frequencies; and 2b) wherein the one or more frequencies are repeatedly adjusted to maintain at least a threshold motion tracking accuracy level while increasing a life of a battery of each of the plurality of motion trackers.
Regarding item 1):
The Examiner takes Official Notice that batteries for powering portable sensors is conventional in the art.
Furthermore, and as supporting factual evidence of the aforementioned assertion, Miller teaches wherein a plurality of motion trackers (fig. 11, physiological sensors 1102 and activity sensors 1104) are each powered by a battery ([0211] “battery power”; [0212] “the portable device can include a swappable battery pack” and “portable device can have an internal battery”). Likewise, Husheer teaches wherein a plurality of (vital sign) motion trackers (fig. 1, vital signs monitor 100) are each powered by a battery (fig. 1, battery 102) ([0054]-[0057] “battery”).
In view of the above, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine a conventional battery—as factually supported by each of Miller’s and Husheer’s battery powered devices—with each of Marques’ motion trackers for the expected purpose(s) of providing power without requiring wiring which could be cumbersome, without requiring power generation/scavenging which can be expensive and/or undependable, and/or for being more convenient to replace/recharge with minimal effort/expertise. With respect to each/all trackers being powered by a battery, it further would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to standardize battery usage for the expected purpose of providing consistent manufacturing standards and/or use of all such trackers including for commercial reasons such as consumer expectations.
Regarding item 2a) and pertinent to item 2b), Miller teaches wherein the one or more frequencies are repeatedly adjusted to maintain motion tracking accuracy level while increasing a life of a battery of each of the plurality of motion trackers (fig. 11, physiological sensors 1102 and activity sensors 1104) ([0033] “adjusting a frequency of taking physiological measurement”; [0165] “the PMM 1120 can determine an activity level based on an activity level (e.g., an activity-based PMM) and can adjust the default pattern in various ways as described in more detail below” and “sensor module 1122 can be programmed to measure a set of physiological measurement according to a default pattern. The default pattern may be the frequency, granularity, and power used for measurements by the physiological sensors” and “adjusting a frequency or granularity of taking physiological measurements; turning off one or more systems of the apparatus”; [0164] “power management activities may be performed to increase measurement granularity or increase accuracy, precision, or resolution of the measurements by the wearable UMD 1100”; [0170] “The higher sampling rate may cause the wearable UMD 1100 to measure the second set of physiological measurements at a higher fidelity than the first set of physiological measurements. It could be higher fidelity, as well as higher accuracy, higher precision, or higher resolution”. See also previously provided citations.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Miller’s power management module and associated method of sampling rate/frequency adjustments for a motion tracking system with Marques motion tracking system for the same combination and motivation provided for the independent claim, and further emphasizing that the combination suggests that the adjustments for higher accuracy reasonably suggests a threshold (high enough) accuracy.
Nevertheless, the Examiner acknowledges that while Miller teaches dynamically adjusting sampling frequency for high enough accuracy, Miller does not explicitly state item 2b).
However:
Choosing from a finite number of identified, predictable solutions, with a reasonable expectation of success is obvious to try, see MPEP § 2143(I)(E). The Examiner also notes that MPEP § 2145(III)(X)(B) states “An “obvious to try” rationale may support a conclusion that a claim would have been obvious where one skilled in the art is choosing from a finite number of identified, predictable solutions, with a reasonable expectation of success. “[A] person of ordinary skill has good reason to pursue the known options within his or her technical grasp. If this leads to the anticipated success, it is likely that product [was] not of innovation but of ordinary skill and common sense. In that instance the fact that a combination was obvious to try might show that it was obvious under § 103.” KSR Int'l Co. v. Teleflex Inc., 550 U.S. 538, 421,82 USPQ2d 1385, 1397 (2007).” It is the Examiner’s position that knowing that a high accuracy when adjusting the sampling rate is desirable would lead an ordinary artisan to conclude that only common sense is required to have a threshold accuracy (i.e., not allow the desired “high accuracy” situational requirement to definitionally dip to a “low accuracy” as opposed to the alternative of accepting a low accuracy when a high accuracy is desirable).
Furthermore, Husheer explicitly teaches wherein the one or more frequencies are repeatedly adjusted to maintain at least a threshold motion tracking accuracy level while increasing a life of a battery of each of the plurality of motion trackers ([0009], [0015]-[0016], [0060], [0094] “predefined or dynamic threshold”; [0065] “in order to achieve sufficient accuracy”; [0073] “sampling frequency which is sufficient”. See also previous provided citations for details).
In view of the above, either one of ordinary skill in the art at the time the invention was effectively filed would at once envisaged that the combination with Miller reasonably suggests that the high accuracy is definitionally above a low accuracy threshold, or nevertheless, or in the alternative, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine Husheer’s explicitly sufficient accuracy sampling frequency requirement with Marques and Miller for the aforementioned common sense minimum high (enough) accuracy and thus preventing measurements that are insufficient at providing usefully quantifiable data that can be used for making decisions with confidence.
Claim(s) 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over newly cited Marques in view of newly cited Miller, newly cited Husheer, and in further view of newly cited Gomes et al (WO 2020127246 A1; hereafter “Gomes”).
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Regarding claim 17, which depends on claim 16,
Marques reasonably teaches wherein a hardware configuration of each of the plurality of motion trackers (figs. 1-3, sensors 20) is identical (see fig. 1 conveniently shown above, the Examiner noting that the sensors are shown with identical hardware configurations therein and thereby at once so envisaged).
The Examiner acknowledges that while shown, Marques does not explicitly state wherein a hardware configuration of each of the plurality of motion trackers is identical.
However:
It does not matter that the feature shown (in this case identical hardware) is unexplained in the specification. The drawings must be evaluated for what they reasonably disclose and suggest to one of ordinary skill in the art. See MPEP § 2125 and In re Aslanian, 590 F.2d 911, 200 USPQ 500 (CCPA 1979).
It has been held that mere duplication of the essential working parts of a device involves only routine skill in the art, see MPEP § 2144.04(VI)(B), St. Regis Paper Co. v. Bemis Co., 193 USPQ 8 (7th Cir. 1977), and In re Harza, 274 F.2d 669, 124 USPQ 378 (CCPA 1960). In the present case it is the Examiner's position that only ordinary skill in the art is required to have duplicate hardware configured motion trackers.
Furthermore, and as supporting factual evidence of the aforementioned assertion, Gomes teaches wherein a hardware configuration of each of the plurality of motion trackers is identical (Title “SENSOR PLACEMENT ERROR DETECTION AND CORRECTION”; Abstract “method of performing sensor placement error detection and correction for a system (10) for tracking human motion comprising -at least one sensor unit (12,14)”; page 6, ll. 26-27 “The sensor units 12, 14 are identical. This applies in particular to the technical features and also to the design of the sensor units 12, 14 (and other sensor units)”; page 7, ll. 16-28 “the sensor units are completely identical”; page 8 line 24 “All sensor units 12, 14, 32, 34, 36 are completely identical”).
In view of the above, either one of ordinary skill in the art at the time the invention was effectively filed would at once envisaged that Marques reasonably teaches identical hardware configurations of motion trackers, or nevertheless, or in the alternative, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to provide duplicate/identical hardware configurations of motion trackers—as factually supported by Gomes—for purposes of replaceability, swappability, and/or for commercial reasons including for simplification of manufacturing/sourcing &/or for the simplified convenience of the user.
Conclusion
The prior art made of record and not relied upon is considered pertinent to Applicant's disclosure. Applicant is invited to review PTO form 892 accompanying this Office Action listing Prior Art relevant to the instant invention cited by the Examiner.
Examiner interviews are available via telephone and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
Any inquiry concerning this communication or earlier communications from the Examiner should be directed to DAVID L SINGER whose telephone number is 303-297-4317. The Examiner can normally be reached Monday - Friday 8:00 am - 6:00pm CT, EXCEPT alternating Friday.
If attempts to reach the Examiner by telephone are unsuccessful, the Examiner’s supervisor, John Breene can be reached on 571-272-4107. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DAVID L SINGER/Primary Examiner, Art Unit 2855 03JAN2026