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 .
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
No claim limitation has been interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 101
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
The claims, specifically independent claims 1, 18, and 20 recite an abstract idea, specifically a mental process, for determining an absence of respiratory motion and obtaining physiological information from depth data that, under the broadest reasonable interpretation, is capable of being performed mentally and/or by a human with the aid of pen and paper. This judicial exception is not integrated into a practical application because the limitations “deriving at least one signal from the depth data” (claim 1), “perform depth data processing to obtain physiological information from the depth data, wherein the depth data processing comprises deriving at least one signal from the depth data” (claim 18), “performing depth data processing to obtain physiological information from depth data, wherein the depth data represents depth across a field of view” (claim 20), “obtaining further information from at least one of: the depth data or the at least one signal derived from the depth data”, “based on the further information, determining an absence of respiratory motion in the field of view”, and “setting a flag based on the determining of the absence of respiratory motion in the field of view” amount to an observation, evaluation, or judgement that a person would perform mentally in determining abnormalities associated with respiration in the depth data, in particular an absence of respiratory motion, and flagging the data for further review by a physician or to alert a patient/caregiver of a potentially dangerous situation.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Regarding claim 1, the limitation “obtaining the depth data, wherein the depth data represents a depth across a field of view” (claim 1), is merely insignificant extra-solution activity, such as mere data gathering, recited at a high level of generality and/or in a well-understood, routine, and conventional way, of the information needed to carry out the claimed algorithm. Regarding claim 18, the limitation “performing depth data processing to obtain physiological information from depth data, wherein the depth data represents depth across a field of view” is well-understood, routine, and conventional in the art. It represents components and/or activities which would routinely be used in applying the abstract idea, as evidenced by Applicant’s disclosure that various depth sensing cameras are well-known and conventional in the art and also depth data processing techniques are well-known, in particular [0058] and [0061] of the specification as originally filed. Regarding claim 20, the limitation “a depth sensing device configured to obtain depth data representing depth across a field of view” is well-understood, routine, and conventional in the art. It represents components and/or activities which would routinely be used in applying the abstract idea, as evidenced by Applicant’s disclosure that various depth sensing cameras are well-known and conventional in the art and also depth data processing techniques are well-known, in particular [0058] and [0061] of the specification as originally filed.
Regarding claims 18 and 20, the claimed “processing resource” and “processor” are merely generic computer components performing generic computer functions which are well-understood, routine, and conventional in the art; as such, they do not meaningfully limit the claim to be more than just the abstract idea. With the exception of generic computer-implemented steps, there is nothing in the claims themselves that foreclose them from being performed by a human, mentally or with pen and paper.
This judicial exception is not integrated into a practical application because the claim does not recite any limitations that amount to an improvement in the functioning of a computer, or an improvement to other technology or technical field, apply or use the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, implement the judicial exception with, or using a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, effect a transformation or reduction of a particular article to a different state or thing, or apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
Regarding dependent claims 2-17, the limitations of these dependent claim(s) merely add details to the algorithm which forms the abstract idea, but does not contain any further “additional elements”. Thus, the dependent claim(s) are not significantly more than the extended abstract idea.
Regarding dependent claim 19, the limitation “the depth sensing device comprises at least one of: a depth sensing camera, a stereo camera, a camera cluster, a camera array, or a motion sensor” further limits the “depth sensing device”, but it is still considered well-understood, routine, and conventional in the art for the same reasons listed above with respect to claim 18.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-2, 4, 7-10, 12, 14-15, and 18-20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Jacquel et al. (US Publication No. 2020/0046302 A1).
Regarding claim 1, Jacquel et al. discloses a computer-implemented method of performing depth data processing to obtain physiological information from depth data, comprising:
obtaining the depth data, wherein the depth data represents a depth across a field of view (see [0028] – “Such information can be used, as disclosed herein, to determine that a patient 112 is within the FOV 116 of the camera 114 and/or to determine one or more regions of interest (ROI's) to monitor on the patient 112. Once a ROI is identified, the ROI can be monitored over time, and the changes in depth of regions (e.g., pixels) within the ROI 102 can represent movements of the patient 112 associated with breathing”);
deriving at least one signal from the depth data (see [0028] – “As described in greater detail in U.S. Provisional Patent Application Ser. No. 62/614,763, those movements, or changes of regions within the ROI 102, can be used to determine various breathing parameters, such as tidal volume, minute volume, respiratory rate, etc. U.S. Provisional Patent Application Ser. No. 62/614,763 is incorporated herein by reference in its entirety”);
obtaining further information from at least one of: the depth data or the at least one signal derived from the depth data (see [0028] – “As described in greater detail in U.S. Provisional Patent Application Ser. No. 62/614,763, those movements, or changes of regions within the ROI 102, can be used to determine various breathing parameters, such as tidal volume, minute volume, respiratory rate, etc. U.S. Provisional Patent Application Ser. No. 62/614,763 is incorporated herein by reference in its entirety”);
based on the further information, determining an absence of respiratory motion in the field of view (see Figures 6C, 7C, 8C, and 9 and [0062] – “In some embodiments, the user can confirm that the patient 112 is not breathing by monitoring one or more (e.g., consecutively) generated images (e.g., including the generated image 933) and seeing that no patient breathing is detected across the one or more generated images. In these and other embodiments, the user can confirm that the patient 112 is not breathing by analyzing a tidal volume signal 999 displayed in a line plot 993 beneath the patient 112 on the display 930. As shown, the tidal volume signal 999 in the plot 993 is relatively flat for the past 22.5 seconds, suggesting that the patient 112 has not been breathing for approximately that period of time”, [0087] – “For example, if the tidal volume for the patient is and/or drops below a low tidal volume threshold value of the predetermined tidal volume range, the routine 1100 can determine that the patient is not breathing and/or that the patient's breathing is restricted and/or impaired”, and [0088] – “For example, if the tidal volume for the patient is and/or drops below a low tidal volume threshold value of the predetermined tidal volume range, the routine 1100 can determine that the patient is not breathing and/or that the patient's breathing is restricted and/or impaired”); and
setting a flag based on the determining of the absence of respiratory motion in the field of view (see [0063] – “In some embodiments, if the system detects a breathing abnormality, the system can trigger an audio and/or visual alarm to alert a user (e.g., the patient, the caregiver, the clinician, etc.)” and [0090] – “If the routine 1100 determines that one or more breathing abnormalities were detected at block 1109, the routine 1100 can proceed to block 1111 to trigger one or more alerts and/or alarms”).
Regarding claim 2, Jacquel et al. discloses the depth data processing is configured to extract a signal related to respiration from the depth data (see Figures 9-10B and [0028] – “As described in greater detail in U.S. Provisional Patent Application Ser. No. 62/614,763, those movements, or changes of regions within the ROI 102, can be used to determine various breathing parameters, such as tidal volume, minute volume, respiratory rate, etc. U.S. Provisional Patent Application Ser. No. 62/614,763 is incorporated herein by reference in its entirety”).
Regarding claim 4, Jacquel et al. discloses deriving the at least one signal comprises deriving a time dependent signal from the depth data, wherein the at least one signal is represented by a waveform (999, 1096, 1097, 1099), and wherein the further information comprises one or more properties of the waveform (see Figures 9-10B).
Regarding claim 7, Jacquel et al. discloses the further information comprises information derived from at least one of: a first signal obtained from the depth data over a first time window or a second signal obtained from the depth data over a second time window (see Figures 9-10B).
Regarding claim 8, Jacquel et al. discloses the physiological information comprises a physiological signal including at least one of: a respiratory rate, a pulse rate, a tidal volume, a minute volume, an oxygen saturation, a breathing parameter, a breathing effort, posture information, or sleep apnea information (see Figures 9-10B and [0028] – “As described in greater detail in U.S. Provisional Patent Application Ser. No. 62/614,763, those movements, or changes of regions within the ROI 102, can be used to determine various breathing parameters, such as tidal volume, minute volume, respiratory rate, etc. U.S. Provisional Patent Application Ser. No. 62/614,763 is incorporated herein by reference in its entirety”, [0046] – “As discussed in greater detail below, this can help a user and/or a video-based patient monitoring system to detect a variety of medical conditions, such as apnea, rapid breathing (tachypnea), slow breathing, intermittent or irregular breathing, shallow breathing, and others”, and [0072] – “For example, the generated tidal volume signal 1099 and/or a generated respiratory rate signal can be used to determine when a patient is hyperventilating, is not breathing, and/or is exhibiting apnea”).
Regarding claim 9, Jacquel et al. discloses the further information represents at least one of a property, a characteristic, or a feature of at least one of the depth data or the at least one signal (see Figures 9-10B and [0028] – “As described in greater detail in U.S. Provisional Patent Application Ser. No. 62/614,763, those movements, or changes of regions within the ROI 102, can be used to determine various breathing parameters, such as tidal volume, minute volume, respiratory rate, etc. U.S. Provisional Patent Application Ser. No. 62/614,763 is incorporated herein by reference in its entirety”, [0046] – “As discussed in greater detail below, this can help a user and/or a video-based patient monitoring system to detect a variety of medical conditions, such as apnea, rapid breathing (tachypnea), slow breathing, intermittent or irregular breathing, shallow breathing, and others”, and [0072] – “For example, the generated tidal volume signal 1099 and/or a generated respiratory rate signal can be used to determine when a patient is hyperventilating, is not breathing, and/or is exhibiting apnea”).
Regarding claim 10, Jacquel et al. discloses the further information for the at least one signal comprises at least one of:
a) an area under at least part of the signal (see [0065] – “In some embodiments, the system (i) can generate the volume gain signal 1096 by (e.g., continuously) integrating (e.g., summing up) all volume increases in the ROI and/or (ii) can generate the volume loss signal 1097 by (e.g., continuously) integrating (e.g., summing up) all volume decreases in the ROI”);
b) an average value for at least part of the signal;
c) one or more properties associated with or derived from at least one of peaks of the signal or troughs of the signal (see [0069] – “In these and other embodiments, assuming that (i) a trough represented on the tidal volume signal 1099 corresponds to a patient's maximum exhalation and (ii) a peak represented on the tidal volume signal 1099 corresponds to the patient's maximum inhalation, the patient's inhalation tidal volume can be calculated by taking a trough to peak measurement of the tidal volume signal 1099 corresponding to a single breath of the patient. Additionally, or alternatively, a patient's exhalation tidal volume can be calculated by taking a peak to trough measurement of the tidal volume signal 1099 corresponding to a single breath of the patient. In embodiments where the tidal volume signal 1099 is displayed inverted, a peak to trough measurement of a single breath of a patient can determine the patient's inhalation tidal volume, whereas a trough to peak measurement of a single breath of the patient can determine the patient's exhalation tidal volume”);
d) a property associated with a zero crossing of the signal;
e) a measure of at least one of bias in the signal or noise in the signal;
f) a count of one or more features in the signal or a density of one or more features in the signal; or
g) a mathematical property of the signal.
Regarding claim 12, Jacquel et al. discloses the determining of the absence of respiratory motion in the field of view comprises classifying the further information as representative of the absence of respiratory motion in the field of view (see Figures 6C, 7C, 8C, and 9 and [0062] – “In some embodiments, the user can confirm that the patient 112 is not breathing by monitoring one or more (e.g., consecutively) generated images (e.g., including the generated image 933) and seeing that no patient breathing is detected across the one or more generated images. In these and other embodiments, the user can confirm that the patient 112 is not breathing by analyzing a tidal volume signal 999 displayed in a line plot 993 beneath the patient 112 on the display 930. As shown, the tidal volume signal 999 in the plot 993 is relatively flat for the past 22.5 seconds, suggesting that the patient 112 has not been breathing for approximately that period of time”, [0087] – “For example, if the tidal volume for the patient is and/or drops below a low tidal volume threshold value of the predetermined tidal volume range, the routine 1100 can determine that the patient is not breathing and/or that the patient's breathing is restricted and/or impaired”, and [0088] – “For example, if the tidal volume for the patient is and/or drops below a low tidal volume threshold value of the predetermined tidal volume range, the routine 1100 can determine that the patient is not breathing and/or that the patient's breathing is restricted and/or impaired”).
Regarding claim 14, Jacquel et al. discloses the determining of the absence of respiratory motion in the field of view comprises applying a threshold based algorithm to compare the further information to one or more thresholds, and wherein determining the one or more thresholds for the threshold based algorithm comprises using training data (see [0070] – “For example, when the tidal volume signal 1099 indicates that the patient is displacing a small volume of air between inhalation and exhalation (e.g., a negligible volume of air, a volume of air equivalent to zero, a volume of air less than a predetermined threshold volume of air and/or below a predetermined tidal volume range, etc.), the system (and/or a clinician) can determine that the patient is either not breathing and/or that the patient's breathing is restricted and/or impaired”, [0087] – “In some embodiments, the routine 1100 can predetermine a tidal volume range (e.g., using a low threshold tidal volume value and a high threshold tidal volume value). The predetermined tidal volume range can be dependent upon a patient's characteristics (e.g., height, weight, gender, etc.). If a tidal volume for the patient falls outside of (e.g., above and/or below) the predetermined tidal volume range, the routine 1100 can determine that the patient is exhibiting a breathing abnormality. For example, if the tidal volume for the patient is and/or drops below a low tidal volume threshold value of the predetermined tidal volume range, the routine 1100 can determine that the patient is not breathing and/or that the patient's breathing is restricted and/or impaired”, and [0100] – “In additional exemplary aspects, the at least one processor is further configured to monitor one or more breathing parameter signals for the at least one ROI and to trigger an alert and/or an alarm when a minute volume signal is below a first threshold minute volume level and/or is above a second threshold minute volume level, a respiratory rate signal is below a first threshold respiratory rate level and/or is above a second threshold respiratory rate level, an inhalation-to-exhalation ratio is below a first threshold inhalation-to-exhalation ratio value and/or is above a second threshold inhalation-to-exhalation ratio value, a degree of consistency signal is below a first threshold degree of consistency level and/or is above a second degree of consistency level, and/or a SpO2 signal is below a first threshold SpO2 level and/or is above a second threshold SpO2 level”).
Regarding claim 15, Jacquel et al. discloses the depth data processing further comprises displaying the physiological information, and wherein the displaying of the physiological information is responsive to the setting the flag (see [0091] – “In these and other embodiments, the routine 1100 can trigger an alert and/or alarm to indicate a concerning condition. For example, the routine 1100 can trigger an alert and/or alarm (e.g., on a user's display) to indicate a patient is exhibiting apnea. In these and other embodiments, the routine 1100 can highlight a problematic site in the ROI on a display. In these and still other embodiments, the routine 1100 can trigger different alerts and/or alarms for different breathing abnormalities. For example, the routine can trigger an alert and/or alarm for apnea and/or a different alert and/or alarm for paradoxical breathing”).
Regarding claim 18, Jacquel et al. discloses an apparatus comprising:
a depth sensing device (114) configured to obtain depth data representing depth across a field of view (see [0028] – “The camera 114 can capture a sequence of images over time. The camera 114 can be a depth sensing camera, such as a Kinect camera from Microsoft Corp. (Redmond, Wash.). A depth sensing camera can detect a distance between the camera and objects within its field of view. Such information can be used, as disclosed herein, to determine that a patient 112 is within the FOV 116 of the camera 114 and/or to determine one or more regions of interest (ROI's) to monitor on the patient 112”); and
a processing resource configured to:
perform depth data processing to obtain physiological information from the depth data, wherein the depth data processing comprises deriving at least one signal from the depth data (see [0028] – “Such information can be used, as disclosed herein, to determine that a patient 112 is within the FOV 116 of the camera 114 and/or to determine one or more regions of interest (ROI's) to monitor on the patient 112. Once a ROI is identified, the ROI can be monitored over time, and the changes in depth of regions (e.g., pixels) within the ROI 102 can represent movements of the patient 112 associated with breathing”);
obtain further information from at least one of: the depth data or the at least one signal derived from the depth data (see [0028] – “As described in greater detail in U.S. Provisional Patent Application Ser. No. 62/614,763, those movements, or changes of regions within the ROI 102, can be used to determine various breathing parameters, such as tidal volume, minute volume, respiratory rate, etc. U.S. Provisional Patent Application Ser. No. 62/614,763 is incorporated herein by reference in its entirety”);
based on the further information, determine an absence of respiratory motion in the field of view (see Figures 6C, 7C, 8C, and 9 and [0062] – “In some embodiments, the user can confirm that the patient 112 is not breathing by monitoring one or more (e.g., consecutively) generated images (e.g., including the generated image 933) and seeing that no patient breathing is detected across the one or more generated images. In these and other embodiments, the user can confirm that the patient 112 is not breathing by analyzing a tidal volume signal 999 displayed in a line plot 993 beneath the patient 112 on the display 930. As shown, the tidal volume signal 999 in the plot 993 is relatively flat for the past 22.5 seconds, suggesting that the patient 112 has not been breathing for approximately that period of time”, [0087] – “For example, if the tidal volume for the patient is and/or drops below a low tidal volume threshold value of the predetermined tidal volume range, the routine 1100 can determine that the patient is not breathing and/or that the patient's breathing is restricted and/or impaired”, and [0088] – “For example, if the tidal volume for the patient is and/or drops below a low tidal volume threshold value of the predetermined tidal volume range, the routine 1100 can determine that the patient is not breathing and/or that the patient's breathing is restricted and/or impaired”); and
based on the determining the absence of respiratory motion in the field of view, set a flag (see [0063] – “In some embodiments, if the system detects a breathing abnormality, the system can trigger an audio and/or visual alarm to alert a user (e.g., the patient, the caregiver, the clinician, etc.)” and [0090] – “If the routine 1100 determines that one or more breathing abnormalities were detected at block 1109, the routine 1100 can proceed to block 1111 to trigger one or more alerts and/or alarms”).
Regarding claim 19, Jacquel et al. discloses the depth sensing device comprises at least one of: a depth sensing camera, a stereo camera, a camera cluster, a camera array, or a motion sensor (see [0028] – “The camera 114 can capture a sequence of images over time. The camera 114 can be a depth sensing camera, such as a Kinect camera from Microsoft Corp. (Redmond, Wash.). A depth sensing camera can detect a distance between the camera and objects within its field of view. Such information can be used, as disclosed herein, to determine that a patient 112 is within the FOV 116 of the camera 114 and/or to determine one or more regions of interest (ROI's) to monitor on the patient 112”).
Regarding claim 20, Jacquel et al. discloses a non-transitory machine-readable medium having instructions recorded thereon for execution by a processor to perform a set of operations, comprising:
performing depth data processing to obtain physiological information from depth data, wherein the depth data represents depth across a field of view (see [0028] – “Such information can be used, as disclosed herein, to determine that a patient 112 is within the FOV 116 of the camera 114 and/or to determine one or more regions of interest (ROI's) to monitor on the patient 112. Once a ROI is identified, the ROI can be monitored over time, and the changes in depth of regions (e.g., pixels) within the ROI 102 can represent movements of the patient 112 associated with breathing”);
deriving at least one signal from the depth data (see [0028] – “As described in greater detail in U.S. Provisional Patent Application Ser. No. 62/614,763, those movements, or changes of regions within the ROI 102, can be used to determine various breathing parameters, such as tidal volume, minute volume, respiratory rate, etc. U.S. Provisional Patent Application Ser. No. 62/614,763 is incorporated herein by reference in its entirety”);
obtaining further information from at least one of: the depth data or the at least one signal derived from the depth data (see [0028] – “As described in greater detail in U.S. Provisional Patent Application Ser. No. 62/614,763, those movements, or changes of regions within the ROI 102, can be used to determine various breathing parameters, such as tidal volume, minute volume, respiratory rate, etc. U.S. Provisional Patent Application Ser. No. 62/614,763 is incorporated herein by reference in its entirety”);
based on the further information, determining an absence of respiratory motion in the field of view (see Figures 6C, 7C, 8C, and 9 and [0062] – “In some embodiments, the user can confirm that the patient 112 is not breathing by monitoring one or more (e.g., consecutively) generated images (e.g., including the generated image 933) and seeing that no patient breathing is detected across the one or more generated images. In these and other embodiments, the user can confirm that the patient 112 is not breathing by analyzing a tidal volume signal 999 displayed in a line plot 993 beneath the patient 112 on the display 930. As shown, the tidal volume signal 999 in the plot 993 is relatively flat for the past 22.5 seconds, suggesting that the patient 112 has not been breathing for approximately that period of time”, [0087] – “For example, if the tidal volume for the patient is and/or drops below a low tidal volume threshold value of the predetermined tidal volume range, the routine 1100 can determine that the patient is not breathing and/or that the patient's breathing is restricted and/or impaired”, and [0088] – “For example, if the tidal volume for the patient is and/or drops below a low tidal volume threshold value of the predetermined tidal volume range, the routine 1100 can determine that the patient is not breathing and/or that the patient's breathing is restricted and/or impaired”); and
setting a flag based on the determining the absence of respiratory motion in the field of view (see [0063] – “In some embodiments, if the system detects a breathing abnormality, the system can trigger an audio and/or visual alarm to alert a user (e.g., the patient, the caregiver, the clinician, etc.)” and [0090] – “If the routine 1100 determines that one or more breathing abnormalities were detected at block 1109, the routine 1100 can proceed to block 1111 to trigger one or more alerts and/or alarms”).
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 3, 5-6, 13, and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jacquel et al., further in view of Petkov et al. (US Publication No. 2023/0270337 A1).
Regarding claim 3, Jacquel et al. teaches the at least one signal derived from the depth data comprises a time dependent signal, and wherein the further information comprises one or more of: information obtained from the time dependent signal or information obtained from the depth data (see Figures 9-10B) but does not specifically teach the at least one signal derived from the depth data comprises a frequency dependent signal. However, Petkov et al. teaches the at least one signal derived from the depth data comprises a time dependent signal and a frequency dependent signal, and wherein the further information comprises one or more of: information obtained from the time dependent signal, information obtained from the frequency dependent signal, or information obtained from the depth data (see [0043] – “At step 120, the featured signal V(t) is filtered. This may, in some examples, allow features of the featured signal V(t) to be analyzed in a specific frequency interval (where the specific frequency interval is, for example, the Frequency of Interest (FOI), the Breathing Frequency of Interest (BFOI), or the interval of frequencies to be used to look for respiratory activity). As one example of this, if a frequency interval [0.5, 1] Hz is desired (e.g., where breathing is defined as a near periodical signal with a frequency between 0.5 and 1 Hz), the featured signal V(t) may be filtered to create a new signal containing only periodicities between 0.5 and 1 Hz” and [0094] – “In some examples, determining the breathing rate includes determining respiratory breaths and times. The respiratory breaths correspond to the Y coordinates (local maxima), and the respiratory times correspond to the X coordinates of the time-dependent signal Sn(t), in some examples. In some examples, the determined breathing rate also (or alternatively) includes respiratory spectral power changes of a subject”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Jacquel et al. to include the at least one signal derived from the depth data comprises a frequency dependent signal, as disclosed in Petkov et al., so as to identify the interval of frequencies used to look for respiratory activity and filter out non-breathing related data from the signal (see Petkov et al.: [0019] and [0043]).
Regarding claim 5, it is noted Jacquel et al. does not specifically teach the at least one signal comprises a further signal obtained from one of: a power spectral analysis or a frequency analysis of the time dependent signal, and wherein the further information comprises one or more properties of the further signal. However, Petkov et al. teaches the at least one signal comprises a further signal obtained from one of: a power spectral analysis or a frequency analysis of the time dependent signal, and wherein the further information comprises one or more properties of the further signal (see [0043] – “At step 120, the featured signal V(t) is filtered. This may, in some examples, allow features of the featured signal V(t) to be analyzed in a specific frequency interval (where the specific frequency interval is, for example, the Frequency of Interest (FOI), the Breathing Frequency of Interest (BFOI), or the interval of frequencies to be used to look for respiratory activity). As one example of this, if a frequency interval [0.5, 1] Hz is desired (e.g., where breathing is defined as a near periodical signal with a frequency between 0.5 and 1 Hz), the featured signal V(t) may be filtered to create a new signal containing only periodicities between 0.5 and 1 Hz” and [0094] – “In some examples, determining the breathing rate includes determining respiratory breaths and times. The respiratory breaths correspond to the Y coordinates (local maxima), and the respiratory times correspond to the X coordinates of the time-dependent signal Sn(t), in some examples. In some examples, the determined breathing rate also (or alternatively) includes respiratory spectral power changes of a subject”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Jacquel et al. to include the at least one signal comprises a further signal obtained from one of: a power spectral analysis or a frequency analysis of the time dependent signal, and wherein the further information comprises one or more properties of the further signal, as disclosed in Petkov et al., so as to identify the interval of frequencies used to look for respiratory activity and filter out non-breathing related data from the signal (see Petkov et al.: [0019] and [0043]).
Regarding claim 6, it is noted Jacquel et al. does not specifically teach the at least one signal comprises a respiratory signal and a power spectrum signal obtained from the respiratory signal, and wherein the further information comprises one or more properties of at least one of: the depth data, the respiratory signal, or the power spectrum signal. However, Petkov et al. teaches the at least one signal comprises a respiratory signal and a power spectrum signal obtained from the respiratory signal, and wherein the further information comprises one or more properties of at least one of: the depth data, the respiratory signal, or the power spectrum signal (see [0043] – “At step 120, the featured signal V(t) is filtered. This may, in some examples, allow features of the featured signal V(t) to be analyzed in a specific frequency interval (where the specific frequency interval is, for example, the Frequency of Interest (FOI), the Breathing Frequency of Interest (BFOI), or the interval of frequencies to be used to look for respiratory activity). As one example of this, if a frequency interval [0.5, 1] Hz is desired (e.g., where breathing is defined as a near periodical signal with a frequency between 0.5 and 1 Hz), the featured signal V(t) may be filtered to create a new signal containing only periodicities between 0.5 and 1 Hz” and [0094] – “In some examples, determining the breathing rate includes determining respiratory breaths and times. The respiratory breaths correspond to the Y coordinates (local maxima), and the respiratory times correspond to the X coordinates of the time-dependent signal Sn(t), in some examples. In some examples, the determined breathing rate also (or alternatively) includes respiratory spectral power changes of a subject”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Jacquel et al. to include the at least one signal comprises a respiratory signal and a power spectrum signal obtained from the respiratory signal, and wherein the further information comprises one or more properties of at least one of: the depth data, the respiratory signal, or the power spectrum signal, as disclosed in Petkov et al., so as to identify the interval of frequencies used to look for respiratory activity and filter out non-breathing related data from the signal (see Petkov et al.: [0019] and [0043]).
Regarding claim 13, it is noted Jacquel et al. does not specifically teach the classifying comprises using one or more of a machine learning derived model, a classifier, a decision tree, a k-Nearest Neighbors (kNN) algorithm, an Adaptive Boosting (AdaBoost) algorithm, a Random Forest, a Neural Network, or a Support Vector Machine (SVM). However, Petkov et al. teaches the classifying comprises using one or more of a machine learning derived model, a classifier, a decision tree, a k-Nearest Neighbors (kNN) algorithm, an Adaptive Boosting (AdaBoost) algorithm, a Random Forest, a Neural Network, or a Support Vector Machine (SVM) (see [0021] – “The data analysis module 4 may be configured to determine if the subject's breathing has stopped by analyzing the determined breathing rate. If there is a loss of the determined breathing rate, the data analysis module 4 may determine if it arises from a breathing stoppage or various non-emergency circumstances, for example, when a baby has been taken out of its crib (or other structure), or there is a physical obstruction of the imaging device 2. Thus, if there is a loss of the determined breathing rate, the data analysis module 4 may be further configured to determine if the loss is abnormal or normal” and [0033] – “The breathing rate analysis may also (or alternatively) be performed using population data for developmental abnormalities. By collecting breathing patterns from a large number of babies, one can normalize such pattern. By comparing normalized patterns, minor irregularities on a specific subject might be detected. The population data may be analyzed using artificial intelligence (AI) and machine learning (ML) techniques”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Jacquel et al. to include the classifying comprises using one or more of a machine learning derived model, a classifier, a decision tree, a k-Nearest Neighbors (kNN) algorithm, an Adaptive Boosting (AdaBoost) algorithm, a Random Forest, a Neural Network, or a Support Vector Machine (SVM), as disclosed in Petkov et al., so as to collect breathing patterns from a large number of subjects in order to normalize the patterns to allow minor irregularities of a specific subject to be detected (see Petkov et al.: [0033]).
Regarding claim 16, it is noted Jacquel et al. does not specifically teach the further information relates to one or more signals derived from the depth data, and wherein the method further comprises: pre-processing the one or more signals; and obtaining the further information from the pre-processed one or more signals, wherein the pre-processing comprises at least one of filtering, selecting, or cleaning of the one or more signals. However, Petkov et al. teaches the further information relates to one or more signals derived from the depth data, and wherein the method further comprises: pre-processing the one or more signals; and obtaining the further information from the pre-processed one or more signals, wherein the pre-processing comprises at least one of filtering, selecting, or cleaning of the one or more signals (see [0019] – “In some examples, to detect the breathing rate, the breath rate detection module 3 may be configured to filter out non-breathing related data from the video received from the imaging device 2, such as non-breathing related motion data” and [0043] – “At step 120, the featured signal V(t) is filtered. This may, in some examples, allow features of the featured signal V(t) to be analyzed in a specific frequency interval (where the specific frequency interval is, for example, the Frequency of Interest (FOI), the Breathing Frequency of Interest (BFOI), or the interval of frequencies to be used to look for respiratory activity). As one example of this, if a frequency interval [0.5, 1] Hz is desired (e.g., where breathing is defined as a near periodical signal with a frequency between 0.5 and 1 Hz), the featured signal V(t) may be filtered to create a new signal containing only periodicities between 0.5 and 1 Hz”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Jacquel et al. to include the further information relates to one or more signals derived from the depth data, and wherein the method further comprises: pre-processing the one or more signals; and obtaining the further information from the pre-processed one or more signals, wherein the pre-processing comprises at least one of filtering, selecting, or cleaning of the one or more signals, as disclosed in Petkov et al., so as to identify the interval of frequencies used to look for respiratory activity and filter out non-breathing related data from the signal (see Petkov et al.: [0019] and [0043]).
Claim(s) 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jacquel et al., further in view of Guo et al. (US Publication No. 2023/0389817 A1).
Regarding claim 11, it is noted Jacquel et al. does not specifically teach the depth data processing further comprises at least one of: determining one or more portions of the depth data corresponding to coherent changes or obtaining a mask for a visual overlay; wherein the further information comprises at least one property of the determined one or more portions or the obtained mask, and wherein the at least one property comprises at least one of: a size, a shape, or a fill ratio. However, Guo et al. teaches the depth data processing further comprises at least one of: determining one or more portions of the depth data corresponding to coherent changes or obtaining a mask for a visual overlay; wherein the further information comprises at least one property of the determined one or more portions or the obtained mask, and wherein the at least one property comprises at least one of: a size, a shape, or a fill ratio (see [0011] – “In some examples, images from the video may be applied to another CNN to produce segmentation masks, and these segmentation masks may be applied to corresponding vector fields to filter vectors in the vector fields that do not correspond to the human torso. For instance, multiplying a vector field by a segmentation mask may cause the vectors corresponding to a background or to another subject(s) in the video to be removed from the vector field” and [0021] – “The method 200 includes using the bounding box or segmentation mask to filter out background vectors (e.g., vectors representing background movement or background noise) from the vector field produced in 208 (210), thus producing a respiration signal. For example, the segmentation mask 309 may be used to filter out the background vectors 308 from the vector field 314. The segmentation mask 309 would not, however, cause vectors 306 to be removed. Similarly, in examples, the bounding box 310 may be used to filter out at least some of the background vectors 308 from the vector field 314, but the bounding box 310 would not cause vectors 306 (and, in examples, some of the vectors 308 circumscribing the human torso 302) to be removed. In examples, the segmentation mask 309 or the bounding box 310 is multiplied by the vector field 314 to produce the respiration signal (210), which is a modified version of the vector field 314. FIG. 3D depicts an example respiration signal 316, which includes the human torso 302 and vectors 306 corresponding to the movement (including respiratory movement) of the human torso 302. The segmentation mask 309, rather than the bounding box 310, is used to produce the specific example of FIG. 3D”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Jacquel et al. to include the depth data processing further comprises at least one of: determining one or more portions of the depth data corresponding to coherent changes or obtaining a mask for a visual overlay; wherein the further information comprises at least one property of the determined one or more portions or the obtained mask, and wherein the at least one property comprises at least one of: a size, a shape, or a fill ratio, as disclosed in Guo et al., so as to filter out background vectors representing background movement or background noise, thus leaving only the respiration signal (see Guo et al.: [0021]).
Claim(s) 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Jacquel et al., further in view of Wolford (US Publication No. 2010/0191136 A1).
Regarding claim 17, Jacquel et al. teaches repeating the determining of the absence of respiratory motion in the field of view (see Figure 11 and [0090] – “At block 1110, the routine 1100 determines whether one or more breathing abnormalities were detected at block 1109. If the routine 1100 determines that one or more breathing abnormalities were detected at block 1109, the routine 1100 can proceed to block 1111 to trigger one or more alerts and/or alarms. On the other hand, if the routine 1100 determines that one or more breathing abnormalities were not detected at block 1109, the routine 1100 can return to block 1104 to capture two or more images of one or more ROI's. In some embodiments, the routine 1100 can automatically return to block 1104 after determining whether one or more breathing abnormalities were detected at block 1109” and [0092] – “For example, before, during, and/or after executing blocks 1109 and/or 1110, the routine 1100 can return to blocks 1101, 1103, 1105, and/or 1107 in addition to or in lieu of returning to block 1104. In these and other embodiments, one or more steps of the routine 1100 illustrated in FIG. 11 can be omitted and/or repeated in some embodiments”) but does not specifically teach storing results of the repeated determining in a memory storage buffer, wherein the setting of the flag is based on an evaluation of stored results in the memory storage buffer. However, Wolford teaches storing results of the repeated determining in a memory storage buffer, wherein the setting of the flag is based on an evaluation of stored results in the memory storage buffer (see [0030] – “In the absence of breathing or movement of the patient, a low level (or zero position movement) data signal is sent (output of S120 is "YES"). To avoid a spurious alarm, a delay or buffer can be inserted, reflected in the control algorithm run by the judging circuit 136 under control of controller 132. The buffer period can be varied depending on the person being monitored; an example range may be between 1.5 to 5 seconds. In another example, a buffer period may be set to 2 seconds for an infant, 4-5 seconds for an adult. If no breathing is detected (output of S130 is "YES") within the buffer period (i.e., follow on signals reveal a continued absence of breathing as judged by judging circuit 136), the controller 132 issues a control signal to emit an audible tone at alarm 133 (S135) and/or to energize the LED alarm 135”). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the method of Jacquel et al. to include storing results of the repeated determining in a memory storage buffer, wherein the setting of the flag is based on an evaluation of stored results in the memory storage buffer, as disclosed in Wolford, so as to avoid a spurious alarm from being issued until the period of absence of breathing is greater than the buffer period (see Wolford: [0030]).
Conclusion
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/DEVIN B HENSON/ Primary Examiner, Art Unit 3791
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