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 Objections
Claims 13 and 20 are objected to because of the following informalities:
In claim 13, line 6, “the shape” should read “a shape”.
In claim 20, line 1, the “a health monitoring method” should read “the health monitoring method”.
Appropriate correction is required.
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.
Claims 4-7 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 pre-AIA the applicant regards as the invention.
Claim 4 recites the " a transmitter … a receiver … a ratio of the number of the transmitter to the number of the receiver included in the IoT radar sensor is 1:N (herein, N is an integer of 1 or greater), and a plurality of the receivers are positioned distributed in a preset area”. This recitation is unclear because of conflicting recitations. It is unclear how many receivers and transmitters are being claimed. It is also unclear how one receiver (N= 1) can be "distributed". For examination purposes, Examiner of record takes this to be “a transmitter … at least one receiver … and the at least one receiver is positioned in a preset area …”.
Claims dependent upon the rejected claims above, but not directly addressed, are also rejected because they inherit the indefiniteness of the claim(s) they respectively depend upon.
Claim Rejections - 35 USC § 102
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.
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.
Claims 1, 4, 8-12, 15, and 18-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Cuddihy et al (US 20130053653), hereinafter Cuddihy.
Regarding claim 1, Cuddihy teaches a health care monitoring and smart home convergence system (100) (“the system 100 includes the range-gated radar 108 coupled to the planar antenna 110 and the one or more processing units 116 over a communications network 202.” [0032] Figs. 1-2) based on a built-in ceiling IoT radar sensor (108) (“the range-gated radar system 108 monitors the subject 102 relaxing or sleeping on the bed 112 disposed in the designated space 102” [0021]; Fig. 1), the health care monitoring and smart home convergence system comprising:
the built-in ceiling IoT radar sensor installed into a ceiling of a bedroom (the radar system 108 is appropriately positioned in the designated space 104 to effectively monitor the subject 102 disposed in the designated space 102…the radar system 108 may be positioned … adjacent or opposite the bed 112, or on the ceiling of the room to monitor the subject 102.” [0021]; Fig. 1), and configured to measure a user's heart rate or respiratory rate (“At step 308, the processing unit 116 further determines one or more patterns in the physiological parameters detected over a designated period of time (designated physiological period of time). To that end, the processing unit 116 extracts heartbeat and respiration data” [0059]) on the basis of time of flight (ToF) of a radar signal to generate biosignal data (“Accordingly, … the range-controlled radar transmits low power, short duration pulses, for example of about 10 microseconds, … towards the desired portions of the designated space at selected time intervals, for example, every ten milliseconds. These pulses, … penetrate the clothing over the sleeping subject and reflect off of the torso to accurately detect micro movements associated with the heart, lungs and thorax portions of the body.” [0055]); and
a health analysis part (116) configured to analyze the user's sleep pattern on the basis of the biosignal data, and use the sleep pattern to generate health prediction information on the user's health state (“Monitoring sleep and wake patterns and various physiological parameters such as heart rate and respiration during sleep, thus, provides clinical markers for identifying and treating various health conditions afflicting a subject.” [0003]; “the processing unit 116 uses the determined heart rate and motion to identify underlying health conditions such as bradycardia (slow heartbeat), tachycardia (fast heartbeat), arrhythmia (irregular heartbeat) and/or sleep fragmentation.” [0043]; “the present systems employ fast and simple computations that evaluate the subject's motion and vital signs to identify if the subject is suffering from an illness” [0068]).
Regarding claim 4, Cuddihy teaches the health care monitoring and smart home convergence system of claim 1, wherein the IoT radar sensor comprises:
a transmitter (204) configured to output the radar signal at set time intervals (“the range-controlled radar transmits low power, short duration pulses, for example of about 10 microseconds, … towards the desired portions of the designated space at selected time intervals, for example, every ten milliseconds.” [0055]), and a receiver (206) configured to receive a reflection signal obtained as the radar signal is reflected (“While monitoring the subject 102, the radar system 108 transmits electromagnetic signals towards the desired portions of the designated space 104 such as the bed 112 and senses corresponding echo signals reflected from the subject 102 disposed on the bed 112.” [0022]; “the radar 108 includes a transmitter 204 and a receiver 206.” [0033] Fig. 2), wherein a ratio of the number of the transmitter to the number of the receiver included in the IoT radar sensor is 1:N (herein, N is an integer of 1 or greater), and a plurality of the receivers are positioned distributed in a preset area within the IoT radar sensor (“the receiver 206 receives and processes the radar signals reflected from the objects 106 in the designated space 104 for further use. The receiver 206, for example, converts the signal from the transmission frequency to an intermediate or baseband frequency, segregates the signal information from noise and interference” [0035] As noted in the 112b rejection, N=1 corresponds to a single receiver for a single transmitter).
Regarding claim 8, Cuddihy teaches the health care monitoring and smart home convergence system of claim 1, wherein the health analysis part further comprises a sleep analysis part (116) configured to analyze the user's sleep pattern on the basis of the biosignal data (“The processing unit 116 may also identify patterns in the sleep and wakeup cycles of the subject to determine if the subject suffers from sleep fragmentation.” [0065]),
wherein the sleep analysis part is configured to classify types of sleep of the user according to number-of-times variations in the respiratory rate or the heart rate (“the processing unit 116 compares the measured motion, heartbeat and respiration values with corresponding baseline information to detect if the subject's resting state includes active stages including rapid eye movement (REM) sleep and passive 1, 2, 3, 4 and 5 sleep stages. Particularly, unobtrusive monitoring using the system 100 allows the processing unit 116 to quantify how much and how often, the motion, respiration and heartbeat patterns change over the designated period of time. The changes in these patterns, in turn, can be used to identify and monitor conditions such as dementia, which are known to disrupt circadian rhythms.” [0028]).
Regarding claim 9, Cuddihy teaches the health care monitoring and smart home convergence system of claim 8, wherein the sleep analysis part is configured to classify the types of sleep into at least one selected from a group of deep sleep, rapid eye movement (REM) sleep, and non-sleep (“the processing unit 116 compares the measured motion, heartbeat and respiration values with corresponding baseline information to detect if the subject's resting state includes active stages including rapid eye movement (REM) sleep and passive 1, 2, 3, 4 and 5 sleep stages.” [0028]; “identify patterns in the sleep and wakeup cycles of the subject to determine if the subject suffers from sleep fragmentation.” [0065]), on the basis of a change range of the number-of-times variations (“Particularly, unobtrusive monitoring using the system 100 allows the processing unit 116 to quantify how much and how often, the motion, respiration and heartbeat patterns change over the designated period of time. The changes in these patterns, in turn, can be used to identify and monitor conditions such as dementia,” [0028]).
Regarding claim 10, Cuddihy teaches the health care monitoring and smart home convergence system of claim 9, wherein the health analysis part is configured to generate the health prediction information on the basis of a sleep duration variation (“The changes in these patterns, in turn, can be used to identify and monitor conditions such as dementia,” [0028]) for at least one selected from a group of the user's total sleep duration, deep sleep duration, REM sleep duration, and non-sleep duration (“identify patterns in the sleep and wakeup cycles of the subject to determine if the subject suffers from sleep fragmentation.” [0065]).
Regarding claim 11, Cuddihy teaches the health care monitoring and smart home convergence system of claim 8, wherein the sleep analysis part is configured to determine that the user has left when it is measured that the biosignal data is less than a limit value for a set period of time or longer (“fails to detect … physiological parameters.” [0037]), and process, as noise, the biosignal data measured while the user has left (“the subject 102 is assumed to be out of range if the radar system 108 focused over a desired portion fails to detect one or more of motion and/or physiological parameters. If the subject 102 is within range, the processing unit 116 extracts data corresponding to the subject's gross motion, respiration and heartbeat from the reflected signal data to determine the subject's health condition.” [0037]).
Regarding claim 12, Cuddihy teaches the health care monitoring and smart home convergence system of claim 8, further comprising:
a positioning detection sensor (“The PIR motion sensor” [0021]) installed in the bedroom, and configured to remotely measure the user's positioning to generate positioning data (“motion in the designated space 104” [0021]),
wherein the sleep analysis part is configured to determine that the user has left when the positioning data corresponds to positioning other than sleep positioning within a preset sleep duration (“over a period of time” [0038]; “during a designated period of time” [0039]), and process, as noise, the biosignal data measured while the user has left (“the system 100 includes a passive infrared (PIR) motion sensor (not shown) coupled to the radar 108. The PIR motion sensor activates and/or deactivates the radar 108 based on a presence or an absence of motion in the designated space 104” [0021]; “the subject 102 is assumed to be out of range if the radar system 108 focused over a desired portion fails to detect one or more of motion and/or physiological parameters. If the subject 102 is within range, the processing unit 116 extracts data corresponding to the subject's gross motion, respiration and heartbeat from the reflected signal data to determine the subject's health condition.” [0037]).
Regarding claim 18, Cuddihy teaches the health care monitoring and smart home convergence system of claim 1, wherein the health analysis part is configured to transmit a notification message (“sending a text message” [0049]) including the health prediction information to a wall pad installed in the user's home or a pre-registered user terminal (118) (“a healthcare monitoring system” [0049]) (“the processing unit 116 triggers an alert through the alerting system 118 coupled to the radar system 108 and/or the processing subsystem 116 on determining deterioration of the subject's health. By way of example, the processing unit 116 generates and/or communicates an audio and/or visual alert … and/or sending a text message through the alerting system 118 upon determining a progressive reduction in the heartbeat and/or respiration rates of the subject 102. The alerting system 118 communicates the alert through a wired and/or wireless link to appropriate personnel or a healthcare monitoring system for immediate assistance.” [0049]; “if the processing unit 116 determines that the subject's heartbeat and/or respiration is outside their designated threshold limits, the processing unit 116 generates an alarm to notify appropriate personnel or health monitoring system of a potential medical condition.” [0067]; Fig. 1).
Regarding claim 19, Cuddihy teaches a health monitoring method (300) using a health care monitoring and smart home convergence system (100) (“the system 100 includes the range-gated radar 108 coupled to the planar antenna 110 and the one or more processing units 116 over a communications network 202.” [0032] Figs. 1-3) based on a built-in ceiling IoT radar sensor (108) (“the range-gated radar system 108 monitors the subject 102 relaxing or sleeping on the bed 112 disposed in the designated space 102” [0021]; Fig. 1) installed in a home (the radar system 108 is appropriately positioned in the designated space 104 to effectively monitor the subject 102 disposed in the designated space 102” [0021]; Fig. 1), the health monitoring method comprising:
measuring, by using the built-in ceiling IoT radar sensor installed into a ceiling of a bedroom (“the radar system 108 may be positioned … on the ceiling of the room to monitor the subject 102.” [0021]; Fig. 1), a user's heart rate or respiratory rate (“At step 308, the processing unit 116 further determines one or more patterns in the physiological parameters detected over a designated period of time (designated physiological period of time). To that end, the processing unit 116 extracts heartbeat and respiration data” [0059]) on the basis of time of flight (ToF) of a radar signal to generate biosignal data (“Accordingly, … the range-controlled radar transmits low power, short duration pulses, for example of about 10 microseconds, … towards the desired portions of the designated space at selected time intervals, for example, every ten milliseconds. These pulses, … penetrate the clothing over the sleeping subject and reflect off of the torso to accurately detect micro movements associated with the heart, lungs and thorax portions of the body.” [0055]); and
analyzing the user's sleep pattern on the basis of the biosignal data, and using the sleep pattern to generate health prediction information on the user's health state (“Monitoring sleep and wake patterns and various physiological parameters such as heart rate and respiration during sleep, thus, provides clinical markers for identifying and treating various health conditions afflicting a subject.” [0003]; “the processing unit 116 uses the determined heart rate and motion to identify underlying health conditions such as bradycardia (slow heartbeat), tachycardia (fast heartbeat), arrhythmia (irregular heartbeat) and/or sleep fragmentation.” [0043]; “the present systems employ fast and simple computations that evaluate the subject's motion and vital signs to identify if the subject is suffering from an illness” [0068]).
Regarding claim 20, Cuddihy teaches a computer program stored on a medium, in combination with hardware, to perform a health monitoring method of claim 19 (“in FIG. 3, the exemplary method is illustrated as a collection of items in a logical flow chart, which represents operations that may be implemented in hardware, software, or combinations thereof.” [0052]).
Claim Rejections - 35 USC § 103
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.
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.
Claims 2-3 are rejected under 35 U.S.C. 103 as being unpatentable over Cuddihy as applied to claim 1, and further in view of Sehlhoff (EP2650849), hereinafter, Sehlhoff.
Regarding claim 2, Cuddihy teaches the health care monitoring and smart home convergence system of claim 1.
Cuddihy does not teach that the IoT radar sensor is installed semi-recessed by a fixing frame and a spring clip inside an installation hole formed in the ceiling of the bedroom in a built-in manner,
the fixing frame is inserted into the installation hole to support a lower portion of the IoT radar sensor and has an opening through which the IoT radar sensor is exposed, and
the spring clip is positioned between the installation hole and the fixing frame, and is configured to fix the fixing frame within the installation hole with elasticity of the spring clip.
However, in the built-in sensors and sensing systems field of endeavor, Sehlhoff discloses a built-in passive infrared sensor device, which is analogous art. Sehlhoff teaches that the IoT radar sensor (“a flush PIR sensor device”) is installed semi-recessed by a fixing frame (6) and a spring clip (4) inside an installation hole (“a mounting opening”) formed in the ceiling of the bedroom in a built-in manner,
the fixing frame is inserted into the installation hole to support a lower portion of the IoT radar sensor (8-9) and has an opening through which the IoT radar sensor is exposed (“So that the further task criterion of the formation of an aesthetically pleasing sensor device can be met, it is provided to design the sensor device as a built-in passive infrared sensor device, in particular as a flush PIR sensor device whose housing is at least partially, in particular mostly with an installation section in or behind a ceiling or wall mounting opening,… so that visible on the ceiling or wall only a viewing portion remains, which can then have a very small height extension, so that at least to the viewer of the impression arises, the entire sensor has an extremely flat design.”; p. 2, 4th para.), and
the spring clip is positioned between the installation hole and the fixing frame, and is configured to fix the fixing frame within the installation hole with elasticity of the spring clip (“In the Fig. 1 to 4 is a constructed as a motion sensor built passive infrared sensor device in the form of a flush PIR sensor device. The sensor device 1 comprises a housing 2 made of plastic injection-molded parts. The housing 2 is divided into a rear, elongate insert portion for insertion through a mounting opening, for example in a suspended ceiling. Laterally on the insert portion are located on two opposite sides of two spring clip 4, which brace in the assembled state located outside the mounting opening viewing portion 5 of the housing 2 with a rear abutment surface 6 flat against the wall or the ceiling, with the spring clip 4, for example support the back of the suspended ceiling. In a rear end region of the insert section 3 is a connection socket 7, designed here for integration into a KNX home bus system, via the connector socket 7, the power supply of the sensor electronics and also a sensor signal can be discharged.” p. 4, the “In the Fig. 1 to 4” para., Figs. 1-5).
Therefore, based on Sehlhoff’s teachings, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention of Cuddihy to employ the IoT radar sensor that is installed semi-recessed by a fixing frame and a spring clip inside an installation hole formed in the ceiling of the bedroom in a built-in manner, the fixing frame that is inserted into the installation hole to support a lower portion of the IoT radar sensor and that has an opening through which the IoT radar sensor is exposed, and the spring clip that is positioned between the installation hole and the fixing frame, and is configured to fix the fixing frame within the installation hole with elasticity of the spring clip, as taught by Sehlhoff, in order to facilitate installing the sensor while improving its appearance.
Regarding claim 3, Cuddihy modified by Sehlhoff teaches the health care monitoring and smart home convergence system of claim 2.
Cuddihy does not teach that the IoT radar sensor is powered by being coupled to a wire harness connected to the installation hole from the inside of the ceiling.
However, in the built-in sensors and sensing systems field of endeavor, Sehlhoff discloses a built-in passive infrared sensor device, which is analogous art. Sehlhoff teaches that the IoT radar sensor is powered by being coupled to a wire harness connected to the installation hole from the inside of the ceiling (“In a rear end region of the insert section 3 is a connection socket 7, designed here for integration into a KNX home bus system, via the connector socket 7, the power supply of the sensor electronics and also a sensor signal can be discharged.”; p. 4, the “In the Fig. 1 to 4” para., l. 7-11; Figs. 1-5).
Therefore, based on Sehlhoff’s teachings, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention of Cuddihy to employ the IoT radar sensor that is powered by being coupled to a wire harness connected to the installation hole from the inside of the ceiling, as taught by Sehlhoff, in order to facilitate installing the sensor while improving its appearance by hiding its wiring in the ceiling.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Cuddihy as applied to claim 1, and further in view of Asianto et al (US 20180220973), hereinafter, Asianto.
Regarding claim 13, Cuddihy teaches the health care monitoring and smart home convergence system of claim 1.
While teaching a sensor (“PIR”) installed in the user's home ([0021]), Cuddihy does not teach a fall detection sensor configured to detect a fall that occurs to the user while walking in a set area,
wherein the health analysis part is configured to detect that the fall has occurred when a positioning change speed of an object recognized by the fall detection sensor is equal to or greater than a set value and a central axis of the object in the shape of a column of which the central axis is perpendicular to the ground makes positioning change horizontal to the ground and remains in changed positioning for a set period of time or longer.
However, in the smart devices field of endeavor, Asianto discloses smart devices that capture images and sensed signals, which is analogous art. Asianto teaches a fall detection sensor (145) (“A given distance/proximity sensor 145 can include or be a radar-based distance/proximity sensor,” [0096]; “the gyroscopes/accelerometers” [0169]) configured to detect a fall that occurs to the user while walking in a set area (“the PWSD assistive apparatus or device, and/or the set of remote servers can issue a set of alerts to one or more target electronic/computing destinations associated with particular individuals or organizations having an interest in whether the PWSD user's physical location/position/orientation has changed relative to the user's … expected … position/orientation.” [0063]; Figs. 12A-C),
wherein the health analysis part (“portable/wearable smart device (PWSD)” [0017]) is configured to detect that the fall has occurred when a positioning change speed of an object recognized by the fall detection sensor (1720-1740) (“A third process portion 1720 involves identifying/recognizing particular features, shapes, structures, and/or objects within the composite image dataset(s) under consideration.” [0163]; “A fourth process portion 1730 involves determining the orientation(s) of one or more identified/recognized features, structures, and/or objects within the composite image(s) relative to the PWSD's x-axis, y-axis, and/or z-axis; and a fifth process portion 1740 involves determining whether such orientations are normal/expected/upright, thereby indicating that the PWSD user is in a normal/expected/upright orientation.” [0164]; Fig. 11B) is equal to or greater than a set value (“the gyroscope/accelerometer signals will indicate that a shock or impact has occurred” [0169]; Figs. 12B-C) and a central axis of the object in the shape of a column of which the central axis is perpendicular to the ground (“a normal upright position” [0169]; Fig. 12A) makes positioning change horizontal to the ground (Figs. 12B-C) and remains in changed positioning for a set period of time or longer (“If the orientation(s) of one or more identified/recognized features, structures, and/or objects are not or are not likely normal/expected/upright, a sixth process portion 1742 flags the presently analyzed composite image dataset(s) with an atypical/fall indicator.” [0164] “As indicated in FIG. 12B, in the event that the PWSD user experiences a fall that orients them in a first fallen position, or as indicated in FIG. 12C in the event that the PWSD user experiences a fall that orients them in a second fallen position, the signals output by the gyroscopes/accelerometers, the distance/proximity sensors 145, … will suddenly, significantly, or dramatically change compared to their values while the PWSD user maintained a normal upright position such as shown in FIG. 12A. More particularly, the gyroscope/accelerometer signals will indicate that a shock or impact has occurred; the distance/proximity sensors 145 will typically generate one or more distance measurements indicating that the PWSD 100 is near or adjacent to the ground;” [0169] Figs. 11B, 12B-C).
Therefore, based on Asianto’s teachings, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention of Cuddihy to employ a fall detection sensor configured to detect a fall that occurs to the user while walking in a set area, wherein the health analysis part is configured to detect that the fall has occurred when a positioning change speed of an object recognized by the fall detection sensor is equal to or greater than a set value and a central axis of the object in the shape of a column of which the central axis is perpendicular to the ground makes positioning change horizontal to the ground and remains in changed positioning for a set period of time or longer, as taught by Asianto, in order to facilitate monitoring user's physical location/position/orientation to provide a medical assistance to the user when needed.
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Cuddihy as applied to claim 1, and further in view of Lee et al (US 20260207878), hereinafter, Lee.
Regarding claim 14, Cuddihy teaches the health care monitoring and smart home convergence system of claim 1.
Cuddihy does not teach an environment controller configured to control color, illuminance, and on/off operation of lighting in the user's home depending on at least one selected from a group of the user's types of sleep, life response, current time, weather, whether the user has gone out, and whether the user has fallen.
However, in the smart devices field of endeavor, Lee discloses a method, apparatus, and system for creating environment through AI-based non-contact sleep analysis, which is analogous art. Lee teaches an environment controller (30) configured to control color, illuminance, and on/off operation of lighting in the user's home depending on at least one selected from a group of the user's types of sleep, life response, current time, weather, whether the user has gone out, and whether the user has fallen (“FIG. 2b is a block diagram illustrating an environment adjustment device equipped with a sleep state information generation means” [0398]; “when the processor 130 identifies that the user has entered a sleep stage (e.g., light sleep) through the user's sleep stage information, it can generate external environment adjustment information to … minimize illumination to create a darkroom environment, or control smart home-appliances to perform tasks such as …, lighting LEDs … thereby facilitating restful sleep. By creating the optimal illumination for each sleep stage of the user, i.e., the optimal sleep environment, the user's sleep efficiency can be improved.” [0836]; Fig. 2b).
Therefore, based on Lee’s teachings, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention of Cuddihy to employ an environment controller configured to control color, illuminance, and on/off operation of lighting in the user's home depending on at least one selected from a group of the user's types of sleep, life response, current time, weather, whether the user has gone out, and whether the user has fallen, as taught by Lee, in order to facilitate monitoring user's physical location/position/orientation and physical state to provide assistance to the user as needed.
Claims 16-17 are rejected under 35 U.S.C. 103 as being unpatentable over Cuddihy as applied to claim 15, and further in view of Mushtaq et al (US 20230218225), hereinafter, Mushtaq.
Regarding claim 16, Cuddihy teaches the health care monitoring and smart home convergence system of claim 15.
Cuddihy does not teach that the health analysis part is configured to receive, from the user, the user's waist circumference or blood pressure measurement value or both, and generate the health prediction information further including the received waist circumference or blood pressure measurement value.
However, in the medical devices and systems field of endeavor, Mushtaq discloses a centralized hub device for determining and displaying health-related metrics, which is analogous art. Mushtaq teaches that the health analysis part (1902) is configured to receive, from the user, the user's waist circumference or blood pressure measurement value or both, and generate the health prediction information (2116) further including the received waist circumference or blood pressure measurement value (“Risk quantification 2116 can also be performed to determine an overall health index for the user 1904, which can be based on all the values 2114 for the vital signs 2102. The health index can, for example, be based on sleep session data, SpO.sub.2, and blood pressure.” [0291] “The heartrate sensor 2526 can be configured to detect the user's heartrate while they are in bed. The hub device 1902 can use the heartrate signal and Pulse Transmit Time (PTT) to estimate the user's blood pressure... The hub device 1902 can analyze the estimated blood pressure to determine whether the user is experiencing or developing any health-related issues/conditions.” [0330]).
Therefore, based on Mushtaq’s teachings, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention of Cuddihy to employ the health analysis part that is configured to receive, from the user, the user's waist circumference or blood pressure measurement value or both, and generate the health prediction information further including the received waist circumference or blood pressure measurement value, as taught by Mushtaq, in order to facilitate monitoring user's health to provide a medical assistance to the user when needed.
Regarding claim 17, Cuddihy teaches the health care monitoring and smart home convergence system of claim 15.
Cuddihy does not teach that the health analysis part is configured to generate a health score by comparing a reference value with at least one selected from a group of the user's heart rate, respiratory rate, sleep duration, and inactivity time, and provide the health score by including the health score in the health prediction information.
However, in the medical devices and systems field of endeavor, Mushtaq discloses a centralized hub device for determining and displaying health-related metrics, which is analogous art. Mushtaq teaches that the health analysis part (2106) is configured to generate a health score (2116) by comparing a reference value (“any deviation outside reference values” [0290]) with at least one selected from a group of the user's heart rate (2102) (“HR” [0290]), respiratory rate, sleep duration, and inactivity time, and provide the health score by including the health score in the health prediction information (“Next, the decision engine 2106 can perform risk quantification 2116. Risk quantification 2116 can be performed to determine whether the vital signs 2102 are trending so outside of the vitals ranges 2108 that the vital signs 2102 should be reported out to the healthcare provider(s) 2118. The decision engine 2106 can detect any deviation outside reference values for any metrics, such as the vital signs 2102…a model can be trained to calculate: z=w1*HR+w2*HRV+w3*RR+w4*SpO.sub.2+w5*BP and to estimate a risk level based on: Risk=1/(1+exp(−z)),” [0290] “The heartrate sensor 2526 can be configured to detect the user's heartrate while they are in bed.” [0330]).
Therefore, based on Mushtaq’s teachings, it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the invention of Cuddihy to employ the health analysis part that is configured to generate a health score by comparing a reference value with at least one selected from a group of the user's heart rate, respiratory rate, sleep duration, and inactivity time, and provide the health score by including the health score in the health prediction information, as taught by Mushtaq, in order to facilitate monitoring user's health to provide a medical assistance to the user when needed.
Allowable Subject Matter
Claims 5-7 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALEXEI BYKHOVSKI whose telephone number is (571)270-1556. The examiner can normally be reached on Monday-Friday: 8:30am - 5:00pm.
Examiner interviews are available via telephone, in-person, 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.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Pascal Bui Pho can be reached on 571-272-2714. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/ALEXEI BYKHOVSKI/
Primary Examiner, Art Unit 3798
Prosecution Insights