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 .
Response to Arguments
Applicant’s arguments filed 05/21/2026 have been fully considered but are not persuasive or are moot in view of new grounds of rejection.
Applicant argues, “… the specification explains that conventional pulse oximetry and related physiological measurements are sensitive not only to emotional background but also to physical activity, thereby reducing the accuracy of psycho-emotional assessment during user movement. The specification then explains that the invention achieves a technical result by simultaneously using multiple physiological sensors together with coordinated analysis and correction of sensor data, thereby allowing accurate psycho-emotional assessment "even during periods of activity." See [0014]. Paragraph [0015] further sets forth that accelerometer data and photoplethysmogram data are jointly analyzed to determine periods and levels of physical activity during psycho-emotional assessment generation, thereby improving the accuracy of heart-rate variability determination and psycho-emotional state assessment. Accordingly, the claims are directed to improving wearable physiological monitoring technology itself.”
Examiner respectfully states that although the instant invention may provide improvements, the claimed invention does not overcome the 35 U.S.C. 101 rejection since claims 1 and 10 are still directed to abstract ideas and are therefore not patent eligible.
Furthermore, the recited “wherein, when the periods of physical activity are detected, the analysis unit is configured to reprocess photoplethysmogram data and electrodermal activity sensor data at time intervals corresponding to the detected periods of physical activity using stronger data filtering algorithms, and to repeat feature extraction after the reprocessing before determining the psycho- emotional state of the user” are interpreted as mental processes, since they’re directed to using judgement or evaluation to reprocess data to determine the psycho- emotional state of the user and to adjust data filtering algorithms.
Further, there is nothing in the claims which integrates the judicial exception into a practical application.
Applicant argues, “…the claims are directed to a concrete technological process that dynamically modifies physiological signal processing based on detected movement conditions in order to improve physiological signal integrity and psycho-emotional classification accuracy in a wearable monitoring environment. These operations cannot practically be performed mentally or with pen and paper. A human mind cannot practically perform synchronized physiological signal acquisition from multiple sensors, movement-triggered adaptive filtering, repeated feature extraction, HRV analysis from P-P intervals, electrodermal phase/frequency decomposition, and machine-learning-based arousal detection in the claimed manner.”
Examiner respectfully states that although the claim recites limitations that cannot be practically performed mentally or with pen and paper, the claim still recites the following additional elements:
- a photoplethysmogram sensor;
- a microcontroller;
- an accelerometer;
- an electrodermal activity sensor;
- an analysis unit configured to generate data for assessing the psycho-emotional state of the user on the basis of based on the signals generated by of the photoplethysmogram sensor, the accelerometer, and the electrodermal activity sensor.
As stated above, the additional elements are directed to insignificant extra solution activities and merely process information and then provide the results of the above identified abstract ideas.
There is nothing in the claims which show how providing the above recited limitations integrates the judicial exception into a practical application.
Applicant agues, “Nor do the claims merely recite generic computer implementation. The specification repeatedly emphasizes that the claimed architecture improves wearable physiological monitoring technology itself. See [0014]-[0015], [0034], [0039], and [0070]-[0071]. The claims improve physiological signal reliability during user movement by selectively reprocessing physiological sensor data corresponding to detected movement periods before psycho-emotional classification. This constitutes a technological improvement to wearable physiological monitoring systems, not an abstract idea implemented on generic hardware.”
Examiner respectfully disagrees. The recited, “microcontroller” is directed toward a generically recited computer element which does not improve the functioning of a computer, or any other technology or technical field.
In other words, these claims are merely directed to an abstract idea with additional generic computer elements which do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer.
Applicant argues, “The Examiner further asserts that the claimed "provide" or graphing limitations constitute insignificant post-solution activity. However, the claims as amended are directed not to mere presentation of information, but rather to a specific movement-aware physiological signal- processing architecture that produces improved psycho-emotional assessment data through repeated adaptive preprocessing and feature extraction. The graphing and output operations occur only after the claimed technological improvements in physiological signal processing have been performed.”
Examiner respectfully disagrees and states that the recited limitation is directed toward insignificant extra solution activity related to graphically outputting the user’s psycho-emotional state.
There is nothing in the claims which show how providing the above recited limitations integrates the judicial exception into a practical application.
Applicant argues, “The cited references likewise fail to disclose this arrangement, confirming that the claimed architecture was not merely well-understood, routine, or conventional.”
Examiner respectfully disagrees. Fedor et al. (US 2019/0117143) discloses a wearable device (fig. 3A: 300) for measuring physiological signals [0072] comprising of
- a photoplethysmogram sensor (304; [0072]),
- a microcontroller [0109],
- an accelerometer (301; [0072]),
- an electrodermal activity sensor (302; [0072]), and
- an analysis unit ([0076]: server 441 is a remote analysis server that receives data from physiological sensors such as sensor 300 and tracks physiological data of users).
Thus, the limitations directed to the photoplethysmogram sensor, the microcontroller, the accelerometer, the electrodermal activity sensor, and the analysis unit are well-understood, routine, and conventional, as evidenced by the reference above.
Additionally, in regards to the data filtering algorithms and machine learning recited in claim 10, Fedor further teaches EDA signal being filtered [0029] and accelerometer data being filtered [0031], as well as a machine learning model [0008] trained to make predictions [0008] such as a patient’s level of depression [0013].
Thus, the limitations directed to the photoplethysmogram sensor, the microcontroller, the accelerometer, the electrodermal activity sensor, the analysis unit, the data filtering algorithms, and machine learning are well-understood, routine, and conventional, as evidenced by the reference above.
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 1-17 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.
In re claim 1, the limitation, “the device” is unclear regarding whether this is a new limitation that lacks antecedent basis, or if it is directed to the earlier recited limitation, “a wearable device”. For examination purposes, the limitation, “the device” is interpreted as being directed to the earlier recited “a wearable device”.
In re claim 1, the limitation, “the signals” lack antecedent basis.
In re claim 12, the limitation, “the extracting step” is unclear regarding whether this is a new limitation that lacks antecedent basis, or if it is directed to the earlier recited limitation, “extracting relevant data” (claim 10). For examination purposes, the limitation, “the extracting step” is interpreted as being directed to the earlier recited “extracting relevant data”.
Appropriate correction is required.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-17 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception, specifically an abstract idea without significantly more.
Step 1:
Independent claim 1 is directed to a wearable device for monitoring data indicative of a psycho-emotional state of a user. Thus, it is directed to statutory categories of invention.
Step 2A, Prong 1:
Claim 1 recites the following claim limitations:
“perform preliminary analysis of the data from the accelerometer and photoplethysmogram sensor to determine periods and levels of physical activity of the user during generation of the data for assessing the psycho-emotional state of the user” (mental process – judgement or evaluation used to determine periods and levels of physical activity of the user) and
“wherein, when the periods of physical activity are detected, the analysis unit is configured
to reprocess photoplethysmogram data and electrodermal activity sensor data at time intervals corresponding to the detected periods of physical activity using stronger data filtering algorithms, and
to repeat feature extraction after the reprocessing before determining the psycho- emotional state of the user” (mental process – judgement or evaluation used to reprocess data to determine the psycho- emotional state of the user and to adjust data filtering algorithms).
The above recited limitations are directed to mental processes, since a person could analyze information from the accelerometer and photoplethysmogram sensor to determine periods and levels of physical activity of the user to determine their psycho-emotional state or to adjust a filtering algorithm.
Additionally, regarding the following limitations in claim 10,
“- performing data preprocessing using the analysis unit;
- extracting relevant data from the processed data using the analysis unit;
- detecting periods of user's movements based on the relevant data using the analysis unit;
- re-processing…
- re-extracting relevant data from the processed data within the periods of user's movements using the analysis unit;
…- classifying psycho-emotional state based on the extracted data using the machine learning or analytical model”,
Examiner asserts that the above recited limitations are also directed to mental processes, since they involve a person extracting and processing relevant information and moving it around to classify the user’s psycho-emotional state.
These limitations, under their broadest reasonable interpretation, cover concepts that can be practically performed in the human mind, i.e., using pen and paper (i.e. mental processes directed to organizing and evaluating data).
Step 2A, Prong 2:
Claim 1 recites the following additional elements: “the device comprises:
- a photoplethysmogram sensor;
- a microcontroller;
- an accelerometer;
- an electrodermal activity sensor;
- an analysis unit configured to generate data for assessing the psycho-emotional state of the user on the basis of based on the signals generated by of the
photoplethysmogram sensor,
the accelerometer, and
the electrodermal activity sensor.
The following limitations:
- a photoplethysmogram sensor
- an accelerometer
- an electrodermal activity sensor
- an analysis unit configured to generate data for assessing the psycho-emotional state of the user on the basis of based on the signals generated by of the photoplethysmogram sensor, the accelerometer, and the electrodermal activity sensor,
are interpreted as insignificant extra solution activities. Specifically, the above recited limitations are directed towards pre-solution activity (see MPEP §2106.05(g)) since they’re used to obtain information about the user to generate data regarding the user’s psycho-emotional state based on the data from the sensors (i.e. mere data gathering).
Additionally, the following limitations recited in claim 10,
“-stronger data filtering algorithms using the analysis unit;
- the reextracted relevant data are fed to a machine learning or analytical model using the analysis unit”
are similarly directed to insignificant extra solution activities, specifically pre-solution activity, since they are also used to obtain information to determine the user’s psycho-emotional state.
Regarding the limitation, “determine periods and levels of physical activity of the user during the said generation of data for assessing the psycho-emotional state of the user”, Examiner asserts that these limitations are directed to mental processes, as discussed above. However, for the same of argument, although Examiner asserts that the above recited limitations are interpreted as a mental concept, for the sake of argument, Examiner asserts that the above limitations would not integrate the abstract ideas into a practical application. For instance, the limitations are not particular and instead are considered insignificant extra solution activity that is used to provide periods and levels of physical activity that will be used in the determination of the psycho-emotional state of the user.
The above recited limitations merely process information and then provide the results of the above identified abstract ideas. Additionally, the recited providing is neither particular enough to meaningfully limit the recited exception nor does it have more than a nominal relationship to the exception. In other words, the breadth of the recited “determine” is such that it substantially encompasses all applications of the recited exception (such as moving information around and analyzing).
Similarly, regarding the limitation, “plotting a graph of the user's psycho-emotional state”, Examiner asserts that the recited limitation is also directed toward insignificant extra solution activity related to graphically outputting the user’s psycho-emotional state.
There is nothing in the claims which show how providing the above recited limitations integrates the judicial exception into a practical application.
Further, there is no evidence of record that would support the assertion that this step is an improvement to a computer or a technological solution to a technological problem.
In other words, these claims are merely directed to an abstract idea with additional generic computer elements which do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer.
Further, the limitation: “a microcontroller”, is directed toward a generically recited computer element which do not improve the functioning of a computer, or any other technology or technical field.
Accordingly, the combination of these additional elements is no more than insignificant extra solution activity. Thus, the abstract ideas are not integrated into a practical application.
Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Additionally, regarding the wearable device, Applicant’s specification discloses: “the device comprises a microcontroller, a photoplethysmogram sensor, an accelerometer, a skin electrical activity sensor, and an analysis unit” [0015].
Regarding the analysis unit, Applicant’s specification discloses: “It should be noted that structurally the analysis unit can be located in the device housing as well as can be distributed, i. e. have some remote computing power, with wireless communication between them” [0039].
Regarding the limitations directed to
the photoplethysmogram sensor,
the microcontroller,
the accelerometer,
the electrodermal activity sensor, and
the analysis unit,
see Fedor et al. (US 2019/0117143), which discloses a wearable device (fig. 3A: 300) for measuring physiological signals [0072] comprising of
- a photoplethysmogram sensor (304; [0072]),
- a microcontroller [0109],
- an accelerometer (301; [0072]),
- an electrodermal activity sensor (302; [0072]), and
- an analysis unit ([0076]: server 441 is a remote analysis server that receives data from physiological sensors such as sensor 300 and tracks physiological data of users).
Thus, the limitations directed to the photoplethysmogram sensor, the microcontroller, the accelerometer, the electrodermal activity sensor, and the analysis unit are well-understood, routine, and conventional, as evidenced by the reference above.
Additionally, in regards to the data filtering algorithms and machine learning recited in claim 10, Fedor further teaches EDA signal being filtered [0029] and accelerometer data being filtered [0031], as well as a machine learning model [0008] trained to make predictions [0008] such as a patient’s level of depression [0013].
Thus, the limitations directed to the photoplethysmogram sensor, the microcontroller, the accelerometer, the electrodermal activity sensor, the analysis unit, the data filtering algorithms, and machine learning are well-understood, routine, and conventional, as evidenced by the reference above.
As discussed with respect to Step 2A, Prong 2 above, the additional elements in the claim amount to no more than insignificant extra solution activity and applying the exception in a general way.
Moreover, implementing an abstract idea on a generic computer, does not add significantly more, similar to how the recitation of the computer in the claim in Alice amounted to mere instructions to apply the abstract idea of intermediated settlement on a generic computer.
Thus, none of the claims 1-17 amount to significantly more than the abstract idea itself. Accordingly, claims 1-17 are not patent eligible and rejected under 35 U.S.C. 101 as being directed to abstract ideas in view of the Supreme Court Decision in Alice Corporation Pty. Ltd. v. CLS Bank International, et al., MPEP §2106.04(a)(2), MPEP §2106.04(d)(2),and MPEP §2106.05(g).
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.
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.
Claims 1-4, 9-11 and 14-16 are rejected under 35 U.S.C. 103 as being unpatentable over Shah (US 2022/0361788) in view of Nakamura (US 2015/0088013).
In re claim 1, Shah discloses a wearable device (fig. 2: 200; [0110]: combinations may be made between various examples) for monitoring data [0043-0044] indicative of a psycho-emotional state of a user ([0038]: sensors measure physiological changes; [0062]: measured parameters used to determine emotional or cognitive stress which are psycho-emotional states),
the device comprises:
- a photoplethysmogram sensor ([0022]: heart sensor may be provided using PPG sensor);
- a microcontroller ([0037-0038]: inherent that a smart watch with integrated sensors would have a microcontroller controlling information received from the sensors and transmitted to user device 116);
- an accelerometer [0025];
- an electrodermal activity sensor ([0030]: skin sensor 112 may measure electrodermal activity; [0061]);
- an analysis unit (118; [0042]) configured to generate data for assessing the psycho-emotional state of the user based on the signals generated by the photoplethysmogram sensors, the accelerometer, and the electrodermal activity sensor ([0052]: EHR server 118 generates a stress reading based on received sensor information);
wherein the analysis unit is configured to perform preliminary analysis of the data from the accelerometer and photoplethysmogram sensor to determine periods ([0064-0065]: preliminary analysis occurs before stress measurements are made to determine which periods occur during exercise and therefore need to be excluded and would involve the use of the accelerometer and PPG sensor (heart rate sensor) to detect exercise) and levels of physical activity of the user during generation of the data for assessing the psycho-emotional state of the user ([0064-0065]: levels of physical activity and afterwards may be excluded from stress measurements so only relevant information regarding stress levels is used); and
wherein, when the periods of physical activity are detected [0064-0065], the analysis unit is configured
to reprocess photoplethysmogram data and electrodermal activity sensor data at time intervals corresponding to the detected periods of physical activity using data filtering algorithms ([00654-0065]: stress reading measurements are reprocessed to exclude the stress reading measurements that were measured during exercise and 45 minutes after exercise and would have to be done with data filtering algorithms based on the elevated heart and accelerometer readings), and
*to repeat feature extraction after the reprocessing before determining the psycho- emotional state of the user ([0062-0065]: stress reading measurement excludes stress measurements from when the user was exercising and afterwards, which means they must be extracted from measured real time physiological parameters before determining the psycho- emotional state of the user).
Shah fails to disclose wherein, when the periods of physical activity are detected, the analysis unit is configured to reprocess photoplethysmogram data and electrodermal activity sensor data at time intervals corresponding to the detected periods of physical activity using stronger data filtering algorithms.
Nakamura teaches a pulse detector [0002] for calculating pulse information [0009] and teaches
wherein, when periods of physical activity are detected ([0094]: detects whether exercise is intense or gentle; [0009]: determination unit determines exercise state of a subject), an analysis unit ([0009]: control unit adjusts calculation based on determination result of the exercise state) is configured
to process pulse wave data ([0004]: pulse wave sensor provides signal corresponding to blood flow rate and is related to a pulse) and body motion data [0009] at time intervals ([0077-0078]: initial pulse information calculation is interpreted as processing; fig. 2: processing of body motion detection signal occurs before an adaptive filter coefficient is applied; [0084]: pulse information is calculated based on an interval), and
to reprocess the pulse wave data and the body motion data at time intervals corresponding to the detected periods of physical activity using stronger data filtering algorithms ([0094]: intense exercise results in a large number of filters i.e. stronger data filtering than gentle exercise; [0167]: calculation processing rate and body motion rate are controlled based on exercise state to switch between low and high power consumption; fig. 2: adaptive filter coefficient is applied to create a residual signal).
*Additionally, regarding the limitations, “to repeat feature extraction after the reprocessing before determining the psycho- emotional state of the user”, at the time the instant application was filed, it would be obvious to try to provide wherein, when the periods of physical activity are detected, the analysis unit is configured to repeat feature extraction after the reprocessing before determining the psycho- emotional state of the user. Furthermore, when there is a design need or market pressure to solve a problem and there are a finite number of identified, predictable solutions, 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, 550 U.S. at 421, 82 USPQ2d at 1397, especially since the claimed repeat feature extraction step is not disclosed as being crucial or unexpected, and a person of ordinary skill at the time the instant application was filed would consider repeating feature extraction after reprocessing the photoplethysmogram data and electrodermal activity sensor data at time intervals corresponding to the detected periods of physical activity so that the photoplethysmogram data and electrodermal activity sensor data are relevant to the determination of the psycho- emotional state of the user.
In re claim 2, Shah discloses
wherein the device additionally comprises at least one of the following sensors:
a muscle activity sensor,
a light sensor ([0022]: heart rate sensor 106 employs light sensors),
a temperature sensor,
a humidity sensor,
a sound recording device ([0037]: voice sensor 104 would be a sound recording device), and
wherein the analysis unit is configured to take into account the data received from the said sensors during the said preliminary analysis ([0064-0065]: elevated heart and accelerometer readings used for preliminary analysis are collected from the said sensors; [0022-0023, 0025]).
In re claim 3, Shah discloses wherein
the analysis unit is configured to be located separately from the wearable device (fig. 1: 118 is remote from sensors 102-114 which would be on the wearable device; [0040, 0044]),
the analysis unit is configured to provide wireless communication with the wearable device ([0044]: watch and EHR server 118 may communicate wirelessly; [0039-0040]).
In re claim 4, Shah discloses wherein the analysis unit is configured to perform at least one of the following:
downsampling to ensure matching time stamps of the data,
randomly reducing or discarding samples for unbalanced samples,
cleansing the data from outliers and anomalies ([0064-0065]: outliers such as physiological measurements affected during exercise may be excluded).
In re claim 9, Shah discloses wherein the device comprises a data transmission module ([0044]: watch transmits information to user device 116 or EHR server 118 and therefore must have a data transmission module that transmits the information).
In re claim 10, Shah discloses a method of analyzing [0042], processing [0042] and correcting [0064-0065] data received from the device (see above) for monitoring a psycho-emotional state of a user according to claim 1 (see above), wherein:
performing data preprocessing using the analysis unit ([0055]: physiological measurements being filtered to remove noise is preprocessing and method 700 is performed by the HER server; fig. 7: 705);
- extracting relevant data ([0055]: filtered data from plurality of sensors) from the processed data using the analysis unit ([0055]: filtered data from the physiological measurements are extracted);
- detecting periods of user's movements based on the relevant data using the analysis unit ([0064-0065]: periods of exercising are detected by the EHR server; [0025-0026]: accelerometer is used to detect motion);
- re-processing ([0064-0065]: periods of exercise are excluded i.e. they are re-processed) with data filtering algorithms using the analysis unit the photoplethysmogram data and electrodermal activity sensor data at time intervals corresponding to the detected periods of user’s movement when the periods of user’s movements are detected;
- re-extracting relevant data from the processed data within the periods of user's movements using the analysis unit (see in re claim 1 above, where feature extraction is repeated);
- feeding the re-extracted relevant data a machine learning or analytical model using the analysis unit ([0078]: the measured parameters are weighted and therefore fed into an analytical model that assigns them weight when determining stress readings; [0060]: appropriate weights applied based on the user; [0083]);
- classifying psycho-emotional state based on the extracted data using the machine learning or analytical model ([0071]: stress readings are provided on a scale from 1-100 i.e. they are classified and the parameters may be weighted differently; [0060]);
- plotting a graph (fig. 6) of the user's psycho-emotional state (fig. 6; [0053]).
Shah fails to disclose
- re-processing with stronger data filtering algorithms using the analysis unit the photoplethysmogram data and electrodermal activity sensor data at time intervals corresponding to the detected periods of user’s movement when the periods of user’s movements are detected.
Regarding the limitation, “re-processing with stronger data filtering algorithms using the analysis unit the photoplethysmogram data and electrodermal activity sensor data at time intervals corresponding to the detected periods of user’s movement when the periods of user’s movements are detected”, see the proposed combination yielded in re claim 1 above.
In re claim 11, regarding the limitation, “wherein at least one of the following is performed in the step of data preprocessing: -
downsampling to ensure matching time stamps of the data;
- randomly reducing or discarding samples for unbalanced samples;
- cleansing the data from outliers and anomalies”,
see in re claim 4 above.
In re claim 14, the proposed combination yields (all mapping directed to Shah unless otherwise stated) wherein the graph of the psycho-emotional state of the user is additionally transmitted to a mobile application by means of a data transmission module ([0051]: EHR server may display results for a user to access from an app; [0089]: app may be on a cell phone; [0011]; fig. 6).
In re claim 15, Shah discloses wherein relevant data are collected and annotated to classify the psycho-emotional state of the user ([0071-0072]: grid of stress readings is provided and compares the stress readings to a user’s own personal baseline i.e. the relevant data is annotated to determine if it’s above or below the baseline level to determine what emotional state the user is in; [0083]: changes in breathing patterns is indicative of emotional states; [0015]: measurements analyzed to determine the stress level i.e. psycho-emotional state of the user).
In re claim 16, Shah discloses wherein at least one of the methods is used to annotate relevant data:
- periodic annotation ([0031]: detection of a fever is a periodic annotation; [0064-0065]: periods of exercise are excluded; [0071]: stress readings may be determined over a 24-hr period, therefore, stress readings are annotated periodically to determine stress over the course of a day or if data should be excluded, as discussed above);
- filling out a self-assessment questionnaire by the user ([0057]: user may input their perception of current stress level);
- an observer's assessment of a level of stress and/or an emotional state during the data collection period.
Claims 5 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Shah (US 2022/0361788) in view of Nakamura (US 2015/0088013) in view of Xu et al. (US 2021/0000403).
In re claim 5, Shah fails to disclose wherein the analysis unit is configured to perform feature extraction including at least the following:
- decomposition into phase and tonic components using a convex optimization approach with sliding windows ranging from 10 to 20 minutes for electrodermal activity sensor data;
- calculation of heart rate variability by P-P intervals of photoplethysmogram and its use for calculation of parameters of temporal and frequency analysis of heart rate variability;
- calculation of a vector of averaged accelerations within an observed time window or deviation of acceleration vectors from each other.
Xu teaches a stress detection method (fig. 2: combination of S301-S303) comprising of a calculation of heart rate variability [0077] by P-P intervals ([0167]: change in heart rate may be based on adjacent peak intervals; [0077]: RRinterval is used which would be consistent with the P-P interval in a normal heart) of photoplethysmogram [0076-0077] and its use for calculation of parameters of temporal ([0077]: features such as RMSSD and SDNN may be obtained; see Applicant’s specification [0054]: “temporal (such as SDNN, RMS-SD”) and frequency analysis of heart rate variability ([0077]: low frequency and high frequency power may be obtained; see Applicant’s specification [0054]: “frequency (Total Power, Low/High Frequency)”).
Xu further teaches obtaining HRV parameters (such as RMSSD and low/high frequency power) so they can be analyzed and used to obtain a stress value of a user [0077].
It would have been obvious to someone of ordinary skill in the art at the time the instant invention was filed to modify the wearable device taught by Shah, to provide calculation of heart rate variability by P-P intervals of photoplethysmogram and its use for calculation of parameters of temporal and frequency analysis of heart rate variability, as taught by Xu, because HRV parameters can be analyzed and used to obtain a stress value of a user.
In re claim 12, regarding the limitations, “wherein the extracting step comprises:
- decomposition into phase and tonic components using a convex optimization approach with sliding windows ranging from 10 to 20 minutes for electrodermal activity sensor data;
- calculation of heart rate variability by P-P intervals of photoplethysmogram and its use for calculation of parameters of temporal and frequency analysis of heart rate variability;
- calculation of the vector of averaged accelerations within the observed time window or deviation of acceleration vectors from each other”,
see in re claim 5 above.
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Shah (US 2022/0361788) in view of Nakamura (US 2015/0088013) in view of Johnstone et al. (US 2020/0275875).
In re claim 6, Shah fails to disclose wherein the analysis unit includes a model trained on relevant annotated data.
Johnstone teaches deriving and storing emotional conditions of humans [0002] and teaches
a wearable device [0027] comprising
a plurality of biosensors [0027] and an analysis unit ([0031]: remote computer system that processes raw biosignal data to generate emotion files), and
wherein the analysis unit includes a model trained on relevant annotated data ([0044]: wearable device regularly prompts user to input current emotion state and manually annotate a raw data file with their emotions so a model can be constructed that is unique to the user).
Johnstone further teaches that having a model trained on relevant annotated data constructs an emotion interpretation model that is unique to the user [0044].
It would have been obvious to someone of ordinary skill in the art at the time the instant invention was filed to modify the wearable device taught by Shah, to provide wherein the analysis unit includes a model trained on relevant annotated data, as taught by Johnstone, because having a model trained on relevant annotated data constructs an emotion interpretation model that is unique to the user.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Shah (US 2022/0361788) in view of Nakamura (US 2015/0088013) in view of Li et al. (US 2024/0130652).
In re claim 7, Shah fails to disclose wherein the electrodermal activity sensor is a two-electrode sensor with the electrodes of the interdigital type.
Li teaches
measuring physiological states of a driver [0004] using an electrodermal activity sensor (fig. 3A: sensor suite 300 includes pair of interdigitated electrodes 310 and 315; [0004, 0050-0051]),
wherein the electrodermal activity sensor is a two-electrode sensor (310 and 315; [0050-0051) with the electrodes of an interdigital type [0050-0051].
Li further teaches that the electrodes are interdigitated to increase electrical interaction between the electrodes so that sensitivity of skin impedance measurements is increased [0051].
It would have been obvious to someone of ordinary skill in the art at the time the instant invention was filed to modify the wearable device taught by Shah, to provide wherein the electrodermal activity sensor is a two-electrode sensor with the electrodes of an interdigital type, as taught by Li, because interdigitated electrodes increase electrical interaction between the electrodes to increase sensitivity of skin impedance measurements.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Shah (US 2022/0361788) in view of Nakamura (US 2015/0088013) in view of Ochs et al. (US 2013/0289413).
In re claim 8, Shah fails to disclose wherein the said preliminary analysis of the data in the analysis unit is performed using downsampling the signals received.
Ochs teaches determining physiological information from a PPG signal [0002] and teaches performing a preliminary analysis of data ([0054]: pre-determined set of processing operations to input signal 310) in an analysis unit (fig. 3: 304 is interpreted as an analysis unit; since it comprises processors that calculate physiological parameters [0051]; [0054]) by downsampling received signals ([0054]: pre-determined set of processing operations includes downsampling of a signal).
Ochs further teaches that a pre-determined set of processing operations are applied to a signal [0054] so that the signal may be appropriately analyzed and interpreted [0054], which includes downsampling [0054].
It would have been obvious to someone of ordinary skill in the art at the time the instant invention was filed to modify the wearable device taught by Shah, to provide wherein the said preliminary analysis of the data in the analysis unit is performed using downsampling the signals received, as taught by Ochs, because doing so will allow the signal to be appropriately analyzed and interpreted.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Shah (US 2022/0361788) in view of Nakamura (US 2015/0088013) in view of Voss et al. (US 2008/0183232).
In re claim 13, the proposed combination fails to yield wherein Hampel filter method is used for preprocessing with stronger data filtering algorithms.
Voss teaches measuring a physiological parameter of a subject [0029] and wherein a Hampel filter method [0111] is used for preprocessing with stronger data filtering algorithms ([0111]: Hampel filters are used to remove beats which are inconsistent and therefore would have stronger data filtering algorithms during preprocessing).
Voss further teaches that Hampel filters are used to remove outliers [0111] and beats that show sufficient degree of inconsistency [0111].
It would have been obvious to someone of ordinary skill in the art at the time the instant invention was filed to modify the wearable device yielded by the proposed combination, to provide wherein Hampel filter method is used for preprocessing with stronger data filtering algorithms, as taught by Voss, because Hampel filters are used to remove outliers and beats that show sufficient degree of inconsistency.
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Shah (US 2022/0361788) in view of Nakamura (US 2015/0088013) in view of Grigoreva (US 2012/0136283).
In re claim 17, the proposed combination fails to yield wherein a general level of anxiety and tension at data collection step is additionally determined by at least one of the methods:
- method using Spielberger-Hanin scale; and/or
- method with determining an individual minute.
Grigoreva teaches subjecting patients with psycho-emotional stress condition [0048] to a Spielberger-Hanin test [0048].
Grigoreva further teaches that the Spielberger-Hanin test is a well-known physiological test [0048] that is able to assess reactive anxiety level [0048].
It would have been obvious to someone of ordinary skill in the art at the time the instant invention was filed to modify the wearable device yielded by the proposed combination, to provide wherein the general level of anxiety and tension at data collection step is additionally determined by a Spielberger-Hanin scale, as taught by Grigoreva, because the Spielberger-Hanin test is a well-known physiological test that is able to assess reactive anxiety level.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure:
Vidrine et al. (US 6/018,677) discloses measuring and monitoring heart rate during exercise (abstract) and teaches re-evaluating heartbeat interval candidates (Col. 3, lines 16-27) after events such as exercise activity (Col. 3, lines 5-27) so that accidental correlations are rescinded (Col. 3, lines 5-27).
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Contact
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/RUMAISA RASHID BAIG/Examiner, Art Unit 3796 /William J Levicky/Primary Examiner, Art Unit 3796
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