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, see page 8, filed 10/13/2025, with respect to the objection to Claim 9 have been fully considered and are persuasive. The objection to Claim 9 has been withdrawn.
Applicant’s arguments, see pages 8-9, filed 10/13/2025, with respect to the rejection of Claims 3-4, 13-14, and 19 under 35 U.S.C. § 112(b) have been fully considered and are persuasive. The rejection of Claims 3-4, 13-14, and 19 under 35 U.S.C. § 112(b) has been withdrawn.
Applicant’s arguments, see pages 9-14, filed 10/13/2025, with respect to the rejection of Claims 1-20 under 35 U.S.C. § 101 have been fully considered and are persuasive. Specifically, the Examiner agrees the clause “wherein the data analysis system is configured to… execute actions based upon the information to improve the individual's health, the actions including: sending soothing tones to speakers of the earbuds to calm the individual and adjust their heart rate, heart rate variability and respiration” in Claim 1 and the substantially similar amendment in Claim 11 amount to significantly more than the abstract idea recite a treatment or prophylaxis. All other sections of the Applicant’s arguments regarding the rejection of the claims under 35 U.S.C. § 101 are considered moot. The rejection of Claims 1-20 under 35 U.S.C. § 101 has been withdrawn.
Applicant’s arguments, see pages 14-18, filed 10/13/2025, with respect to the rejection(s) of Claims 1, 3, 8-11, 13 and 18-20 under 35 U.S.C. § 103 have been fully considered. Upon further consideration, a new ground(s) of rejection is made in view of Söhne, Barnacka, and Siever. However, the applicant’s arguments are not entirely persuasive. The applicant has argued that “Barnacka does not teach or suggest the ability for its processing system to receive other physiological information at an interface, where the other physiological data is obtained by and sent to the interface from either one or more sensors external to the closed loop system that monitor the individual or from one or more external systems to the closed loop system, as recited in revised claim 1.” The examiner respectfully disagrees and believes Barnacka teaches this limitation in [0190], as explained below in the updated rejection(s) under 35 U.S.C. § 103.
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.
Claims 1, 3, 8-10, 11, 13, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Söhne et al (US 20200035337 A1, hereinafter Söhne) in view of Barnacka et al (US 20190247010 A1, cited in applicant IDS, hereinafter Barnacka) and Siever (US 20210183262 A1, hereinafter Siever).
Regarding Claim 1, Söhne discloses a closed loop system ([0001]), the system comprising:
an interface configured to receive biosignals (“For example logged are the HR, HRV, … Current (such as wearable) devices have or could have a lot of sensors on board which can be used to register these events automatically by using these sensors…”, [0122]; “Technology for sending heart, heart rate frequency, heart rate variability, flow, state information, heart pulse, pulse time into the cloud are for example client-server network, or peer-to-peer networks, or chain network”, [0187]); and
a data analysis system (“A method that automatically stimulates an adaptable and proactive life style by increasing flow that is secured in a partly decentralized fashion as a standalone decentralized end-user system such as a smart sport watch or app on a smart phone and partly centralized and secured as a (on request) big data system, which is envisioned and part of this invention and an embodiment of this invention”, [0187]; “Above methods are implemented as a program code on a computer readable media, and such program code is loaded into a computer, by which computer is behaving as method of claim 1. Several device types can be used for such a method. Examples are smart watch, smart phone, server machine, or cloud machine, which are behaving as one of the methods of claim 1”, [0052]) that monitors the received biosignals at the interface over time and identifies physiological data of the individual based upon the received biosignals (“FIG. 20 illustrates a scenario of real time measuring HR and HRV over time”, [0071]);
wherein the data analysis system creates a baseline autonomic nervous system profile of the individual over a time period from the identified physiological data (“The invented (for example flow) state value relation (FIG. 8) can be easily expressed in HR and HRV… for example the flow state could be; “worse”, “better” or “good”…”, [0081]), and wherein the baseline autonomic nervous system profile tracks changes to a physiological state of the individual over the time period (See Fig. 21; “In FIG. 21 is indicated for an embodiment of this invention the measured and calculated flow (vertical axes; low, mid and high level) values (indicated with 26) over time (horizontal axes)”, [0186]);
wherein the data analysis system identifies current physiological data of the individual from new biosignals received at the interface over a current time period, and identifies a current physiological state of the individual by mapping the current identified physiological data against the baseline autonomic nervous system profile (See Figs. 17-18; “FIG. 18 illustrates an example of different emotion (for example flow) states in which the user can be in. Illustrated with an oval (18) a set of real time HR values, and real time HRV values are calculated and illustrated in this figure. The emotions can be measured based upon embodiment of this invention in (relative and/or absolute) values of HR, and HRV”, [0128]; the intersection of all flow states can be considered the baseline);
wherein the data analysis system is configured to:
receive information including the new biosignals at the interface (“Technology for sending heart, heart rate frequency, heart rate variability, flow, state information, heart pulse, pulse time into the cloud are for example client-server network, or peer-to-peer networks, or chain network”, [0187]).
Söhne discloses the claimed invention except for expressly disclosing an in-ear biosensor system worn by an individual that detects biosignals including infrasound signals in ear canals of the individual, wherein the in-ear biosensor system includes earbuds;
an interface configured to receive the biosignals including infrasonic signals sent from the in-ear biosensor system worn by the individual;
wherein the data analysis system is configured to:
receive including other physiological data at the interface, wherein the other physiological data is obtained by and sent to the interface from either one or more sensors external to the closed loop system that monitor the individual or from one or more external systems to the closed loop system; and
execute actions based upon the information to improve the individual's health, the actions including: sending soothing tones to speakers of the earbuds to calm the individual and adjust their heart rate, heart rate variability and respiration and sending audio messages to the earbuds that recommend breathing exercises.
However, Barnacka teaches an in-ear biosensor system worn by an individual that detects biosignals (“A portable infrasonic body activity monitoring system including a headset and portable device”, Abstract) including infrasound signals in ear canals of the individual (“The acoustic transducers, such as one or an array of microphones, detects sound in the infrasonic and audible frequency ranges, typically from the user's ear canal”, [0043]), wherein the in-ear biosensor system includes earbuds (“a user 10 wears a head-mounted transducer system 100 in the form of right and left earbuds 102, 103, in the case of the illustrated embodiment. The right and left earbuds 102, 103 mount at the entrance or inside the user's two ear canals”, [0050]);
an interface configured to receive biosignals including infrasonic signals sent from the in-ear biosensor system worn by the individual (“The head-mounted transducer system provides an output data stream of detected acoustic signals and other data generated by the auxiliary sensors to the processing system such as a mobile computing device, such as for example, a smartphone or smartwatch or other carried or wearable mobile computing device and/or server systems connected the transducer system and/or the mobile computing device”, [0007]); and
wherein the data analysis system is configured to:
receive information (“Referring to FIG. 15 there is illustrated a network 1200 supporting communications to and from biosensor systems 50 for various users”, [0190]) including other physiological data at the interface, wherein the other physiological data is obtained by and sent to the interface from either one or more sensors external to the closed loop system that monitor the individual or from one or more external systems to the closed loop system (“Data from these users may be transferred online, e.g. to remote servers, server farms, data centers, computing clouds etc. More complex data analysis may be achieved using online computing resources, i.e. cloud computing and online storage. Each user preferably has the option of sharing data or the results of data analysis using for example social media, social network(s), email, short message services (SMS), blogs, posts, etc.”, [0067]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to add the infrasonic signals and in-ear biosensor of Barnacka to the system of Söhne, because such a system is discreet, accessible, easy to use, and cost-efficient, as taught by Barnacka ([0005]). In addition, infrasonic signals from a user hold information about the physical state of a user (Barnacka, [0018]). Furthermore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Söhne such that the other physiological data is obtained by and sent to the interface from either one or more sensors external to the closed loop system that monitor the individual or from one or more external systems to the closed loop system, as taught by Barnacka, for the advantage of connecting with other users on social media (Barnacka, [0190]).
Siever teaches wherein the data analysis system is configured to: execute actions based upon the information (“the headphones 30 produce sound in response to light and audio signals, respectively, provided by one or both of the control module 12 and the HRV module 2”, [0045]) to improve the individual's health, the actions including: sending soothing tones to speakers of the earbuds to calm the individual and adjust their heart rate, heart rate variability (“This discloses enables various technologies for audio-visual entrainment with breathing cues for managing heart rate variability”, Abstract) and respiration and sending audio messages to the earbuds that recommend breathing exercises (“visual inspiration and expiration breathing cues to the user through audio tonal changes delivered through the headphones (or speakers) worn by the user”, [0085]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the system of Söhne with the data analysis system configuration of Siever, because there is a need in the heart rate variability detecting field for technology that can teach a user to manage HRV for better life quality (Seiver, [0004]-[0007]).
Regarding Claim 3, modified Söhne discloses the closed loop system of claim 1, wherein the data analysis system creates the baseline autonomic nervous system profile over the time period by plotting one or more types of the identified physiological data against one or more other types of physiological data (See Figs. 15-18; flow state is calculated by plotting heart rate against heart rate variability).
Regarding Claim 8, modified Söhne discloses the closed loop system of claim 1, wherein the data analysis system presents the current physiological state of the individual and the baseline autonomic nervous system profile of the individual to the interface for access by one or more external systems to the closed loop system (“An example of an embodiment for the local or the (cloud) remote user interface will follow. This user interface should be clear, fast and convenient for, for example, the user, coach or doctor”, [0108]; “One aspect of the invention is logging an event in which a subject is having a too low flow or high flow…These events logs eventually can be send real time to the cloud for further services such as alarming, coaching, or big data analysis”, [0113]). Modified Söhne discloses the claimed invention except for expressly disclosing wherein the one or more external systems include social media platforms and gaming system platforms. However, Barnacka teaches wherein the one or more external systems include social media platforms and gaming system platforms (“Each user preferably has the option of sharing data or the results of data analysis using for example social media, social network(s), email, short message services (SMS), blogs, posts, etc.”, [0190]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Söhne such that wherein the one or more external systems include social media platforms and gaming system platforms, as taught by Barnacka, for the advantage of connecting with other users on social media.
Regarding Claim 9, modified Söhne discloses the closed loop system of claim 1, wherein when the data analysis system maps the current identified physiological data against the baseline autonomic nervous system profile (“In FIG. 21 is indicated for an embodiment of this invention the measured and calculated flow (vertical axes; low, mid and high level) values (indicated with 26) over time (horizontal axes). Also the adaptive high threshold (indicated with 24) and low threshold (indicated with 25) are dynamically measured based upon the real time flow value and both are displayed in this figure.”, [0186]), wherein if the current identified physiological data deviates from that of the physiological data in the profile by a threshold amount (S8, Fig. 7“For example for sporting a flow (=HR*HRV/25) higher than approximately 15 seems to be advisable (the exact value could be individual determined or via big data analysis determined) and a value lower than approximately 10 should be avoided. Feedback to the user of flow value warnings related to such thresholds and advices what to do in such case is part of an embodiment of this invention”, [0186]), the data analysis system instructs the individual to perform one or more actions designed to adjust the current physiological state of the individual to be similar to that of the physiological state in the profile (S8, Fig. 7; “Embodiment of the invention is, in case of too low or too high flow value, that the user is advised and stimulated to do some specific exercise change to increase or decrease the flow fast depending on the activity”, [0196]).
Regarding Claim 10, modified Söhne discloses the closed loop system of claim 1, wherein the data analysis system accesses a target physiological state at the interface (“Per activity type or sport type there could be a (number of max flow) scale. This scale is between a number of interval flow max and a number of endurance flow max which is differentiated by the number of flow peaks for a specific sport type, or training level on that scale...Such a max flow interval number per activity type can be made person dependent and/or sport type dependent and could be adaptable depending on the sport level of execution. By preselect a max flow interval number per activity type or user type or challenge level as a initial target for an activity and then based upon this target instruct the user for certain real time flow value target to act upon”, [0219]) that was sent to the interface by an external system of the one or more external systems to the closed loop system (A subject state determining device comprising at least one of a server machine, and cloud machine, such a device being to execute all claimed method steps is disclosed [0052] and Claim 26; therefore, any of these devices could send the target state to any of at least one other of these devices claimed as the data analysis system), and wherein the closed loop system instructs the individual to perform one or more actions designed to adjust the current physiological state of the individual to be that of the target physiological state (“By indicating and instructing the user to increase a real-time flow level to a dynamic maximal flow level (a local maximum)”, [0219]), and wherein the external system is a user device including an app executing on the user device (“[0187] A method that automatically stimulates an adaptable and proactive life style by increasing flow that is secured in a partly decentralized fashion as a standalone decentralized end-user system such as a smart sport watch or app on a smart phone...”, [0187]).
Regarding Claim 11, Söhne discloses the method of operation for a closed loop system ([0001]), the method comprising:
(b) receiving, at an interface (A subject state determining device comprising at least one of a smart watch, smart phone, heart rate information sensor, such a device being to execute all claimed method steps is disclosed [0052] and Claim 26; therefore, the interface could be any one of these elements), biosignals (“For example logged are the HR, HRV, … Current (such as wearable) devices have or could have a lot of sensors on board which can be used to register these events automatically by using these sensors…”, [0122]);
(c) monitoring the received biosignals at the interface over time and identifying physiological data of the individual based upon the received biosignals (“FIG. 20 illustrates a scenario of real time measuring HR and HRV over time”, [0071]);
(d) creating a baseline autonomic nervous system profile of the individual over a time period from the identified physiological data (“The invented (for example flow) state value relation (FIG. 8) can be easily expressed in HR and HRV… for example the flow state could be; “worse”, “better” or “good”…”, [0081]), the baseline autonomic nervous system profile tracking changes to a physiological state of the individual over the time period (See Fig. 21; “In FIG. 21 is indicated for an embodiment of this invention the measured and calculated flow (vertical axes; low, mid and high level) values (indicated with 26) over time (horizontal axes)”, [0186]);
(e) identifying current physiological data of the individual from new biosignals received at the interface over a current time period, and identifying a current physiological state of the individual by mapping the current identified physiological data against the baseline autonomic nervous system profile (See Figs. 17-18; “FIG. 18 illustrates an example of different emotion (for example flow) states in which the user can be in. Illustrated with an oval (18) a set of real time HR values, and real time HRV values are calculated and illustrated in this figure. The emotions can be measured based upon embodiment of this invention in (relative and/or absolute) values of HR, and HRV”, [0128]; the intersection of all flow states can be considered the baseline);
(f) receiving information at the interface including the new biosignals (“Technology for sending heart, heart rate frequency, heart rate variability, flow, state information, heart pulse, pulse time into the cloud are for example client-server network, or peer-to-peer networks, or chain network”, [0187]).
Söhne discloses the claimed invention except for expressly disclosing:
(a) detecting, in ear canals of the individual, biosignals including infrasonic signals from an in-ear biosensor system worn by the individual, the in-ear biosensor system including earbuds;
(b) receiving, at an interface, the biosignals including infrasonic signals from the in-ear biosensor system worn by the individual;
(f) receiving information at the interface including other physiological data wherein the other physiological data is obtained by and sent to the interface from either one or more sensors external to the closed loop system that monitor the individual or from one or more external systems to the closed loop system: and
(g) executing actions based upon the information to improve the individual's health, the actions including: sending soothing tones to speakers of the earbuds to calm the individual and adjust their heart rate, heart rate variability and respiration and sending audio messages to the earbuds that recommend breathing exercises.
However, Barnacka teaches (a) detecting, in ear canals of the individual, biosignals including infrasonic signals (“The acoustic transducers, such as one or an array of microphones, detects sound in the infrasonic and audible frequency ranges, typically from the user's ear canal”, [0043]) from an in-ear biosensor system worn by the individual (“A portable infrasonic body activity monitoring system including a headset and portable device”, Abstract), the in-ear biosensor system including earbuds (“a user 10 wears a head-mounted transducer system 100 in the form of right and left earbuds 102, 103, in the case of the illustrated embodiment. The right and left earbuds 102, 103 mount at the entrance or inside the user's two ear canals”, [0050]);
(b) receiving, at an interface, the biosignals including infrasonic signals from the in-ear biosensor system worn by the individual (“The head-mounted transducer system provides an output data stream of detected acoustic signals and other data generated by the auxiliary sensors to the processing system such as a mobile computing device, such as for example, a smartphone or smartwatch or other carried or wearable mobile computing device and/or server systems connected the transducer system and/or the mobile computing device”, [0007]); and
(f) receiving information (“Referring to FIG. 15 there is illustrated a network 1200 supporting communications to and from biosensor systems 50 for various users”, [0190]) at the interface including other physiological data wherein the other physiological data is obtained by and sent to the interface from either one or more sensors external to the closed loop system that monitor the individual or from one or more external systems to the closed loop system (“Data from these users may be transferred online, e.g. to remote servers, server farms, data centers, computing clouds etc. More complex data analysis may be achieved using online computing resources, i.e. cloud computing and online storage. Each user preferably has the option of sharing data or the results of data analysis using for example social media, social network(s), email, short message services (SMS), blogs, posts, etc.”, [0067]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to add the infrasonic signals and in-ear biosensor of Barnacka to the system of Söhne, because such a system is discreet, accessible, easy to use, and cost-efficient, as taught by Barnacka ([0005]). In addition, infrasonic signals from a user hold information about the physical state of a user (Barnacka, [0018]). Furthermore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Söhne such that the other physiological data is obtained by and sent to the interface from either one or more sensors external to the closed loop system that monitor the individual or from one or more external systems to the closed loop system, as taught by Barnacka, for the advantage of connecting with other users on social media (Barnacka, [0190]).
Siever teaches (g) executing actions based upon the information (“the headphones 30 produce sound in response to light and audio signals, respectively, provided by one or both of the control module 12 and the HRV module 2”, [0045]) to improve the individual's health, the actions including: sending soothing tones to speakers of the earbuds to calm the individual and adjust their heart rate, heart rate variability (“This discloses enables various technologies for audio-visual entrainment with breathing cues for managing heart rate variability”, Abstract) and respiration and sending audio messages to the earbuds that recommend breathing exercises (“visual inspiration and expiration breathing cues to the user through audio tonal changes delivered through the headphones (or speakers) worn by the user”, [0085]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the method of Söhne with the steps of Siever, because there is a need in the heart rate variability detecting field for technology that can teach a user to manage HRV for better life quality (Seiver, [0004]-[0007]).
Regarding Claim 13, modified Söhne discloses the method of claim 11, wherein the creating of (d) comprises creating a baseline autonomic nervous system profile over the time period by plotting one or more types of the identified physiological data against one or more other types of physiological data (See Figs. 15-18; flow state is calculated by plotting heart rate against heart rate variability).
Regarding Claim 18, modified Söhne discloses the method of claim 11, further comprising presenting the current physiological state of the individual and the baseline autonomic nervous system profile of the individual to the interface for access by the one or more external systems to the closed loop system (“One aspect of the invention is logging an event in which a subject is having a too low flow or high flow…These events logs eventually can be send real time to the cloud for further services such as alarming, coaching, or big data analysis”, [0113]). Modified Söhne discloses the claimed invention except for expressly disclosing the one or more external systems including social media platforms and gaming system platforms. However, Barnacka teaches the one or more external systems including social media platforms and gaming system platforms (“Each user preferably has the option of sharing data or the results of data analysis using for example social media, social network(s), email, short message services (SMS), blogs, posts, etc.”, [0190]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Söhne with Barnacka, for the advantage of connecting with other users on social media.
Regarding Claim 19, modified Söhne discloses the method of claim 11, wherein when mapping the current identified physiological data against the baseline autonomic nervous system profile (“In FIG. 21 is indicated for an embodiment of this invention the measured and calculated flow (vertical axes; low, mid and high level) values (indicated with 26) over time (horizontal axes). Also the adaptive high threshold (indicated with 24) and low threshold (indicated with 25) are dynamically measured based upon the real time flow value and both are displayed in this figure.”, [0186]), wherein if the current identified physiological data deviates from that of the physiological data in the profile by a threshold amount (S8, Fig. 7“For example for sporting a flow (=HR*HRV/25) higher than approximately 15 seems to be advisable (the exact value could be individual determined or via big data analysis determined) and a value lower than approximately 10 should be avoided. Feedback to the user of flow value warnings related to such thresholds and advices what to do in such case is part of an embodiment of this invention”, [0186]), the closed loop system then instructing the individual to perform one or more actions designed to adjust the current physiological state of the individual to be similar to that of the physiological state in the profile (S8, Fig. 7; “Embodiment of the invention is, in case of too low or too high flow value, that the user is advised and stimulated to do some specific exercise change to increase or decrease the flow fast depending on the activity.”, [0196]).
Regarding Claim 20, modified Söhne discloses the method of claim 11, further comprising accessing a target physiological state at the interface that was sent to the interface (“Per activity type or sport type there could be a (number of max flow) scale. This scale is between a number of interval flow max and a number of endurance flow max which is differentiated by the number of flow peaks for a specific sport type, or training level on that scale...Such a max flow interval number per activity type can be made person dependent and/or sport type dependent and could be adaptable depending on the sport level of execution. By preselect a max flow interval number per activity type or user type or challenge level as a initial target for an activity and then based upon this target instruct the user for certain real time flow value target to act upon”, [0219]) by an external system of the one or more external systems to the closed loop system (A subject state determining device comprising at least one of a server machine, and cloud machine, such a device being to execute all claimed method steps is disclosed [0052] and Claim 26; therefore, any of these devices could send the target state to any of at least one other of these devices claimed as the data analysis system), and instructing the individual to perform one or more actions designed to adjust the current physiological state of the individual to be that of the target physiological state (“By indicating and instructing the user to increase a real-time flow level to a dynamic maximal flow level (a local maximum)”, [0219]), and wherein the external system is a user device including an app executing on the user device (“[0187] A method that automatically stimulates an adaptable and proactive life style by increasing flow that is secured in a partly decentralized fashion as a standalone decentralized end-user system such as a smart sport watch or app on a smart phone...”, [0187]).
Claims 2 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Söhne in view of Barnacka and Siever, and further in view of Olive et al (US 4733667 A, hereinafter Olive).
Regarding Claim 2, modified Söhne discloses the closed loop system of claim 1, wherein the physiological data includes a heart rate (See Figs. 17-18; the y-axis is heart rate), a heart rate variability (See Figs. 17-18; the x-axis is heart rate variability), a blood pressure measurement (“Another embodiment of this invention is to derive the blood pressure in a real-time easy way”, [0133]), a respiration rate (“This higher frequency of measurement of heart rate variability and so possible flow or state gives additional precision information and therefore so makes precise analyses in real time better (such as states of heart rate, respiratory rate…”, [0215]), and a stroke volume (“Part of the insight of this invention is the understanding that a real time HRV calculation which is an embodiment of this invention is an indirect measurement of real time heart Stroke Volume variation”, [0134]). Modified Söhne discloses the claimed invention except for expressly disclosing wherein the physiological data includes a heart contractility of the individual. However, Olive teaches wherein a heart contractility of the individual is a function of the autonomic nervous system (“The heart's contractility is, in turn, a function of the catecholamine level in the blood and the degree of activation of the sympathetic nervous system, both of which vary with exercise”, 2:15-19). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the system of Söhne by using a heart contractility of the individual as additional physiological data with which to create the baseline autonomic nervous system profile, because heart contractility provides information about the autonomic nervous system, as suggested by Olive.
Regarding Claim 12, modified Söhne discloses the method of claim 11, further comprising the physiological data including a heart rate (See Figs. 17-18; the y-axis is heart rate), a heart rate variability (See Figs. 17-18; the x-axis is heart rate variability), a blood pressure measurement (“Another embodiment of this invention is to derive the blood pressure in a real-time easy way”, [0133]), a respiration rate (“This higher frequency of measurement of heart rate variability and so possible flow or state gives additional precision information and therefore so makes precise analyses in real time better (such as states of heart rate, respiratory rate…”, [0215]), and a stroke volume (“Part of the insight of this invention is the understanding that a real time HRV calculation which is an embodiment of this invention is an indirect measurement of real time heart Stroke Volume variation”, [0134]). Modified Söhne discloses the claimed invention except for expressly disclosing further comprising the physiological data including a heart contractility of the individual. However, Olive teaches wherein a heart contractility of the individual is a function of the autonomic nervous system (“The heart's contractility is, in turn, a function of the catecholamine level in the blood and the degree of activation of the sympathetic nervous system, both of which vary with exercise”, 2:15-19). Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the method of Söhne by using a heart contractility of the individual as additional physiological data with which to create the baseline autonomic nervous system profile, because heart contractility provides information about the autonomic nervous system, as suggested by Olive.
Claims 4-7 and 14-17 are rejected under 35 U.S.C. 103 as being unpatentable over Söhne in view of Barnacka and Siever, and further in view of Faghih et al (US 20220142556 A1, hereinafter Faghih).
Regarding Claim 4, modified Söhne discloses the closed loop system of claim 1, wherein the data analysis system creates the baseline autonomic nervous system profile of the individual over the time period (See Fig. 21; “In FIG. 21 is indicated for an embodiment of this invention the measured and calculated flow (vertical axes; low, mid and high level) values (indicated with 26) over time (horizontal axes)”, [0186]). Modified Söhne discloses the claimed invention except for expressly disclosing wherein the data analysis system creates the baseline autonomic nervous system profile of the individual over the time period by passing the identified physiological data to a machine learning model for training, and wherein the trained machine learning model incorporates the baseline autonomic nervous system profile of the individual. However, Faghih teaches wherein the data analysis system creates the baseline autonomic nervous system profile of the individual over the time period by passing the identified physiological data to a machine learning model for training, and wherein the trained machine learning model incorporates the baseline autonomic nervous system profile of the individual (Step 450, Fig. 4; “Intermittently or periodically during method 400, the estimated state and/or the input data is utilized to re-train the neural network system and determine (if necessary) modified weights ψ and ϕ, as indicated at 450, that are fed back to the neural network system to improve accuracy of the estimated nervous system state output at 440”, [0075]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to add the machine learning model of Faghih into the system of modified Söhne for the advantage of improved accuracy in creating a baseline autonomic nervous system profile and more accuracy in identifying a current physiological state, as suggested by Faghih ([0075]).
Regarding Claim 5, modified Söhne discloses the closed loop system of claim 4, wherein the data analysis system maps the current identified physiological data against the baseline autonomic nervous system profile (See Figs. 15 and 17-18). Modified Söhne discloses the discloses the claimed invention except for expressly disclosing wherein the data analysis system maps the current identified physiological data against the baseline autonomic nervous system profile by passing the current identified physiological data as input to the trained machine learning model, the result of which is the current physiological state of the individual. However, Faghih teaches wherein the data analysis system maps the current identified physiological data against the baseline autonomic nervous system profile by passing the current identified physiological data as input to the trained machine learning model, the result of which is the current physiological state of the individual (Step 430, Fig. 4; “As indicated at 410 and 420 of FIG. 4, the physiological condition data, e.g., skin conductance data or cortisol level data, and the external input(s), respectively, are obtained and are input to the neural network system to perform state estimation, as indicated at 430. The neural network system, based on the state estimation performed, outputs an estimation of the state, as indicated at 440”, [0074]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to add the machine learning model of Faghih into the system of modified Söhne for the advantage of improved accuracy in creating a baseline autonomic nervous system profile and more accuracy in identifying a current physiological state, as suggested by Faghih ([0075]).
Regarding Claim 7, Modified Söhne discloses the closed loop system of claim 1. Modified Söhne discloses the claimed invention except for expressly disclosing wherein the system creates the baseline autonomic nervous system profile of the individual from the identified physiological data and from user provided physiological data received at the interface. However, Faghih teaches wherein the system creates the baseline autonomic nervous system profile of the individual (Step 430, Fig. 4) from the identified physiological data and from user provided physiological data received at the interface (Step 420, Fig. 4; “knowledge of biological rhythms”, Fig. 5A; “With regard to this additional input data, processing device 140 may be configured to receive, for example: demographic information (age, height/weight, sex, ethnicity, etc.), medical history information, historical nervous system state information, user-provided labels (e.g., relating to emotional feeling, energy level, etc.), user-provided indications/symptoms, healthcare professional-provided labels, healthcare professional-provided indications/symptoms, historical and/or contemporaneous physiological condition data (including biological rhythm data, heart rate data, etc.), environmental data (including, for example, GPS location data, motion data, temperature data, and/or time of day data, from which other information such as a relative noise level can be determined), and/or other suitable data”, [0058]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the system of Söhne by adding the user provided physiological data of Faghih, because this user provided physiological data can facilitate estimation of the nervous system state, as taught by Faghih ([0058]).
Regarding Claim 14, modified Söhne discloses the method of claim 11, wherein the creating of (d) comprises creating the baseline autonomic nervous system profile of the individual over the time period (See Fig. 21; “In FIG. 21 is indicated for an embodiment of this invention the measured and calculated flow (vertical axes; low, mid and high level) values (indicated with 26) over time (horizontal axes)”, [0186]). Modified Söhne discloses the claimed invention except for expressly disclosing wherein the creating of (d) comprises creating the baseline autonomic nervous system profile of the individual over the time period by passing the identified physiological data to a machine learning model for training, the trained machine learning model incorporating the baseline autonomic nervous system profile of the individual. However, Faghih teaches wherein the creating of (d) comprises creating the baseline autonomic nervous system profile of the individual over the time period by passing the identified physiological data to a machine learning model for training, the trained machine learning model incorporating the baseline autonomic nervous system profile of the individual (Step 450, Fig. 4; “Intermittently or periodically during method 400, the estimated state and/or the input data is utilized to re-train the neural network system and determine (if necessary) modified weights ψ and ϕ, as indicated at 450, that are fed back to the neural network system to improve accuracy of the estimated nervous system state output at 440”, [0075]).
Regarding Claim 15, modified Söhne discloses the method of claim 14, further comprising the data analysis system mapping the current identified physiological data against the baseline autonomic nervous system profile (See Figs. 15 and 17-18). Modified Söhne discloses the claimed invention except for expressly disclosing the data analysis system mapping the current identified physiological data against the baseline autonomic nervous system profile by passing the current identified physiological data as input to the trained machine learning model, the result of which is the current physiological state of the individual. However, Faghih teaches the data analysis system (Element 540, Fig. 5A) mapping the current identified physiological data against the baseline autonomic nervous system profile by passing the current identified physiological data as input to the trained machine learning model, the result of which is the current physiological state of the individual (Step 430, Fig. 4; “As indicated at 410 and 420 of FIG. 4, the physiological condition data, e.g., skin conductance data or cortisol level data, and the external input(s), respectively, are obtained and are input to the neural network system to perform state estimation, as indicated at 430. The neural network system, based on the state estimation performed, outputs an estimation of the state, as indicated at 440”, [0074]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to add the machine learning model of Faghih into the method of modified Söhne for the advantage of improved accuracy in creating a baseline autonomic nervous system profile and more accuracy in identifying a current physiological state, as suggested by Faghih ([0075]).
Regarding Claim 17, modified Söhne discloses the method of claim 11. Modified Söhne discloses the claimed invention except for expressly disclosing wherein the creating of (d) comprises creating the baseline autonomic nervous system profile of the individual from the identified physiological data and from user provided physiological data received at the interface. However, Faghih teaches wherein the creating of (d) comprises creating the baseline autonomic nervous system profile of the individual (Step 430, Fig. 4) from the identified physiological data and from user provided physiological data received at the interface (Step 420, Fig. 4; “knowledge of biological rhythms”, Fig. 5A; “With regard to this additional input data, processing device 140 may be configured to receive, for example: demographic information (age, height/weight, sex, ethnicity, etc.), medical history information, historical nervous system state information, user-provided labels (e.g., relating to emotional feeling, energy level, etc.), user-provided indications/symptoms, healthcare professional-provided labels, healthcare professional-provided indications/symptoms, historical and/or contemporaneous physiological condition data (including biological rhythm data, heart rate data, etc.), environmental data (including, for example, GPS location data, motion data, temperature data, and/or time of day data, from which other information such as a relative noise level can be determined), and/or other suitable data”, [0058]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the method of Söhne by adding the user provided physiological data of Faghih, because this user provided physiological data can facilitate estimation of the nervous system state, as taught by Faghih ([0058]).
Claims 6 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Söhne in view of Barnacka, and further in view of Kiso et al (US 20130096397 A1, hereinafter Kiso).
Regarding Claim 6. (Currently amended) The closed loop system of claim 1, wherein the system creates the baseline autonomic nervous system profile of the individual from the identified physiological data (See Figs. 15 and 17-18). Modified Söhne discloses the claimed invention except for expressly disclosing wherein the system creates the baseline autonomic nervous system profile of the individual (“The biological data analysis unit may judge, by referring to the sympathetic nervous system, the magnitude and the intensity of "desire", "interest", "excitement", "stress", and the like of the current inner states of the subject. Further, the biological data analysis unit may judge, by referring to the parasympathetic nervous system, the magnitude and the intensity of "feeling of security", "relaxation", "fatigue", and the like”, [0080]) from the other physiological data received at the interface (“The biological data acquisition unit acquires, for the pupil diameter, for example, image data of an eye of the subject via image capturing means. For the temperature near the nostril, for example, a thermography is used to measure and acquire the temperature by specifying a certain area around the nose on the face… those pieces of bio-information may be acquired collectively for both the sympathetic nervous system and the parasympathetic nervous system”, [0077]; the examiner notes the instant written description recites pupil diameter and body temperature as other types of physiological data in [0136]), wherein the other physiological data is detected by and sent from the one or more sensors external to the closed loop system (“…image data of an eye of the subject via image capturing means. For the temperature near the nostril, for example, a thermography is used to measure and acquire the temperature…”, [0077]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the system of Söhne by using other physiological data as additional physiological data with which to create the baseline autonomic nervous system profile, because this other physiological data provides additional information about the autonomic nervous system.
Regarding Claim 16, modified Söhne discloses the method of claim 11, wherein the creating of (d) comprises creating the baseline autonomic nervous system profile of the individual from the identified physiological data (See Figs. 15 and 17-18). Modified Söhne discloses the claimed invention except for expressly disclosing wherein the creating of (d) comprises creating the baseline autonomic nervous system profile of the individual from the other physiological data received at the interface, wherein the other physiological data is detected by and sent from the one or more external sensors external to the closed loop system. However, Kiso teaches wherein the creating of (d) comprises creating the baseline autonomic nervous system profile of the individual (“The biological data analysis unit may judge, by referring to the sympathetic nervous system, the magnitude and the intensity of "desire", "interest", "excitement", "stress", and the like of the current inner states of the subject. Further, the biological data analysis unit may judge, by referring to the parasympathetic nervous system, the magnitude and the intensity of "feeling of security", "relaxation", "fatigue", and the like”, [0080]) from the other physiological data received at the interface (“The biological data acquisition unit acquires, for the pupil diameter, for example, image data of an eye of the subject via image capturing means. For the temperature near the nostril, for example, a thermography is used to measure and acquire the temperature by specifying a certain area around the nose on the face… those pieces of bio-information may be acquired collectively for both the sympathetic nervous system and the parasympathetic nervous system”, [0077]; the examiner notes the instant written description recites pupil diameter and body temperature as other types of physiological data in [0136]), wherein the other physiological data is detected by and sent from the one or more sensors external to the closed loop system (“…image data of an eye of the subject via image capturing means. For the temperature near the nostril, for example, a thermography is used to measure and acquire the temperature…”, [0077]). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the method of Söhne by using other physiological data as additional physiological data with which to create the baseline autonomic nervous system profile, because this other physiological data provides additional information about the autonomic nervous system.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
See Osorio (US 8951192 B2) (Fig. 1, Fig. 6)
See Sherwood et al (US 10770182 B2).
See Honeycutt et al (US 20200338348 A1) ([0004]).
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.
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/JONATHAN E. COOPER/Examiner, Art Unit 3791
/JACQUELINE CHENG/Supervisory Patent Examiner, Art Unit 3791