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 Amendment
The amendment filed on 07/27/2026 has been acknowledged. Claims 1-2, 5-9 remain pending in the application and are under examination.
Response to Arguments
Applicant's arguments filed 07/27/2026 have been fully considered but they are not persuasive or are moot in view of new grounds of rejection (See 35 U.S.C. 103 Rejection below).
Applicant arguments with respect to the U.S.C. 101 rejection have been considered but are not persuasive. Applicant argues that “a human mind cannot collect real-time physiological sensor signals from a subject’s physical body, synthesize dynamic physical intensity metrics alongside continuous spatial sway/gait balance metrics, and execute temporal-spatial algorithmic state-space transformations”.
Examiner respectfully disagrees. It is noted that the features upon which applicant relies (i.e., real-time physiological sensor signals and synthesize dynamic physical intensity metrics alongside continuous spatial sway/gait balance metrics) are not recited in the rejected claim 1. Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). Claim 1 requires receiving one or more physical intensity measures and one or more stability measures from the subject to produce a subject data set and applying a computational model of temporal and spatial data to the data set to identify a match between the data set and the model to detect a neurological and/or physical condition. These steps could be accomplished by a human mind; for example, a clinician examining a patient and assessing their physical intensity measures and stability measures against a correlation of temporal and spatial information for diagnosis.
Applicant argues that the claims integrate the concept into a practical application as “it directly improves medical diagnostic systems by dynamically transforming combined physical intensity signals and spatial stability metrics into an objective, real-time detection of neurological/physical conditions” branching away from traditional diagnostic evaluations by providing “a concrete technological solution to an established technical problem in medical biometrics”. Applicant argues that claims recite significantly more and that “combining physical intensity monitoring with spatial kinetic stability metrics into a unified temporal-spatial state-space dynamic model was not routine or conventional in the art”.
Examiner respectfully disagrees. As discussed above, the features upon which applicant relies (i.e., real-time physiological sensor signals and synthesize dynamic physical intensity metrics alongside continuous spatial sway/gait balance metrics) are not recited in the rejected claim 1. Claimed additional elements may be used to demonstrate that a claim is directed to patent-eligible subject matter by integrating the judicial exception into a practical application, however applying an abstract idea with a computer or generally linking the use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a practical application (MPEP 2106.04(d) I). Additionally, there is nothing in the claims which show how detecting the neurological and/or physical condition in the subject integrates the judicial exception into a practical application or provides a particular prophylaxis. Further, the limitations directed to "the computer" amount to nothing more than mere instructions to apply the abstract idea using a generic computer (MPEP 2106.05(f), Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983). Regarding dependent claims 2, 5-9, Examiner asserts that these claims further limit the abstract idea of claim 1. In re claim 6, the sensor amounts to pre-solution data gathering. In re claim 7, the wearable device is another generic computer device. In re claim 8, the steps occur “substantially” in real time, which does not serve to integrate the abstract idea into a practical application, see above arguments, In re claim 1. In re claim 9, one or more elements of Floquet theory serves to further limit the computation model, which does not serve to integrate the abstract idea into a practical application.
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 1-2, 5-9 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1-2, 5-9 do not include additional elements that integrate the exception into a practical application of the exception or that are sufficient to amount to significantly more than the judicial exception for the reasons provided below which are in line with the 2014 Interim Guidance on Patent Subject Matter Eligibility (Federal Register, Vol. 79, No. 241, p. 74618, December 16, 2014), the July 2015 Update on Subject Matter Eligibility (Federal Register, Vol. 80, No. 146, p. 45429, July 30, 2015), the May 2016 Subject Matter Eligibility Update (Federal Register, Vol. 81, No. 88, p. 27381, May 6, 2016), and the 2019 Revised Patent Subject Matter Eligibility Guidance (Federal Register, Vol. 84, No. 4, p. 50, January 7, 2019).
Step 1: Claim 1 is drawn to a method.
Step 2A – Prong 1:
Claim 1 is drawn to an abstract idea, that under its broadest reasonable interpretation, covers a mental process but for the recitation of generic computer components to collecting and processing data. In particular, claim 1 recites the following limitations:
a method of detecting a neurological and/or physical condition in a subject using a computer, the method comprising:
receiving, by the computer, one or more physical intensity measures and one or more stability measures (optional) from the subject to produce a subject data set; and,
applying, by the computer, a computational model of temporal and spatial indicative of the neurological and/or physical condition to the subject data set to identify a substantial match between at least a subset of the subject data set and the computational model of temporal and spatial data, thereby detecting the neurological and/or physical condition in the subject using the computer.
These limitations of claim 1 are drawn to an abstract idea because they are processes that, under their broadest reasonable interpretation, are steps merely comprised of mental processes.
Step 2A – Prong Two:
Claim 1 recites the following emphasized (indicated in bold) additional elements that are beyond the judicial exception:
a method of detecting a neurological and/or physical condition in a subject using a computer, the method comprising:
receiving, by the computer, one or more physical intensity measures and one or more stability measures (optional) from the subject to produce a subject data set; and,
applying, by the computer, a computational model of temporal and spatial indicative of the neurological and/or physical condition to the subject data set to identify a substantial match between at least a subset of the subject data set and the computational model of temporal and spatial data, thereby detecting the neurological and/or physical condition in the subject using the computer.
The additional elements do not integrate the exception into a practical application of the exception because the elements are directed to insignificant extra-solution activity. The computer system is a computer that carries out abstract steps described in claim 1 (see 2106.05(g) and 2106.05(f)). Accordingly, each of the additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limitations on practicing the abstract idea. Further, the judicial exception does not integrate the claim as a whole into a practical application because the claimed invention does not improve another technology or technical field. The alleged improvement made by the claimed invention as argued by the application above sets forth the improvement in a conclusory manner and the claim does not include the components or steps of the invention that the improvement described.
Step 2B:
Claim 1 does not recite additional elements that amount to significantly more than the judicial exception itself. Under 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B to determine if it is more than what is well understood, routine, conventional activity. The computer system is a computer that carries out abstract steps described in claim 1. All uses of the recited abstract idea require the pre-solution data gathering.
Claims 2 and 5-9 recite the same abstract idea as their respective parent claims. Furthermore, these claims only contain recitations that further limit the abstract idea.
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.
Claims 1-2 and 5-7 are rejected under 35 U.S.C. 103 as being unpatentable by McEwen (US 20210113140) in view of [Nagale (US 20180153477) and/or Piazza (US 20200108291)].
In re claim 1, McEwen discloses method of detecting a neurological and/or physical condition in a subject using a computer (Fig. 3: 300; abstract), the method comprising:
receiving, by the computer, one or more physical intensity measures (310; [0036-0037]: heart rate variability is a physical intensity measure) and/or one or more stability measures from the subject to produce a subject data set (312; [0038]); and,
applying, by the computer (Fig. 1: 108), a computational model of temporal and spatial data (210 and 314; [0039]: “HRV algorithm”; [0043-0044]: an algorithm developed with data tracking the physical activity of the subject over time is a computational model of temporal and spatial data) indicative of the neurological and/or physical condition to the subject data set to identify a substantial match between at least a subset of the subject data set and the computational model of temporal and spatial data, thereby detecting the neurological and/or physical condition in the subject using the computer (302; [0040-0043]).
McEwen lacks:
receiving, by the computer, one or more physical intensity measures and one or more stability measures from the subject to produce a subject data set.
Nagale discloses a method for detecting a brain injury (stroke), analogous in nature to the brain injury (concussion) in McEwen, in a patient (abstract) with a computer [0047] that, like the system of McEwen, discloses utilizing a physiological signal (i.e. physical intensity measure) such as heart rate variability [0011, 0052] to determining risk of the neurological and/or physical condition [0007]. In addition, Nagale discloses a functional signal (i.e. stability measure) wherein the functional signal can include gait, posture, or physical activity intensity or duration, grip strength signal, a locomotion pattern, a sleep or awakening state detector, or a balance indicator [0026, 0052, 0080] to produce data (i.e. spatial data as the gait is indicative of spatial movement of the subject) that is analyzed to detect stroke [0048, 0054, 0072].
Piazza discloses the consideration of both heart rate and stability in a concussion assessment ([0038]: item xiii).
It would have been obvious before the effective filing date of the claimed invention to one of ordinary skill in the art to modify McEwen by providing wherein the computer receives one or more functional signals (i.e. stability measures) from the subject to produce a subject data set as taught by Nagale and/or Piazza because symptomatic changes in stability such as in gait, can occur with a neurological and/or physical condition, such as a brain injury like stroke or concussion, and can be used to confirm brain injury detection based on a physical intensity measure such as heart rate variability (Nagale: [0059]) and it is known to consider both heart rate and stability in a concussion assessment (Piazza). This combination would yield a method of detecting a neurological and/or physical condition in a subject using a computer, the method comprising: receiving, by the computer, one or more physical intensity measures and/or one or more stability measures from the subject to produce a subject data set; and, applying, by the computer, a computational model of temporal and spatial data indicative of the neurological and/or physical condition to the subject data set to identify a substantial match between at least a subset of the subject data set and the computational model of temporal and spatial data, thereby detecting the neurological and/or physical condition in the subject using the computer.
In re claim 2, McEwen discloses wherein the physical intensity measures comprise a heart rate intensity measure (optional), a heart rate variability measure (310, [0016]), a heart rate interval measure (optional), cardiac stability index (CSI) (optional), and/or an electrocardiogram (ECG) measure (optional).
In re claim 5, McEwen discloses wherein the neurological and/or physical condition comprises a concussion [0016], mental fatigue, physical fatigue, bodily injury, traumatic brain injury, and/or frailty.
In re claim 6, McEwen discloses receiving the physical intensity measures and/or the stability measures from at least one sensor (Fig. 1: 102; [0026-0027]: “The HRV monitor 102 can include an electrocardiogram (ECG) or use photoplethysmography (PPG) technology”) within communication of at least one target location of the subject ([0027]: “The HRV monitor 102 can be worn on the wrist, chest, arm, finger, feet or ear”).
In re claim 7, McEwen discloses wherein a wearable device worn by the subject comprises the at least one sensor ([0027, 0029]: “The individual engages in all the physical activities they normally would and wears the HRV monitor 102 during these activities”).
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over McEwen (US 20210113140) in view of [Nagale (US 20180153477) and/or Piazza (US 20200108291)] in further view of Herman (US 20160051179).
In re claim 8, the proposed combination does not yield:
wherein the receiving and applying steps are performed in substantially real-time.
Herman discloses a method for detecting a brain injury, for example a concussion (i.e. a neurological and/or physiological condition) that, like the method disclosed by McEwen, monitors heart rate variability [0013]. In addition, Herman discloses wherein the reception of data, application of algorithm (i.e. model), and assessment are performed in real-time [0012, 0028].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify the method disclosed by the proposed combination to provide wherein the receiving and applying steps of the method are performed in real time as taught by Herman because this would allow for accurate detection of neurological and/physical conditions, like concussions, sooner in the case of patients who could be masking their symptoms or deceiving other concussion assessments (Herman: [0005]).
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over McEwen (US 20110152727) in view of [Nagale (US 20180153477) and/or Piazza (US 20200108291)] in further view of Coleman Boone (US 20120119904) in further view of Ten Kate (US 20120119904).
In re claim 9, the proposed system lacks:
using one or more elements of Floquet theory to generate the computational model of temporal and spatial data indicative of the neurological and/or physical condition.
Coleman Boone (US 20120119904) discloses a method for assessing the risk of a patient to fall (abstract) that, like the method disclosed by McEwen, monitors a subject with sensors [0007] for a computational model of temporal and spatial indicative of falling (i.e. physical condition) to stability data [0007, 0055] to identify a substantial match between at least a subset of the subject data set and the computational model of temporal and spatial data [0079]. In addition, Coleman Boone discloses using Floquet numbers in a statistical analysis tool (i.e. using one or more elements of Floquet theory) which uses a non-linear dynamical approach to examine dynamic stability during gait [0092].
In addition, Ten Kate discloses a method for assessing the risk of a patient falling [0015] that, like the method disclosed by McEwen, monitors a subject with sensors [0015] for a computational model of temporal and spatial indicative of falling (i.e. physical condition) to date [0041, 0055]. Additionally, Ten Kate discloses Floquet Multipliers (i.e. one or more elements of Floquet theory) being a useful metric to determine stability of a subject’s walking and gait [0042, 0064] because walking exhibit non-linear characteristics [0062] and Floquet multipliers can be used as in non-linear time series analysis of human walking [0042].
It would have been obvious to one of ordinary skill in the art before the effective filing date to modify the method disclosed by the proposed combination to provide using one or more elements of Floquet theory to generate the computational model of temporal and spatial data indicative of the neurological and/or physical condition as taught by Coleman Boone. One would have been motivated to make this modification because walking and gait exhibit non-linear characteristics as evidenced by Ten Kate [0042, 0062], making elements of Floquet theory ideal for modeling walking and gait. Such a combination would yield “using one or more elements of Floquet theory to generate the computational model of temporal and spatial data indicative of the neurological and/or physical condition”.
Conclusion
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.
The following prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Palmer (US 20210338173) discloses a method for predicting heat stroke with a worn sensor that uses accelerometry based functionality to provide a gait-based heat stroke score which also uses a heart rate sensor to detect heart rate to estimate temperature to predict risk of heat stroke.
Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HALLE M WELCH whose telephone number is (571)272-0168. The examiner can normally be reached Mon-Fri, 8:30 am to 5:00 pm..
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, David E Hamaoui can be reached at (571) 270-5625. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/HALLE MARGARET WELCH/Examiner, Art Unit 3796
/DAVID HAMAOUI/SPE, Art Unit 3796
