DETAILED ACTION
Response to Amendment
This Office Action is responsive to the Amendment filed 15 December 2025. Claims 1-4, 8-19, 31 are now pending. The Examiner acknowledges the amendments to claims 1, 2, 3, 14, 19.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Objections
Claims 1, 2, 3, 8, 14, 19 are objected to because of the following informalities:
-Claim 1 recites “mood threshold predetermined” in line 11. Examiner recommends amending to –predetermined mood threshold—
-Claim 2 recites “when determines” in line 2. Examiner recommends amending to –when determining—
-Claim 3 recites “the physchologicalpsychiatirc” in line 1. Examiner recommends amending to –psychiatric—
-Claim 3 recites “or
schizophrenia.” Examiner recommends removing additional spacing between or and schizophrenia.
-Claim 8 recites “The system of claim 6” in line 1. Examiner recommends amending to –The system of claim 1—due to the fact that claim 6 was cancelled.
-Claim 14 recites “patient responsesinformation” in line 2. Examiner recommends amending to –patient responses—
-Claim 19 recites “mood threshold predetermined” in lines 8-9. Examiner recommends amending to –predetermined mood threshold—
Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
- Claim 1 recites “a device” which is a generic placeholder. There is no sufficient
structure for this limitation provided in the claims. The function of this limitation is
to obtain one or more data features from the patient. According to the specification the device includes a computer, a laptop, a tablet computer, a mobile phone, a smartwatch, a ring or an implantable or partially-implanted device such as an implant [0035] and equivalents thereof.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 2, 14 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.
-Claim 2 recites “the mood plot does not meet the predetermined mood threshold for the patient.” It is unclear what aspect of the mood plot is being referred to in this recitation. As previous recited in claim 1, the mood plot encompasses a plurality of mood reports which would insinuate that the mood plot encompasses multiple data values. Further clarification should be provided to identify which aspect of the mood plot is compared to the predetermined mood threshold in order to determine whether the mood plot “does not meet the predetermined mood threshold.”
-Claim 2 recites “wherein relapse is predicted if” in line 1. It is unclear from this recitation and the claims dependency on Claim 1, whether relapse prediction is actually required as a limitation for the system. Claim 1, line 10 recites “predict relapse…” as a limitation required by the machine learning algorithm and system for predicting relapse. Examiner recommends rewording or providing further clarification as to whether the limitation is or is not required.
-Claim 14 recites “wherein the one or more data features comprises information estimated from a clinician administered inventory” in lines 1-2. It is unclear from this recitation what the limitation is referring to in terms of estimates from an inventory. The one or more data features recited are obtained via a device as mentioned in claim 1. Further clarification should be provided to identify how this data, collected from a device, also pertains to inventory-based information.
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, 3, 4, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 31 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) a system and method for a mental process of predicting relapse of a neurological or a psychiatric disorder of a patient, which can be considered as a mental process and/or implemented with pen/paper. The steps of “inputting data features,” “generate(ing) a mood report and a mood plot,” “add(ing) the mood report to a plot,” “predict(ing) relapse of the neurological or the psychiatric disorder in the patient,” and “transmit(ting) a flag” could be interpreted as a provider receiving any data set on a piece of paper, compiling the data, and reviewing this data set for indicators of relapse.
The “predicting relapse” steps (claim 1, lines 10-11 and claim 19, lines 11-12) could be performed mentally or on a piece of paper. The “determining that the mood plot does not meet the predetermined threshold,” (claim 2, lines 2-3) “transmitting a flag” (claim 1, line 15) and “recommending a treatment schedule” (claim 18, line 2) are also steps that could be performed mentally or on a piece of paper as is normally accomplished when a provider reviews a data set to recommend intervention to a patient.
This judicial exception is not integrated into a practical application because the claims, as written can be performed in a provider’s mind, or implemented with pen/paper and further do not positively recite any application of these steps in claims 1, 2, 3, 4, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 31. While claim 1 recites the additional elements of a data module, one or more processors, a machine learning algorithm, these additional elements are not sufficient to amount to significantly more than the judicial exception because the mental steps of “analyze,” “generate,” are merely being implemented on generic computer elements and thus do not add a meaningful limitation to the abstract idea since they simply amount to implementing the abstract idea on a generic computer and treatment component which is essentially a data collection and analysis tool. Claim 15 does recite the additional element of a “device” encompassing a computer, laptop, table, mobile, smart-watch or ring and claim 16 does refer to the system of claim 1 further “comprising a treatment device” however such devices for collecting data and providing treatment are well-understood and conventional in the art as suggested by (U.S. 20160339239).
And while claim 19 also appears to recite the step of “delivering neurostimulation therapy,” these therapeutic steps are not positively recited and lack any further specification of the “use” and amount to no more than merely adding a generic step of “delivering” treatment (or the equivalent thereof) with respect to the mood reports and generated data.
And with respect to the recitation of “the machine learning algorithm” and “applying a machine learning algorithm” this likewise amounts to an added generic step of “apply it” (or equivalent thereof) by simply reciting using a machine learning model to analyze, generate and process received data, which could be implemented using a generic computer application “a machine learning model” lacking any further specification. However, such a machine learning model for data processing and generation is well-understood and conventional in the art as suggested by (U.S. 20210361948).
Dependent claims 2-18 and 31-34 merely further limit generic steps, which can also be performed mentally “determining that the mood plot does not meet the predetermined threshold,” and “recommending a treatment schedule,” which is addressed above.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 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.
Claim(s) 1, 3, 11 and 14-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Javitt (U.S. 11311193) in view of Lazarus (U.S. 11116564).
Regarding Claim 1, Javitt teaches a system for predicting relapse of a neurological or a psychiatric disorder of a patient [Col 6, lines 47-51] comprising: a device configured to obtain one or more data features from the patient [Figure 11, element 1105] and, [Col 34, lines 9-11], wherein the one or more data features include mood data [Col 13, lines 47-52; “The number of treatments needed per subject at the end of each treatment course was recorded, and the number of remissions defined by a HDRS-17 score of <8 and HDRS item 1 ( e.g., depressed mood) score=0 after last session of ECT and at month 6 after completion of ECT treatments was utilized.”], and a data module [Figure 12, element 1205], the data module comprising one or more processors configured to run a machine learning algorithm [Col 34, lines 41-46] wherein the machine learning algorithm is configured to: generate a mood report based on the one or more data features [Col 9-10, lines 64-1]; add the mood report to a mood plot comprising a time-series of mood reports [Figures 5A-5D, Col 23, lines 33-52]; predict relapse of the neurological or the psychiatric disorder in the patient based on the mood plot [Col 34, lines 2-4] and a mood threshold predetermined for the patient [Col 21, lines 65-67] based on a plurality of mood reports generated from data features obtained from the patient over a plurality of neurostimulation treatment sessions [Figures 5A-5D, Col 23, lines 33-52]; and transmit a flag indicating the predicted relapse [Col 7, lines 3-9].
Javitt is silent on the mood data comprising a patient self-report of daily mood using a visual analog scale. Lazarus teaches the mood data comprising a patient self-report of daily mood using a visual analog scale [Col 21, lines 45-46 and 55-56]—references to daily activities and a visual analog scale (VAS) screening tool.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to mood data collected using self reporting and visual analog scales as taught by Lazarus to predict relapse conditions as suggested by Javitt as Javitt discusses using depressed mood scoring after treatment to indicate responsiveness and success [Col 13, lines 46-52] with Lazarus because Lazarus teaches using multiple screening instruments to look at multiple risk factors in assessment processes [Col 21, lines 56-59].
Regarding Claim 3, Javitt further teaches wherein the psychologicalpsychiatric disorder is depression, treatment-resistant depression, anxiety, post-traumatic stress disorder (PTSD), obsessive-compulsive disorder (OCD), a substance use disorder, bipolar disorder, or schizophrenia [Col 3, lines 61-67]—reference to the psychiatric disorder can be (i) depression, (ii) Autism, (iii) suicidality, (iv) obsessive compulsive disorder, or (v) hallucinations.
Regarding Claim 11, Javitt further teaches wherein the one or more data features comprises information related to heart rate, heart rate variability, electroencephalography, electrogastrography, electrogastroenterography, galvanic skin response, sleep, sweat chloride, neuroimaging, patient demographics, outcome data from an acute treatment, outcome data from a prior maintenance treatment, or a combination thereof [Col 9, lines 54-60]—reference to ECT and TMS outcomes that can drive an exemplary machine learning engine. In this interpretation, the limitation outcome data from a prior maintenance treatment is taught.
Regarding Claim 14, Javitt further teaches wherein the one or more data features comprises patient responsesinformation estimated from a clinician administered inventory [Col 34, lines 13-15; “At procedure 1115, a database having information related to a plurality of disorders and associated brain parcels can be accessed.”] and [Col 21, lines 45-46 and 55-56]—reference to patient self-reporting, interpreted to be patient responses, on the plurality of disorders.
Regarding Claim 15, Javitt further teaches wherein the device comprises a computer, a laptop, a tablet computer, a mobile phone, a smart-watch, or a ring [Fig. 12, element 1210] and [Claim 1, Col 38, lines 56-60]—reference to a computer.
Regarding Claim 16, Javitt further teaches comprising a treatment device [Abstract; “and determining the position or the characteristic of the target(s) for the TMS treatment of the patient(s) based on the imaging information.”]
Regarding Claim 17, Javitt further teaches wherein the treatment device comprises a transcranial magnetic stimulation coil [Col 3, lines 51-53; “A placement a TMS coil on the portion(s) of the head of the patient(s) can be determined based on the position or the characteristic of the target(s).”]
Regarding Claim 18, Javitt further teaches wherein the machine learning algorithm is further configured to recommend a treatment schedule to minimize relapse of the neurological or the psychiatric disorder [Col 6, lines 47-51; “In addition, the exemplary system, method and computer-accessible medium can be utilized to monitor the treatment efficacy ( e.g., determine how many treatments need to be given) and/or predict a potential relapse in patients who have previously responded to ECT.”]
Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Javitt (U.S. 11311193) in view of Lazarus (U.S. 11116564) and in further view of McNair (U.S. 11069446).
Regarding Claim 2, Javitt and Lazarus are silent on wherein relapse is predicted if the machine learning algorithm is further configured to predict relapse when determining that the mood plot does not meet the predetermined mood threshold for the patient.
McNair teaches wherein relapse is predicted if the machine learning algorithm determines that the mood plot does not meet the predetermined mood threshold for the patient [Col 20, lines 12-16; “comparing the predicted likelihood of relapse with a threshold; and responsive to the predicted likelihood of relapse exceeding the predetermined threshold, automatically modifying a care plan for the individual subject.”] In this embodiment, the mood plot is considered to be formed of the data input into the treatment / relapse logging system [Fig. 1A, element 160].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the machine learning algorithm to compare mood plot data as taught by McNair to predict relapse as suggested by Javitt and Lazarus as Javitt discusses the use of a Hamilton depression rating scale (HDRS) that is monitored and recorded throughout the course of treatment [Col 13, lines 34-40] and Lazarus which discusses the use of therapeutically effective renal neuromodulation to reduce risk of recurrence of anxiety-related disorders [Col 2, lines 60-64] with McNair because McNair teaches the use of information collected via the system which can include depression index information and presented in relation to time series to produce a result [Col 2, lines 35-57].
Claim(s) 4, 8, 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Javitt (U.S. 11311193) in view of Lazarus (U.S. 11116564).
Regarding Claim 4, Javitt is silent on wherein the neurological disorder is Parkinson's disease, essential tremor, stroke, epilepsy, traumatic brain injury, migraine headache, cluster headache, or chronic pain. Lazarus teaches wherein the neurological disorder is Parkinson's disease, essential tremor, stroke, epilepsy, traumatic brain injury, migraine headache, cluster headache, or chronic pain. [Col 6, lines 11-19]—reference to Parkinson’s disease.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the system to treat specific neurological disorders as taught by Lazarus to provide treatment/neuromodulation in response to these disorders as suggested by Javitt as Javitt discusses the use of the system and database containing information related to a plurality of disorders and associated spatially defined brain regions [Col 3-4, lines 67-2] with Lazarus because Lazarus teaches the use of this treatment for improving and reducing the risk of developing an anxiety disorder [Abstract].
Regarding Claim 8, Javitt is silent on wherein the mood data comprises psychometric data. Lazarus teaches wherein the mood data comprises psychometric data [Col 21, lines 56-59]—reference to anxiety disorder status.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate psychometric data as taught by Lazarus to provide treatment/neuromodulation in response to these disorders as suggested by Javitt as Javitt discusses the use of a rating scale to assess and score depression which would be considered a mental measurement [Col 13, lines 35-40] with Lazarus because Lazarus teaches this use of self-reporting tools that screen and monitor disorder progression by means of scoring depression symptoms which fall under the categorization of mental measurements and psychometric data [Col 35, lines 58-63].
Regarding Claim 9, Javitt is silent on wherein the psychometric data comprises information relating to mind wandering, anxiety, processing speed, task switching ability, attention, loneliness, or a combination thereof. Lazarus teaches wherein the psychometric data comprises information relating to mind wandering, anxiety, processing speed, task switching ability, attention, loneliness, or a combination thereof [Col 22, lines 6-8]—reference to cerebral activities encompassing reasoning, memory, attention, and language), emotional/social functioning and [Col 22, lines 16-23]—reference to anxiety disorders. In the described interpretation, the combination of limitations of anxiety, memory and attention are taught.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the specified groupings of psychometric data as taught by Lazarus to provide treatment/neuromodulation in response to these disorders as suggested by Javitt as Javitt discusses the use of a rating scale to assess and score depression which would be considered a mental measurement [Col 13, lines 35-40] with Lazarus because Lazarus teaches this use of self-reporting tools that screen and monitor disorder progression by means of scoring depression symptoms which fall under the categorization of mental measurements and psychometric data [Col 35, lines 58-63].
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Javitt (U.S. 11311193) in view of Lazarus (U.S. 11116564) and in further view of Poltorak (U.S. 20200368491).
Regarding Claim 10, Javitt and Lazarus are silent on wherein the one or more data features comprises information relating to motor activity. Poltorak teaches wherein the one or more data features comprises information relating to motor activity [0336]—references to motor response and motor activity.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include motor activity data as taught by Poltorak to predict relapse as suggested by Javitt and Lazarus as Javitt discusses directing TMS treatments towards the motor cortex which motor threshold consideration [Col 9, lines 17-20] and Lazarus which discusses the relationship of the sensorimotor cortex with regulation in anxiety [Col 9, lines 18-23] with Poltorak because Poltorak teaches modifying brainwave patterns of a subject with simultaneous monitoring of motor patterns [0407].
Claim(s) 12, 13, is/are rejected under 35 U.S.C. 103 as being unpatentable over Javitt (U.S. 11311193) in view of Lazarus (U.S. 11116564) and in further view of Howard (U.S. 20190381314).
Regarding Claim 12, Javitt and Lazarus are silent on wherein the information related to sleep comprises a total duration of sleep, a sleep onset time, a sleep offset time, a sleep cycle duration, a number of sleep cycles per night, sleep movements, sleep vocalizations, or a combination thereof. Howard teaches wherein the information related to sleep comprises a total duration of sleep, a sleep onset time, a sleep offset time, a sleep cycle duration, a number of sleep cycles per night, sleep movements, sleep vocalizations, or a combination thereof [0160]—reference to the use of sleep data. In this interpretation, the limitation of sleep duration is taught.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use sleep data as taught by Howard to predict relapse as suggested by Javitt and Lazarus, as Javitt discusses the use of resting-state imaging pre/post treatment in combination with screening assessments [Col 16, lines 53-57] and Lazarus which discusses the correlation of sleep and anxiety disorders [Col 18, lines 54-67] with Howard because Howard teaches the reasoning for including sleep data within the screening and visual analog-based questionnaires [0185].
Regarding Claim 13, Javitt and Lazarus are silent on wherein the one or more data features comprises body temperature, a mean body temperature within a given period of time, a fluctuation in body temperature, or a combination thereof. Howard teaches wherein the one or more data features comprises body temperature, a mean body temperature within a given period of time, a fluctuation in body temperature, or a combination thereof [0012]—reference to body temperature sensors, in this interpretation, the limitation of body temperature is taught.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use body temperature data as taught by Howard to predict relapse as suggested by Javitt and Lazarus as Javitt discusses considering the physical side effects of ECT treatment which include many physiological problems including cardiac issues [Col 2, lines 3-7] and Lazarus which discusses using sensory feedback such as impedance and temperature to detect instability and alert the operator [Col 48, lines 4-6] with Howard because Howard teaches use of these sensors to monitor for cardiac side effects of treatment [0160].
Claim(s) 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Javitt (U.S. 11311193) in view of Lazarus (U.S. 11116564) and in further view of Williams (U.S. 20190216342).
Regarding Claim 19, Javitt teaches a method for predicting relapse of a neurological or a psychiatric disorder of a patient [Col 6, lines 47-51] comprising: inputting one or more data features from the patient into a predictive model for the neurological or the psychiatric disorder; [Col 28, lines 41-44; “ROI is for these analyses were defined using the multi-modal parcellation of human cortex. Areas within the left DMN (e.g., s32) and left DLPFC (46) were selected following results on predictive models of ECT response.”]—where region of interest (ROI) is interpreted to be the inputted data features, wherein the one or more data features include mood data [Col 13, lines 47-52; “The number of treatments needed per subject at the end of each treatment course was recorded, and the number of remissions defined by a HDRS-17 score of <8 and HDRS item 1 ( e.g., depressed mood) score=0 after last session of ECT and at month 6 after completion of ECT treatments was utilized.”], applying a machine learning algorithm to the one or more data features to generate a mood report and a mood plot [Col 9, lines 57-60] and [Col 9-10, lines 64-1] and [Col 13, lines 47-52],
wherein the mood plot has a mood threshold predetermined for the patient based on a plurality of mood reports taken over a plurality of neurostimulation treatment sessions; [Figures 5A-5D, Col 23, lines 33-52] predicting relapse of the neurological or the psychiatric disorder in the patient based on the mood plot [Col 34, lines 2-4].
Javitt is silent on the mood data comprising a patient self-report of daily mood using a visual analog scale. Lazarus teaches the mood data comprising a patient self-report of daily mood using a visual analog scale [Col 21, lines 45-46 and 55-56]—references to daily activities and a visual analog scale (VAS) screening tool;
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to mood data collected using self reporting and visual analog scales as taught by Lazarus to predict relapse conditions as suggested by Javitt as Javitt discusses using depressed mood scoring after treatment to indicate responsiveness and success [Col 13, lines 46-52] with Lazarus because Lazarus teaches using multiple screening instruments to look at multiple risk factors in assessment processes [Col 21, lines 56-59].
Javitt and Lazarus are silent on delivering neurostimulation therapy when relapse is predicted. Williams teaches delivering neurostimulation therapy when relapse is predicted [Abstract; “providing an indicator…and treating the patient using a transcranial stimulation device”]
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply treatment after relapse is predicted as taught by Howard to develop the number of treatment sessions as suggested by Javitt and Lazarus as Javitt discusses needing multiple repeat sessions over the course of treatment to prevent relapse [Col 12, lines 6-8] and Lazarus which discusses the recurring and ongoing nature of anxiety disorders [Col 4, lines 38-42] with Williams because Williams teaches a system capable of predicting and providing treatment for a neurological condition [0015].
Claim(s) 31 is/are rejected under 35 U.S.C. 103 as being unpatentable over Javitt (U.S. 11311193) in view of Lazarus (U.S. 11116564) and in further view of Williams (U.S. 20190216342) and in even further view of Howard (U.S. 20190381314).
Regarding Claim 31, Javitt, Lazarus and Williams are silent on wherein the one or more data features comprises body temperature, a mean body temperature within a given period of time, a fluctuation in body temperature, or a combination thereof.
Howard teaches wherein the one or more data features comprises body temperature, a mean body temperature within a given period of time, a fluctuation in body temperature, or a combination thereof [0012]. In this interpretation, the limitation of body temperature is taught.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use body temperature data as taught by Howard to predict relapse as suggested by Javitt, Lazarus and Williams, as Javitt discusses considering the physical side effects of ECT treatment which include many physiological problems including cardiac issues [Col 2, lines 3-7] and Lazarus which discusses the thermal effects of neuromodulation [Col 40, lines 47-53] and Williams which discloses using heart rate variability measurements to predict relapse [0015] with Howard because Howard teaches use of these sensors to monitor for cardiac side effects of treatment [0160].
Response to Arguments
Applicant's arguments filed 12 December 2025 with respect to the specification, drawing objections have been fully considered and are persuasive in light of the amendments.
Applicant's arguments filed 12 December 2025 with respect to the claim objections have been fully considered and are persuasive however, new objections are presented for claims 1, 2, 3, 8, 14, 19.
Applicant's arguments filed 12 December 2025 with respect to 35 U.S.C. 112(b)
rejections have been fully considered and are persuasive however, new rejections are
presented in light of the amendments for claims 1, 2, 3, 4, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 31.
Applicant’s arguments filed 12 December 2025 with respect to the rejection of
claims 1 and 19 under 35 U.S.C.101 have been fully considered but they are not persuasive. While the claim limitations remove some of the previously recited steps of analyzing data features and generating mood plots, the amendments and claim language still include mental process language and additional elements that do not amount to more than the judicial exception, are implemented on generic computing components and thus do not add a meaningful limitation to the abstract idea. Claim 19 was amended to add the recitation “delivering neurostimulation therapy when relapse is predicted” however, this limitation is not positively recited. While the applicant’s arguments present a valid discussion explaining that early detection based on readily accessible information comprises additional integrations into practical considerations, the rejection is maintained due to the explanation presented above.
Applicant’s arguments filed 12 December 2025 with respect to the rejection of
claims 1, 3, 11, 14-19 and 34 under 35 U.S.C.102(a)(2) have been fully considered and are persuasive, however, new rejections are presented above in light of the amendments. In regards to claim 1, the applicant presents an argument in regards to Javitt failing to teach or suggest the limitation requiring mood data and the use of visual analog scales to record this data. The examiner has presented new grounds of rejection for claim 1 under 35 U.S.C. 103 in light of the amendments. Applicant also presents an argument in regards to Javitt failing to teach the limitation “a device configured to obtain one or more data features from the patient.” The examiner maintains the previous rejection due to the broad nature of this limitation including the generic recitation of “the device” and “one or more data features.” The examiner has presented new grounds of rejection for claim 19 under 35 U.S.C. 103 in light of the amendments including “delivering neurostimulation therapy when relapse is predicted”.
Applicant’s arguments filed 12 December 2025 with respect to the rejection of
Claim 7 under 35 U.S.C.103 has been fully considered however, the examiner acknowledges the cancellation of claim 7 per the most recent set of claim amendments submitted on 12 December 2025.
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.
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/B.N.K./Examiner, Art Unit 3791
/CHRISTINE H MATTHEWS/Primary Examiner, Art Unit 3791