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 .
Status of the Claims
A timeline of recent prosecution is provided below:
On 7/24/2024, a final rejection was mailed by the Office.
On 11/25/2024, a response after final action with a set of amended claims was submitted by the Applicant.
On 12/3/2024, an advisory action was mailed by the Office, responsive to the after final response.
On 12/19/2024, a request for continued examination was submitted by the Applicant. The RCE form requested examination of claims filed 12/3/2025; however, no claims were filed on that date, and Examiner assumed a clerical error and intention to examine the most recently submitted claims (those filed 11/15/2024 with the after final response).
On 1/7/2025, an interview was conducted telephonically between Primary Examiner Karen Hranek and Applicant’s Representative Mark Harrington (Reg. No. 31686).
On 1/10/2025, an interview summary was mailed by the Office.
On 1/15/2025, a supplemental amendment was filed by the Applicant, which was mis-labeled as an Applicant summary of the interview in the file wrapper.
On 2/6/2025, a nonfinal rejection was mailed by the Office, examining the claims filed 11/25/2024.
On 8/6/2025, a request for reconsideration was filed by the Applicant, requesting consideration of the claims filed 1/15/2025 with the supplemental amendment. The request for reconsideration included a copy of the claims with “previously presented” status indicators for each of the claims relative to those filed with the supplemental amendment.
In the instant case, the supplemental amendment filed 1/15/2025 is being entered, and the corresponding claims are considered on the merits below in a non-final rejection.
The status of the claims as of the supplemental response filed 1/15/2025 is as follows: Claims 1-33, 35-53, 55, and 69 remain cancelled. Claims 34, 54, 56, 64-65, and 73 are currently amended. Claims 57-63, 66-68, and 70-72 are as previously presented. Claims 34, 54, 56-68, and 70-73 are currently pending in the application and have been considered below.
Response to Amendment
Rejection Under 35 USC 101
The claims have been amended but the 35 USC 101 rejections are upheld.
Rejection Under 35 USC 103
The amendments made to the claims introduce limitations that are not fully addressed in the previous office action, and thus the corresponding 35 USC 103 rejections are withdrawn. However, Examiner will consider the amended claims in light of an updated prior art search and address their patentability with respect to prior art below.
Response to Arguments
Rejection Under 35 USC 101
On pages 10-11 of the response filed 8/6/2025 Applicant argues that claim 56 as amended in the 1/15/2025 submission is not directed to an abstract idea because it “is directed to a specific, practical technological solution” including “an apparatus that dynamically detects physiological events, associates those events with personal annotations, and uses the association to prioritize and calibrate future detection.” Applicant concludes that “these steps do not merely involve data collection and display – they involve technological operations that affect how future event detection is performed, representing an improvement in physiological monitoring systems.” Applicant’s arguments are fully considered, but are not persuasive. Examiner maintains that the steps of evaluating physiological data collected from biosensors to detect events, associating those events with contemporaneous patient annotations (e.g. confirming that an event did in fact occur, or that there is no health-related event currently being experienced), and evaluating the associated data to prioritize and calibrate future event detection parameters is part of the abstract idea itself, because a human actor managing their personal behavior and interactions with a patient could achieve these functions (as explained in para. 18 below). The alleged improvement is thus in the abstract process of adjusting or calibrating future event detection parameters and prioritization schemas, not in any technical elements of the biosensors themselves or specific technical signal processing techniques. Because these functions are part of the abstract idea itself, they cannot provide “significantly more” than the abstract idea and thus do not confer eligibility (see MPEP 2106.05(a): “It is important to note, the judicial exception alone cannot provide the improvement. The improvement can be provided by one or more additional elements.” See also 2106.05(a)(II): “it is important to keep in mind that an improvement in the abstract idea itself… is not an improvement in technology.”)
On page 11 of the response Applicant argues that “the combination of customized event detection, biosensor-derived physiological data, temporal correlation with a user annotation, and adaptive updating of event detection criteria provides a non-conventional and non-generic arrangement of known technologies,” and that “the calibration step after event detection reflects a feedback loop for personalized medical monitoring systems, which is a technical improvement over conventional static threshold systems.” Applicant’s arguments are fully considered, but are not persuasive. Examiner maintains that the functions of maintaining customized event detection data, evaluating biosensor-derived physiological data to detect events, correlating detected events with contemporaneously collected user annotations, and adaptively updating event detection criteria fall into the abstract idea category of certain method of organizing human activity, because they describe steps that a human actor such as a clinician or caregiver could achieve by managing their personal behavior and/or interactions with a patient for ongoing patient monitoring and event detection operations. As explained above, an improvement to an abstract idea (i.e. iteratively adjusting patient monitoring and event detection/prioritization schemas in a feedback loop) is not an improvement to technology, nor does it represent an unconventional combination of additional elements. The only additional elements recited beyond the abstract idea itself in claim 56 are the use of a processor executing stored instructions to perform the various steps of the invention as well as the use of a biosensor to electronically receive and obtain the physiological measurement data. Such additional elements amount to instructions to “apply” the exception (e.g. by using a high-level computer components like a processor and memory to digitize and/or automate the otherwise-abstract functions of maintaining event detection data, receiving an annotation from a person, detecting an event, temporally associating the event and annotation, prioritizing the detected event, and calibrating the customized event detection data) and insignificant extra-solution activity (e.g. by utilizing high-level biosensors as a means of gathering the physiological measurement data required for the main data analysis steps of the invention).
On pages 11-12 of the response, Applicant argues that “unlike manual care, Claim 56 automates detection, annotation association, prioritization, and calibration steps – across time and data sources” and that “the apparatus does not simulate human behavior – it adapts dynamically in real time based on user-provided contextual data (annotations), sensor data, and personalized parameters, leading to automated tuning of detection logic,” concluding that “this is more akin to the type of technological solution to a medical signal analysis problem, not organizing human activity,” citing to McRO and CardioNet. Applicant’s arguments are fully considered, but are not persuasive. Examiner agrees that the invention appears to automate detection, annotation association, prioritization, and calibration steps, but respectfully disagrees that such steps do not simulate human behavior. Each of these steps are claimed at a highly functional level, with no technical details regarding how any of these steps are achieved; Examiner maintains that but for the recitation of high-level computing components, a human actor would be capable of performing the event detection, annotation association, prioritization, and calibration steps as claimed by using their medical expertise and judgement in conjunction with interactions with a patient under their care. The automation of these otherwise-abstract steps in a computerized environment thus amounts to mere instructions to “apply” the exception such that they are digitized and/or automated, and does not provide integration into a practical application or “significantly more” than the abstract idea itself.
Examiner respectfully disagrees that the claims are similar to those found eligible in McRO and CardioNet. In McRO, the claimed invention recited a very specific set of rules that allowed a computer to perform animation in a manner that was previously only performable by human animators. The very fact that the animation could not be previously performed by computers and that the rules applied by the claimed invention solved this problem was the reason the claimed invention in McRO was found to be not directed to an abstract idea by improving an existing technological process. Here there is no evidence on record that establishes that the claimed invention was only previously performable by humans in the manner of McRO. The claimed invention thus does not provide an analogous technological improvement, and is instead directed to the abstract idea of patient monitoring and event detection, which is not understood to be a technological problem because it is a common type of patient-clinician interaction. Further, the instant claims are not analogous to the specific cardiac signal processing determined to be an improvement to cardiac monitoring technology as in CardioNet. As explained above, the data processing steps of the instant claims are recited functionally at a very high level and do not include technical details of signal processing of any specific type of physiological measurement data, and thus are not found to be directed to be directed to a technological solution to a medical signal analysis problem as Applicant asserts.
On page 12 of the response Applicant argues that “claim 56 improves event detection systems by: reducing false positives and improving accuracy, automatically adapting based on personalized annotations and biosignal context, [and] introducing a feedback loop that reconfigures event detection thresholds and logic, based on temporally associated user insight.” Applicant’s arguments are fully considered, but are not persuasive. As explained in paras. 6-8 above, such functions are considered part of the abstract idea itself and thus do not provide a technological improvement. The use of computer elements to automate these otherwise-abstract functions amounts to instructions to “apply” the abstract idea and does not confer patent eligibility.
On page 12 of the response Applicant argues that the elements of claim 56 “are not generic,” submitting that “claim 56 includes a feedback calibration mechanism that updates detection logic based on real-time physiological sensor data plus annotation-derived context,” which is not a well-understood, routine, and conventional combination and further “works without human intervention once running.” Applicant’s arguments are fully considered, but are not persuasive. As explained in paras. 6-8 above, such functions are considered part of the abstract idea itself and thus do not provide a technological improvement or “significantly more” than the abstract idea itself. The use of computer elements to automate these otherwise-abstract functions amounts to instructions to “apply” the abstract idea and does not confer patent eligibility.
Rejection Under 35 USC 103
On pages 12-17 of the response filed 8/6/2025 Applicant alleges various deficiencies of the Koverzin and Dumont references with respect to claim 56 as presented in the amendments filed 1/15/2025. Applicant’s arguments are fully considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 34, 54, 56-68, and 70-73 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claims 34, 54, 56, and 73 each recite limitations directed to “subsequently temporally associating the event with the annotation to form a derived temporally associated annotation signal based on: the annotation, the physiological measurement data from the electronic signals, and the customized event detection data to form the temporally associated annotation signal.” Applicant’s original specification does not provide sufficient written support for a positively recited step of temporally associating an event object with an annotation object to form a derived temporally associated annotation signal. The specification provides no evidence that a distinct step of amending, editing, or otherwise manipulating an event data object with a temporal association to an annotation data object to generate a separate “temporally associated annotation signal” is intended. Rather, the only mention of temporal association in the original disclosure includes “detecting an event that is temporally associated with the annotation using the physiological measurement data and the event detection data” as in paras. [0009], [0031], [0058]-[0059], & [0079] (paragraphs are renumbered in accordance with the amended specification filed 1/10/2022). This disclosure shows that an event and an annotation may be considered “temporally associated” with each other as a time-based descriptor rather than as a result of a separate “temporal associating” step that derives a separate “temporally associated annotation signal.” As Applicant notes on page 11 of the response filed 1/15/2025, Pg 8 of the original specification discloses that the system may send “collected and/or derived information to the remote data processing system.” However, this is the only mention of “derived” data in the entire specification, and it makes no mention of a distinct “temporally associated annotation signal” being the type of data that is derived. Because this limitation was not present in the original disclosure as filed, it constitutes new matter and is rejected under 35 U.S.C. 112(a). Claims 57-68 and 70-72 are also rejected on this basis because they inherit the unsupported limitation due to their dependence on claim 56.
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 56-68 and 70-72 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 56 recites “calibrate the customized event detection data for a future detecting of the event or the prioritizing of the event based on a combination of the annotation and the obtained physiological measurement the temporally associated annotation signal” in the final limitation. It is unclear what specific data types are required as the basis for calibrating the prioritizing of the event, because the claim recites that this step is “based on a combination of the annotation and the obtained physiological measurement the temporally associated annotation signal,” which contains confusing wording/grammar. For purposes of examination, Examiner will interpret this limitation as indicating that calibrating the prioritizing of the event is based on the temporally associated annotation signal in accordance with a similar limitation of claim 73. Claims 57-68 and 70-72 are also rejected on this basis because they inherit the indefinite limitation due to their dependence on claim 56.
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 34, 54, 56-68, and 70-73 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
In the instant case, claims 34, 56-68, and 70-73 are directed to apparatuses (i.e. machines), and claim 54 is directed to a method (i.e. a process). Thus, each of the claims falls within one of the four statutory categories. Nevertheless, the claims fall within the judicial exception of an abstract idea.
Step 2A – Prong 1
Independent claims 34 and 54 recite steps that, under their broadest reasonable interpretations, cover certain methods of organizing human activity, e.g. managing personal behavior, relationships, or interactions between people. Specifically, claim 34 (as representative) recites:
An apparatus comprising: at least one processor; and at least one memory storing instructions, that when executed by the at least one processor, cause the apparatus at least to:
maintain customized event detection data for a person;
receive electronic signals from at least two different biosensors on or in the person to obtain physiological measurement data indicative of physiological status of the person, wherein the obtaining of the physiological measurement data comprises using the electronic signals from the two different biosensors to obtain the physiological measurement data;
detect at least one event using the physiological measurement data from the electronic signals and the event detection data;
responsive to detection of the at least one event, prompt the person to issue an annotation;
subsequently temporally associate the event with the annotation to form a derived temporally associated annotation electronic signal based on: the annotation, the physiological measurement data from the electronic signals, and the customized event detection data to form the temporally associated annotation electronic signal;
where the instructions, when executed by the at least one processor, cause the apparatus to use the temporally associated annotation electronic signal to calibrate at least one of: a listing of the detected at least one event, or a prioritizing of the detected at least one event comprising: adjusting, for a physiological parameter, a maximum or a minimum of an anomaly limit of an anomaly pattern of the customized event detection data detected based on threshold limits for the person, wherein the adjusting comprises suppressing a detected event by lowering a prioritization order of the event in future reports by one step; and
based on the adjusting, determining a development curve or mutual changes of measurements based on the at least two different biosensors obtaining the physiological measurement data from the electronic signals;
based on the determined development curve or mutual changes of measurements and the temporally associated annotation electronic signal, prioritizing the detected at least one event, wherein the prioritizing is configured to be used for subsequent verification, and wherein the prioritizing uses predetermined prioritizing criteria arranged using a list comprising a set of events prioritized by order;
use the prioritizing and the determined development curve or mutual changes of measurements to calibrate the detecting of the at least one event comprising adjusting the customized event detection data for diagnostically evaluating the physiological measurement data from the electronic signals based on the temporally associated annotation electronic signal.
Each of the italicized steps, when considered in the context of each claim as a whole, describe a medical monitoring / event detection interaction that could take place between a patient and their care team. For example, a caregiver could keep records or notes about medical or physiological parameters and customized thresholds that need to be monitored for a particular patient (i.e. maintain customized event detection data), look at electronic signals indicative of physiological measurement data obtained by at least two physiological sensors (e.g. heart rate, blood pressure, glucose levels, etc.), and determine if an adverse event (e.g. heart attack, hypoglycemia, etc.) may be occurring based on that patient’s specific thresholds. The caregiver could then interact with the patient to prompt them for a spoken or uttered confirmation or denial of the potential adverse event, temporally associate the response with the detected event (e.g. by recording time stamps for both data types), and use the patient’s response to prioritize the severity of the detected event based on a preset list of priority conditions and re-adjust the personalized thresholds maintained for that patient (e.g. by increasing an allowed maximum of certain physiological parameter(s) if they are leading to false positive events). Further, a confirmed false alarm could lead the caregiver to pay less attention to future event detections of the same type (i.e. suppress a detected event by lowering a prioritization order of the event in future reports by one step). Throughout this process, the caregiver may adjust the thresholds being monitored for each parameter for each patient (i.e. calibrating a listing or prioritization) and determine events going forward based on the adjusted thresholds, e.g. by considering simultaneous changes in at least two sensor readings (i.e. determining mutual changes of measurements by biosensors) for the purpose of diagnostic evaluation. Thus, the steps recited in these claims describe various interactions between a patient and a monitoring care team, and accordingly each independent claim recites an abstract idea in the form of a certain method of organizing human activity.
Independent claims 56 and 73 recite substantially similar steps that, under their broadest reasonable interpretations, cover certain methods of organizing human activity, e.g. managing personal behavior, relationships, or interactions between people. Specifically, the claim 56 (as representative) recites:
An apparatus for processing physiological measurement, the apparatus comprising: at least one processor; and at least one memory storing instructions, that when executed by the at least one processor, cause the apparatus at least to:
maintain customized event detection data for a person, comprising at least one of: age, weight, height, normal blood pressure, indication of one or more illnesses of the person, or maximum pulse of the person;
receive electronic signals from at least one biosensor on or in the person to obtain physiological measurement data indicative of physiological status of the person, where the obtaining of the physiological measurement data comprises using the electronic signals from the at least one biosensor to obtain the physiological measurement data;
receive an annotation from the person;
detect an event using the physiological measurement data from the electronic signals and the customized event detection data;
subsequently temporally associate the event with the annotation, to form a temporally associated annotation signal based on: the annotation, the physiological measurement data from the electronic signals, and the customized event detection data to form the temporally associated annotation signal;
where the instructions, when executed by the at least one processor, cause the apparatus to use the temporally associated annotation signal to prioritize the detected event;
where the instructions, when executed by the at least one processor, cause the apparatus to, after the event is detected, calibrate the customized event detection data for a future detecting of the event or the prioritizing of the event based on a combination of the annotation and the obtained physiological measurement the temporally associated annotation signal.
Each of the italicized steps, when considered in the context of each claim as a whole, describe a medical monitoring / event detection interaction that could take place between a patient and caregiver. For example, a caregiver could keep records or notes about medical or physiological parameters and customized thresholds that need to be monitored for a particular patient (i.e. maintain customized event detection data), look at electronic signals indicative of physiological measurement data (e.g. heart rate, blood pressure, glucose levels, etc.) from a biosensor along with hearing notes or related information spoken by the patient (i.e. receive an annotation). The caregiver could then examine the received patient information against the known threshold parameters to determine if an event has occurred and note if any annotations occurred near in time to the event (i.e. temporally associate the event with the annotation, e.g. determined by recording and evaluating time stamps for both data types), and determine a severity or other priority of any detected event. The caregiver could then make adjustments or calibrations to the patient-specific event detection thresholds (e.g. raising a threshold needed to trigger a heart-related event) or event prioritization schema for use in future monitoring based on the evaluated data. Thus, the steps recited in these claims describe various interactions between a patient and a monitoring caregiver, and accordingly recite an abstract idea in the form of a certain method of organizing human activity.
Dependent claims 57-68 and 70-72 inherit the limitations that recite an abstract idea from their dependence on claim 56, and thus these claims also recite an abstract idea under the Step 2A – Prong 1 analysis. In addition, claims 57-68 merely further describe the abstract idea identified above, and thus also fall into the certain method of organizing human activity identified above. Specifically, claim 57 further describes the annotation as being received by monitoring output of the person, which a caregiver could perform during a patient monitoring interaction. Claims 58-60 further describe the customized event detection data as indicating parameter limits or thresholds for one or more types of parameters, which a caregiver would be capable of maintaining and referring back to throughout a patient monitoring interaction. Claims 61-62 further describe supplementing received physiological measurements with additional parameters if a predetermined event defined by the customized event detection data is detected, which a caregiver could perform by checking for additional data if a particular known event occurs (e.g. looking for time of last meal or insulin injection if blood sugar drops below a certain threshold) during a patient monitoring interaction. Claims 63-65 describe estimating a significance of a detected event and prioritizing and/or classifying the event based on the estimated significance and annotation, which a caregiver could perform during a patient monitoring interaction by using past experience or medical training to determine how serious a detected event is and classifying or prioritizing the severity of the event according to the available patient information. Claim 66 describes prompting a patient for the annotation based on a detected event, physiological measurements, and the customized event detection data, which a caregiver could achieve by asking a patient if they are okay or need assistance if they notice that parameters falling outside of the patient’s known acceptable limits during a patient monitoring interaction. Claim 67 recites sending at least one of the physiological measurement data, an indication of the detected event, or the annotation to another entity, which a caregiver could achieve by sharing these types of data with a colleague, family member of the patient, or other entity. Claim 68 describes receiving feedback about event detection or prioritization, which a caregiver could achieve by soliciting feedback from a patient about the accuracy of their monitoring or severity estimations. Thus, dependent claims 57-68 and 70-72 also recite an abstract idea in the form of a certain method of organizing human activity.
However, recitation of an abstract idea is not the end of the analysis. Each of the claims must be analyzed for additional elements that indicate the abstract idea is integrated into a practical application to determine whether the claim is considered to be “directed to” an abstract idea.
Step 2A – Prong 2
The judicial exception is not integrated into a practical application. In particular, independent claims 34, 54, 56, and 73 do not include additional elements that integrate the abstract idea into a practical application. Claims 34, 56, and 73 include the additional elements of an apparatus comprising at least one processor and at least one memory storing instructions, that when executed by the at least one processor, cause the apparatus to perform the maintaining, receiving, obtaining, detecting, prompting, associating, calibrating, adjusting, suppressing, determining, prioritizing, using, etc. functions described above, as well as receiving electronic signals from biosensors on or in a person to obtain the physiological measurement data. Claim 34 further specifies that the temporally associated annotation signal is electronic. These additional elements, when considered in the context of each claim as a whole, do not provide integration into a practical application. The use of computing elements recited at a high level of generality (such as a processor executing instructions stored in a memory) to perform the steps and/or functions of the invention amount to the words “apply it” with a computer because otherwise-abstract steps are merely being implemented with generic computing elements such that the certain method of organizing human activity is digitized/automated (see MPEP 2106.05(f)). Similarly, specifying that the temporally associated annotation signal is electronic merely utilizes high-level computer architecture to digitize this otherwise-abstract element such that it is embodied in an electronic environment rather than being manually derived by a human actor like a caregiver managing their personal behavior and interactions with a patient. Further, the use of biosensors to receive electronic signals to obtain the physiological measurement data amounts to insignificant extra-solution activity in the form of a data gathering operation because these high-level elements are merely invoked as a means of gathering data needed for the main patient monitoring and event detection steps (see MPEP 2106.05(g)). Accordingly, each independent claim as a whole is directed to an abstract idea without integration into a practical application.
The judicial exception recited in dependent claims 57-68 and 70-72 is also not integrated into a practical application under a similar analysis as above. Claims 57-62, 64-66, and 68 do not introduce any new additional elements, and are performed with the same additional elements identified for claim 56 above; accordingly, they are not integrated into a practical application. Claim 63 specifies that the prioritization and significance estimation functions are performed via usage of a machine learning process, but because the machine learning process is recited at a high level of generality with no particular steps, inputs, outputs, etc., this additional element also merely amounts to the words “apply it” with a computer because it uses generic computer elements to digitize or automate otherwise-abstract steps that could be achieved by a caregiver during a patient monitoring interaction. Claim 67 introduces the functional additional element of sending at least one of the physiological measurement data, an indication of the detected event, and the annotation to a remote data processing system, merely digitizes the otherwise-abstract function of sharing data between entities such that it amounts to instructions to “apply” the judicial exception in a digitized environment. Examiner notes that the sent data is not further relied upon or utilized in any manner and thus may also be considered to amount to a mere data outputting function which is insignificant extra-solution activity (see MPEP 2106.05(g)). Claim 70 specifies that a speech recognition circuitry is used to recognize spoken annotation from the person, while claims 71-72 specify that a user interface is used to receive the annotation from the person in a context-sensitive manner. Each of these additional elements again merely utilize a computing component recited at a high level of generality (e.g. a speech recognition circuitry or a user interface) to digitize steps that could otherwise be achieved in a patient monitoring interaction between a patient and caregiver (e.g. hearing and recognizing human speech in context) and thus amount to the words “apply it” with a computer.
Accordingly, the additional elements of claims 34, 54, 56-68, and 70-73 do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Claims 34, 54, 56-68, and 70-73 are directed to an abstract idea.
Step 2B
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of a processor executing stored instructions to electronically perform the maintaining, receiving, obtaining, detecting, prompting, associating, calibrating, adjusting, suppressing, determining, prioritizing, using, etc. steps of the invention amount to mere instructions to apply the exception using generic computer components. As evidence of the generic nature of the above recited additional elements, Examiner notes Fig. 8 and paras. [0060]-[0063] of Applicant’s specification, where a data processing system with various known processor and memory elements are described (e.g. “The at least one processor 830 comprises, for example, any one or more of: a master control unit (MCU); a microprocessor; a digital signal processor (DSP); an application specific integrated circuit (ASIC); a field programmable gate array; and a microcontroller” in [0061] & “a ‘computer-readable medium’ may be any non-transitory media or means that can contain, store, communication, propagate or transport the instructions for use by or in connection with an instruction execution system, apparatus, or device, such as a computer, with one example of a computer described and depicted in Fig. 8” in [0063]) such that one of ordinary skill in the art would understand that any generic processor and memory combination could be utilized to achieve the invention.
Use of various biosensors on or in a patient to receive electronic signals to obtain physiological measurement data of the patient amounts to insignificant extra-solution activity in the form of necessary data gathering, as explained above. Examiner further notes that receiving or transmitting data over a network is a well-understood, routine, and conventional computer function, as outlined in MPEP 2106.05(d)(II). Further, the use of multiple biosensors to electronically obtain data for use in patient monitoring and/or event detection applications is well-understood, routine, and conventional, as evidenced by at least Brockway et al. (US 20060200007 A1) Fig. 6, [0021], [0026], & [0030]; Koverzin (US 20100286490 A1) Fig. 2 & [0060]-[0064]; and Papadopolos et al. (US 20110025493 A1) Figs. 1-2 & [0032].
Further, the combination of these additional elements is not expanded upon in the specification as a unique arrangement and as such relies on the knowledge of one of ordinary skill in the art to understand the combination of components within a computer system as a well-known and generic combination for automating an abstract idea that could otherwise be performed as a certain method of organizing human activity and thus do not provide an inventive concept. Additionally, the combination of a processor executing stored instructions to receive and analyze physiological parameters and other patient information obtained from biosensors for event detection purposes is a well-understood, routine, and conventional combination, as evidenced by Brockway Figs. 1 & 6, [0048]; Koverzin Figs. 2-3 & [0055]; and Papadopolos Figs. 1-2 & [0032]-[0033].
Additionally, as noted above, the use of a machine learning process to estimate event significance as in claim 63, a speech recognition circuitry to recognize spoken annotation as in claim 70, and a user interface to receive the annotation as in claims 71-72 amount to mere instructions to apply the exception using generic computer components. As evidence of the generic nature of the above recited additional elements, Examiner notes that no specific machine learning processes are described in Applicant’s specification, and they appear to be intended as any generic artificial intelligence or machine learning methods capable of automating the expertise of a medical professional as noted in at least paras. [0024] & [0054] (“The diagnostic work can be left for such a professional or perhaps be performed by an artificial intelligence circuitry configured to perform the work of such a professional”). Further, the user interface and speech recognition circuitry are not described in-depth as particular systems, with para. [0061] utilizing broad language and examples of known types of user interfaces and generic speech recognition. Additionally, use of artificial intelligence and machine learning processes in combination with generic computer processing elements to provide event detection and/or prioritization is well-understood, routine, and conventional, as evidenced by at least Brockway Fig. 1 & [0064]-[0067]; Strachan et al. (US 20170071484 A1) abstract & [0035]-[0037]; Chung et al. (US 20150106020 A1) [0046]-[0049] & [0073]-[0074]; and Johnson et al. (US 20080139898 A1) [0022]. Similarly, the use of a user interface in combination with generic computer processing elements to receive annotations or other information from a patient is well-understood, routine, and conventional, as evidenced by at least Koverzin Fig. 2, [0056], & [0065]; Bardy (US 6997873 B2) Col8 L47-53 & Col14 L37-59; and Shaoulian (US 20140114142 A1) Fig. 2, [0015], & [0021]. Finally, the use of a speech recognition circuitry in combination with generic computer processing elements to recognize spoken patient input is well-understood, routine, and conventional, as evidenced by at least Bardy Col15 L43 – Col16 L14; Koverzin Fig. 3 & [0082]; and Shaoulian Fig. 2 & [0021].
As explained above, the additional element of sending various types of data to a remote data processing system as in claim 67 amounts to the mere digitization of an otherwise-abstract data sharing function and/or insignificant extra-solution activity in the form of outputting data from the main analysis steps. This activity is also nothing more than that recognized as a well-understood, routine, and conventional computer function performed using generic computer components; for example, receiving or transmitting data over a network is recognized as a well-understood, routine, and conventional function previously known to the industry, as outlined in MPEP 2106.05(d)(II).
Thus, when considered as a whole and in combination, claims 34, 54, 56-68, and 70-73 are not patent eligible.
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 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.
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.
Claims 34, 54, 56-60, 63-68, and 70-73 are rejected under 35 U.S.C. 103 as being unpatentable over Booth (US 20160227361 A1) in view of Zhang (Reference U on the accompanying PTO-892).
Claims 34 and 54
Booth teaches an apparatus comprising:
at least one processor; and at least one memory storing instructions, that when executed by the at least one processor, cause the apparatus at least to (Booth [0108]-[0111]):
maintain customized event detection data for a person (Booth [0006], [0038], [0062], [0072], [0079], noting the system stores user-specific thresholds, sensitivity levels, “normal” patterns or ranges, etc. for each user that may be utilized for detecting events, considered to encompass customized event detection data);
receive electronic signals from at least two different biosensors on or in the person to obtain physiological measurement data indicative of physiological status of the person, where the obtaining of the physiological measurement data comprises using the electronic signals from the at least two different biosensors to obtain the physiological measurement data (Booth [0008], [0037], [0043], noting data from multiple wearable sensors like accelerometers, magnetometers, altimeters, gyroscopes, and temperatures sensors can be obtained and electronically sent for analysis to a server of the system to assess the health status of a user; see also [0093], noting other sensors can include leads for obtaining heart data as well as oxygen and pulse sensors);
detect at least one event using the physiological measurement data from the electronic signals and the event detection data (Booth [0072], [0080], [0084], noting the system can evaluate the collected data (i.e. physiological measurement data) to detect an aberration or break in the user’s specific learned patterns of activity data (i.e. event detection data) indicative of an event);
responsive to detection of the at least one event, prompt the person to issue an annotation (Booth [0072]-[0073], [0080], [0087], noting the system queries the user for a verbal or button-based indication that they are okay or not when an aberrant event is detected);
where the instructions, when executed by the at least one processor, cause the apparatus to use the temporally associated annotation electronic signal to calibrate at least one of: a listing of the detected at least one event, or a prioritizing of the detected at least one event (Booth [0072], noting the detected aberration or break (i.e. event) can be categorized (i.e. prioritized), for example based on a user determined urgency (i.e. based on a user annotation temporally associated with the event as in [0073])) comprising: adjusting for a physiological parameter, a maximum or a minimum of an anomaly limit of an anomaly pattern of the customized event detection data detected based on threshold limits for the person (Booth [0038], [0079], noting the patient-specific thresholds and “normal” activity patterns are continuously adjusted/updated for each user; such activity patterns can include “normal ranges of physiologic patterns” per [0006], which is considered to include a maximum and minimum of an anomaly limit), wherein the adjusting comprises suppressing a detected event by lowering a prioritization order of the event in future reports by one step (Booth [0072], noting a user can indicate that a detected pattern aberration (i.e. event) should be ignored for a future period of time; this is considered equivalent to lowering a prioritization order of the event in future reports by one step because the event urgency is being lowered from causing an alert to being ignored for alerting purposes); and
based on the adjusting, determining a development curve or mutual changes of measurements based on the at least two different biosensors obtaining the physiological measurement data from electronic signals (Booth [0037]-[0038], noting data from multiple sensors can be fused together to determine patterns (i.e. mutual changes of multiple sensor types) and aberrations from the continuously updated “normal” patterns (i.e. based on the adjusted anomaly limits)), and
based on the determined development curve or mutual changes of measurements and the temporally associated annotation electronic signal, prioritize the detected at least one event, wherein the prioritizing is configured to be used for subsequent verification, and wherein the prioritizing uses predetermined prioritizing criteria that it is not considered patentably limiting);
use the prioritizing and the determined development curve or mutual changes of measurements to calibrate the detecting of the at least one event comprising adjusting the customized event detection data for diagnostically evaluating the physiological measurement data from the electronic signals based on the temporally associated annotation electronic signal (Booth [0038], [0079], noting the patient-specific thresholds and “normal” activity patterns are continuously adjusted/updated for each user based on the collected data, i.e. the fused data representing mutual changes and other patterns as in [0037]; see also [0072], noting that a user annotation designating that a detected event should be ignored (i.e. deprioritized) is considered during a future time period for determining whether or not to output an alert related to a detected event).
In summary, Booth teaches a system that learns and stores customized event detection criteria for each patient so that health-related events may be detected. The system includes the ability to collect user-provided annotations that are temporally associated with detected events, e.g. by prompting a user to provide an input at the time of a detected event (see [0072], [0080], [0087]). However, though the annotations are clearly collected such that they are temporally associated with the detected events, Booth does not discuss a specific step for temporally associating the annotation with the event to form a derived temporally associated annotation electronic signal, such that it fails to explicitly disclose subsequently temporally associate the event with the annotation to form a derived temporally associated annotation electronic signal based on: the annotation, the physiological measurement data from the electronic signals, and the customized event detection data to form the temporally associated annotation electronic signal.
However, Zhang teaches an analogous system for patient monitoring of health-based events that includes steps for temporally associating a detected event (which includes collected physiological data determined to satisfy event/alarm detection criteria) with a subjective