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 Application
Claims 1-12 are currently pending in this case and have been examined and addressed below. This communication is a Final Rejection in response to the Amendments to the Claims and Remarks filed on 10/06/2025.
Claims 1-3, 5-8, and 10-12 are currently amended.
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.
Independent Claims 1, 11, and 12 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without significantly more.
Step 1: Claims 1, and 12 are drawn to a machine. Independent claim 11 is drawn to a process. As such, independent claims 1, 11, and 12 are drawn to one of the statutory categories of invention (Step 1: YES).
Step 2A - Prong One: In prong one of step 2A, the claim(s) is/are analyzed to evaluate whether it/they recite(s) a judicial exception.
Independent Claim 1: A determination apparatus comprising:
at least one memory configured to store processing instructions;
and at least one processor configured to execute the processing instructions to:
compute, from time-series data used when an agitation state is determined, one or more objective indices of data quality including at least one of: a timestamp-difference index, an out-of-range ratio, a data-availability ratio relative to an ideal number of data points, and a matching-rate index;
estimate a cause for an error based on the time-series data used when the agitation state is determined and the one or more objective indices, by applying machine learning;
and issue, via a communication interface, a notification according to a result of the estimation, the notification being selected by decision making logic implemented by the at least one processor.
Independent Claim 11: A notification method for causing a computer to:
compute, from time-series data used when an agitation state is determined, one or more objective indices of data quality including at least one of: a timestamp-difference index, an out- of-range ratio, a data-availability ratio relative to an ideal number of data points, and a matching- rate index;
estimate a cause for an error based on the time-series data used when the agitation state is determined and the one or more objective indices, by applying machine learning;
and issue, via a communication interface, a notification according to a result of the estimation, the notification being selected by decision making logic implemented by the at least one processor.
Independent Claim 12: A non-transitory computer readable recording medium recording a program for causing a computer to realize processing including:
computing, from time-series data used when an agitation state is determined, one or more objective indices of data quality including at least one of: a timestamp-difference index, an out- of-range ratio, a data-availability ratio relative to an ideal number of data points, and a matching- rate index;
estimating a cause for an error based on the time-series data used when the agitation state is determined and the one or more objective indices, by applying machine learning;
and issuing a notification according to a result of the estimating, the notification being selected by decision making logic implemented by the at least one processor.
(Examiner notes: The above claim terms underlined are additional elements that fall under Step 2A - Prong Two analysis section detailed below)
These steps amount to methods of organizing human activity which includes functions relating to interpersonal and intrapersonal activities, such as managing relationships or transactions between people, social activities, and human behavior; satisfying or avoiding a legal obligation; advertising, marketing, and sales activities or behaviors; and managing human mental activity (MPEP § 2106.04(a)(2)(II)(C) citing the abstract idea grouping for methods of organizing human activity for managing personal behavior or relationships or interactions between people). Therefore, compute objective indices of data quality, estimate a cause for an error, and issue a notification are directed to managing personal interactions or personal behavior.
Step 2A - Prong Two: In prong two of step 2A, an evaluation is made whether a claim recites any additional element, or combination of additional elements, that integrate the exception into a practical application of that exception. An “additional element” is an element that is recited in the claim in addition to (beyond) the judicial exception (i.e., an element/limitation that sets forth an abstract idea is not an additional element). The phrase “integration into a practical application” is defined as requiring an additional element or a combination of additional elements in the claim to apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that it is more than a drafting effort designed to monopolize the exception.
Independent claim 1 recites the use of a determination apparatus, at least one memory configured to store processing instructions, and at least one processor configured to execute the processing instructions, in this case to compute, from time-series data used when an agitation state is determined, one or more objective indices of data quality including at least one of: a timestamp-difference index, an out-of-range ratio, a data-availability ratio relative to an ideal number of data points, and a matching-rate index, estimate a cause for an error based on the time-series data used when the agitation state is determined and the one or more objective indices, and issue a notification according to a result of the estimation, only as a tool to perform an existing process and only amounts to an instruction to implement the abstract idea using a computer (MPEP § 2106.05(f)(2)).
Independent claims 1, 11, and 12 recite the use of applying machine learning, only as a tool to apply data to an algorithm and report the results (MPEP § 2106.05(f)(2)) amounting to instruction to implement the abstract idea using a general purpose computer.
Independent claims 1 and 11 recite the use of a via a communication interface, only as a tool to perform an existing process and only amounts to an instruction to implement the abstract idea using a computer (MPEP § 2106.05(f)(2)).
Independent claims 1, 11, and 12 recite the use of the notification being selected by decision making logic implemented by the at least one processor, only as a tool to perform an existing process and only amounts to an instruction to implement the abstract idea using a computer (MPEP § 2106.05(f)(2)).
Independent claim 11 recites the use of a computer, in this case to compute, from time-series data used when an agitation state is determined, one or more objective indices of data quality including at least one of: a timestamp-difference index, an out-of-range ratio, a data-availability ratio relative to an ideal number of data points, and a matching-rate index, estimate a cause for an error based on the time-series data used when the agitation state is determined and the one or more objective indices, and issue a notification according to a result of the estimation, only as a tool to perform an existing process and only amounts to an instruction to implement the abstract idea using a computer (MPEP § 2106.05(f)(2)).
Independent claim 12 recites the use of a non-transitory computer readable recording medium recording a program for causing a computer to realize processing, in this case to compute, from time-series data used when an agitation state is determined, one or more objective indices of data quality including at least one of: a timestamp-difference index, an out-of-range ratio, a data-availability ratio relative to an ideal number of data points, and a matching-rate index, estimate a cause for an error based on the time-series data used when the agitation state is determined and the one or more objective indices, and issue a notification according to a result of the estimation, only as a tool to perform an existing process and only amounts to an instruction to implement the abstract idea using a computer (MPEP § 2106.05(f)(2)).
The Examiner has therefore determined that the additional elements, or combination of additional elements, do not integrate the abstract idea into a practical application. Accordingly, the claim(s) is/are directed to an abstract idea (Step 2A – Prong two: NO).
Step 2B: In step 2B, the claims are analyzed to determine whether any additional element, or combination of additional elements, is/are sufficient to ensure that the claims amount to significantly more than the judicial exception.
As discussed above in “Step 2A – Prong 2”, the identified additional elements, such as the determination apparatus, at least one memory configured to store processing instructions, at least one processor configured to execute the processing instructions, applying machine learning, via a communication interface, the notification being selected by decision making logic implemented by the at least one processor, computer, and non-transitory computer readable recording medium recording a program for causing a computer to realize processing in independent claims 1, 11, and 12 are equivalent to adding the words “apply it” on a generic computer. Each of these elements is only recited as a tool for performing steps of the abstract idea, such as the use of the computer and data processing devices to apply the algorithm. These additional elements therefore only amount to mere instructions to perform the abstract idea using a computer and are not sufficient to amount to significantly more than the abstract idea (MPEP 2016.05(f) see for additional guidance on the “mere instructions to apply an exception”). Each additional element under Step 2A, Prong 2 is analyzed in light of the specification’s explanation of the additional element’s structure. The claimed invention’s additional elements are directed to generic computer component and functions being used to perform the abstract idea.
This conclusion is based on a factual determination. Applicant’s own disclosure in paragraph [0033] acknowledges that the “agitation determination apparatus 400 is, for example, an information processing apparatus such as a personal computer or a tablet used by medical staff, a server set up in a hospital or the like, or a cloud server. The agitation determination apparatus 400 may be a combination of the information processing apparatus such as a personal computer or a tablet, and the server and/or the like". Paragraph [0038] acknowledges that the “storage unit 440 is a storage device such as a hard disk or a memory". Also, paragraph [0049] discloses that the “arithmetic processing unit 450 includes a microprocessor such as an MPU and a peripheral circuit thereof. The arithmetic processing unit 450 reads in the program 446 from the storage unit 440 and executes it, thereby causing the above-described hardware and the program 446 to cooperate with each other to realize various kinds of processing units. Examples of main processing units realized by the arithmetic processing unit 550 include a data acquisition unit 451, an error detection unit 452, an error cause estimation unit 453, a correction instruction unit 454, the score calculation unit 455, the agitation state determination unit 456, and a notification unit 457". Additionally, the disclosure acknowledges in paragraphs [0020-0021] that the “sensor apparatus 200 measures, for example, vital data of the patient, which is a target. Fig. 2 illustrates an example of the configuration of the sensor apparatus 200. Referring to Fig. 2, the sensor apparatus 200 includes, for example, a sensor 210 and a transmission/reception unit 220. For example, the sensor apparatus 200 can realize each of the above-described processing units by hardware. The sensor apparatus 200 may realize each of the above-described processing units through execution of a program stored in a storage device by an arithmetic device such as a CPU…the sensor 210 is at least one of vital sensors such as a heart rate sensor, a respiratory rate sensor, a blood pressure sensor, a body temperature sensor, and a blood oxygen saturation level sensor". Furthermore, paragraph [0112] discloses “the recording medium is a portable medium such as a flexible disk, an optical disk, a magneto-optical disk, or a semiconductor memory".
The Examiner has therefore determined that no additional element, or combination of additional claims elements is/are sufficient to ensure the claim(s) amount to significantly more than the abstract idea identified above (Step 2B: NO).
Therefore, independent claims 1, 11, and 12 are not eligible subject matter under 35 USC 101.
Similarly to independent claims 1, 11, and 12, their dependent claims 2-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., an abstract idea) without significantly more.
Step 1: As for the dependent claims 2-10, the claims are drawn to a machine, as their respective independent claim. Therefore, similarly to the independent claims, the dependent claims are drawn to one of the statutory categories of invention (Step 1: YES).
Step 2A - Prong One:
The dependent claim 2 is directed to estimate the cause for the error based on a quantified state of the data used when the agitation state is determined, the quantified state comprising at least one of the one or more objective indices.
The dependent claim 3 is directed to in a case where the data used when the agitation state is determined is in a state of satisfying a predetermined criterion, estimate that the cause for the error is present, the predetermined criterion including at least one of: the timestamp-difference index exceeding an allowable range, the out-of-range ratio being equal to or greater than a threshold, and the data-availability ratio falling below a threshold relative to an ideal number of data points.
The dependent claim 4 is directed to estimate the cause for the error based on an acquisition condition of the data used when the agitation state is determined.
The dependent claim 5 is directed to estimate the cause for the error based on information indicating a time of acquisition of the data used when the agitation state is determined, including comparison between a time stamp of last-acquired data and a detection time.
The dependent claim 6 is directed to estimate the cause for the error based on connection condition information indicating a connection condition.
The dependent claim 7 is directed to issue a restart instruction according to the result of the estimation.
The dependent claim 8 is directed to determine a priority serving as an index indicating importance of the notification according to information indicating a result of the determination about agitation determined including an agitation determination-use score and issue the notification according to the determined priority.
The dependent claim 9 is directed to determine the priority based on attribute information indicating an attribute of a target.
The dependent claim 10 is directed to detect the occurrence of the error based on the data used when the agitation state is determined, including at least comparing a time stamp with a detection time or confirming whether the data satisfies the predetermined criterion and estimate the cause for the error according to the detection of the occurrence of the error.
Each of these steps of the preceding dependent claims 2-10 only serve to further limit or specify the features of independent claim 1 accordingly, and hence are nonetheless directed towards fundamentally the same abstract idea as the independent claim and utilize the additional elements analyzed below in the expected manner.
As such, the Examiner concludes that the preceding claims recite an abstract idea (Step 2A – Prong One: YES).
Step 2A - Prong Two:
Dependent claims 2-10 recite the use of at least one processor is configured to execute the processing instructions , in this case to estimate the cause for the error, estimate that the cause for the error is present in a sensor configured to acquire the data satisfying the criterion, estimate the cause for the error based on an acquisition condition of the data used when the agitation state is determined, estimate the cause for the error based on information indicating a time of acquisition of the data used when the agitation state is determined, including comparison between a time stamp of last-acquired data and a detection time, estimate the cause for the error based on connection condition information, issue a restart instruction according to the result of the estimation, determine a priority serving as an index indicating importance of the notification according to information indicating a result of the determination about agitation determined, including an agitation determination-use score, issue the notification according to the determined priority, determine the priority based on attribute information indicating an attribute of a target, detect the occurrence of the error based on the data used when the agitation state is determined, and estimate the cause for the error according to the detection of the occurrence of the error, only recites the at least one processor is configured to execute the processing instructions as a tool to perform an existing process and only amounts to an instruction to implement the abstract idea using a computer (MPEP § 2106.05(f)(2)).
Dependent claim 3 recites the use of a sensor, in this case to acquire the data satisfying the criterion, only as being used in its ordinary capacity and is merely a tool to execute the abstract idea (MPEP § 2106.05(f)(2)).
Dependent claim 7 recites the use of an estimation unit, in this case to , only recites the estimation unit as a tool to perform an existing process and only amounts to an instruction to implement the abstract idea using a computer (MPEP § 2106.05(f)(2)).
The Examiner has therefore determined that the additional elements, or combination of additional elements, do not integrate the abstract idea into a practical application. Accordingly, the claim(s) is/are directed to an abstract idea (Step 2A – Prong two: NO).
Step 2B:
As discussed above in “Step 2A – Prong 2”, the identified additional elements, such as the at least one processor is configured to execute the processing instructions, sensor, and estimation unit in dependent claims 2-10 are equivalent to adding the words “apply it” on a generic computer. Each of these elements is only recited as a tool for performing steps of the abstract idea, such as the use of the computer and data processing devices to apply the algorithm. These additional elements therefore only amount to mere instructions to perform the abstract idea using a computer and are not sufficient to amount to significantly more than the abstract idea (MPEP 2016.05(f) see for additional guidance on the “mere instructions to apply an exception”). Each additional element under Step 2A, Prong 2 is analyzed in light of the specification’s explanation of the additional element’s structure. The claimed invention’s additional elements are directed to generic computer component and functions being used to perform the abstract idea.
The Examiner has therefore determined that no additional element, or combination of additional claims elements is/are sufficient to ensure the claim(s) amount to significantly more than the abstract idea identified above (Step 2B: NO).
Therefore, the dependent claims 1-10 are not eligible subject matter under 35 USC 101.
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 1-5, 10, and 12 are rejected under 35 U.S.C. 103 as being unpatentable over KOJIMA (JP-2018083014-A)[hereinafter Kojima], in view of Mahajan et al. (US-20160030752-A1)[hereinafter Mahajan].
As per Claim 1, Kojima discloses a determination apparatus in paragraphs [0012] (vital signal acquisition device) comprising: at least one memory configured to store processing instructions; and at least one processor configured to execute the processing instructions in paragraphs [0017] (a memory to store vital signal acquisition program (synonymous to processing instructions) and a CPU to execute the vital signal acquisition program) to: compute, from time-series data used when an agitation state is determined, one or more objective indices of data quality including at least one of: a timestamp-difference index, an out-of-range ratio, a data-availability ratio relative to an ideal number of data points, and a matching-rate index in paragraphs [0013] and [0023] (compute, from vital and non-vital signals (synonymous to time-series data) used when noise occurs (synonymous to when an agitation state is determined), the amount of times the amplitude is larger than the threshold in a predetermined time (synonymous to an out-of-range ratio)); estimate a cause for an error based on the time-series data used when the agitation state is determined and the one or more objective indices in paragraphs [0013] and [0023] (estimate a noise generation condition (synonymous to a cause of error) based on the vital and non-vital signals used when noise occurs and the amount of times the amplitude is larger than the threshold).
Kojima discloses estimating a cause for an error but does not disclose the process being done by applying machine learning. However, Mahajan discloses estimate a cause for an error based on the time-series data used when the agitation state is determined and the one or more objective indices, by applying machine learning in paragraphs [0024] and [0032-0033] and [0042-0043] and [0072] (estimate the cause of noise (synonymous to a cause for an error) based on physiological data (synonymous to time series data) used when noise occurs (synonymous to when an agitation state is determined) and the first or second noise detection criteria (synonymous to one or more objective indices), by applying algorithms); and issue, via a communication interface, a notification according to a result of the estimation, the notification being selected by decision making logic implemented by the at least one processor in paragraphs [0024] and [0028] and [0045] (display, via a user interface, an alert representing potential lead failure (synonymous to a result of the estimation), the alert selected by alert modules (synonymous to decision making logic) implemented by the processing circuitry).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention of a determination apparatus, as disclosed by Kojima, to be combined with estimating a cause for an error based on the time series data and one or more objective indices by applying machine learning and issuing a notification according to a result of the estimation, as disclosed by Mahajan, for the purpose of accurately identifying a problematic lead with the information available [0004].
As per Claim 2, Kojima and Mahajan disclose the determination apparatus according to claim 1, Kojima also discloses wherein the at least one processor is configured to execute the processing instructions to estimate the cause for the error based on a quantified state of the data used when the agitation state is determined, the quantified state comprising at least one of the one or more objective indices in paragraphs [0013] and [0023-0025] (estimate a noise generation condition based on the statistical value (synonymous to a quantified state of the data) used when noise occurs, the statistical value includes the amount of times the amplitude is larger than a threshold value).
As per Claim 3, Kojima and Mahajan disclose the determination apparatus according to claim 1, Kojima also discloses wherein the at least one processor is configured to execute the processing instructions to, in a case where the data used when the agitation state is determined is in a state of satisfying a predetermined criterion, estimate that the cause for the error is present in a sensor configured to acquire the data satisfying the criterion, the predetermined criterion including at least one of: the timestamp-difference index exceeding an allowable range, the out-of-range ratio being equal to or greater than a threshold, and the data-availability ratio falling below a threshold relative to an ideal number of data points in paragraphs [0013] and [0023-0025] (when the vital and non-vital signals that are acquired when noise occurs is satisfying a predetermined condition (synonymous to a predetermined criterion), estimate a noise generation condition is in a sensor to acquire the vital and non-vital signals satisfying the predetermined criterion of the amount of times the amplitude is larger than the threshold in a predetermined time).
As per Claim 4, Kojima and Mahajan disclose the determination apparatus according to claim 1, Kojima also discloses wherein the at least one processor is configured to execute the processing instructions to estimate the cause for the error based on an acquisition condition of the data used when the agitation state is determined in paragraphs [0013] and [0019] and [0026] (estimate a noise generation condition based on the vital signals measured by sensors, wherein the vital signals include one or more waveforms of P,Q,R,S,T,U waves (synonymous to the acquisition condition)).
As per Claim 5, Kojima and Mahajan disclose the determination apparatus according to claim 1, Kojima also discloses wherein the at least one processor is configured to execute the processing instructions to estimate the cause for the error based on information indicating a time of acquisition of the data used when the agitation state is determined, including comparison between a time stamp of last-acquired data and a detection time in paragraphs [0033-0035] and [0041] (estimate the noise generation condition based on the detection of the P,Q,R,S,T,U waves (synonymous to a time of acquisition of the data used) when noise occurs, including a comparison between a time stamp of last acquired waveform and time stamp when noise occurs).
As per Claim 10, Kojima and Mahajan disclose the determination apparatus according to claim 1, Kojima also discloses wherein the at least one processor is configured to execute the processing instructions to: detect the occurrence of the error based on the data used when the agitation state is determined, including at least comparing a time stamp with a detection time or confirming whether the data satisfies the predetermined criterion in paragraphs [0025-0026] and [0032] and [0041] (detect the occurrence of noise generation based on vital and non-vital signals when noise occur, including confirming whether the vital signals satisfy the predetermined condition); and estimate the cause for the error according to the detection of the occurrence of the error in paragraphs [0032-0033] and [0041] (estimate the noise generation condition according to the detection of noise occurrence).
As per Claim 12, Kojima discloses a non-transitory computer readable recording medium recording a program for causing a computer to realize processing in paragraphs [0017] (a computer readable recording medium recording vital signal acquisition program for causing a CPU to realize processing) including: computing, from time-series data used when an agitation state is determined, one or more objective indices of data quality including at least one of: a timestamp-difference index, an out- of-range ratio, a data-availability ratio relative to an ideal number of data points, and a matching- rate index in paragraphs [0013] and [0023] (computing, from vital and non-vital signals (synonymous to time-series data) used when noise occurs (synonymous to when an agitation state is determined), the amount of times the amplitude is larger than the threshold in a predetermined time (synonymous to an out-of-range ratio)); estimating a cause for an error based on the time-series data used when the agitation an state is determined and the one or more objective indices in paragraphs [0013] and [0023] (estimating a noise generation condition (synonymous to a cause of error) based on the vital and non-vital signals used when noise occurs and the number of times the amplitude is larger than the threshold).
Kojima discloses estimating a cause for an error but does not disclose the process being done by applying machine learning. However, Mahajan discloses estimating a cause for an error based on the time-series data used when the agitation an state is determined and the one or more objective indices, by applying machine learning in paragraphs [0024] and [0032-0033] and [0042-0043] and [0072] (estimating the cause of noise (synonymous to a cause for an error) based on physiological data (synonymous to time series data) used when noise occurs (synonymous to when an agitation state is determined) and the first or second noise detection criteria (synonymous to one or more objective indices), by applying algorithms); and issuing a notification according to a result of the estimating, the notification being selected by decision making logic implemented by the at least one processor in paragraphs [0024] and [0028] and [0045] (displaying an alert representing potential lead failure (synonymous to a result of the estimating), the alert selected by alert modules (synonymous to decision making logic) implemented by the processing circuitry).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention of a non-transitory computer readable recording medium recording a program for causing a computer to compute one or more objective indices of data quality and estimating a cause for an error based on the time series data and one or more objective indices, as disclosed by Kojima, to be combined with estimating a cause for an error based on the time series data and one or more objective indices by applying machine learning and issuing a notification according to a result of the estimation, as disclosed by Mahajan, for the purpose of accurately identifying a problematic lead with the information available [0004].
Claims 6-9 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over KOJIMA (JP-2018083014-A)[hereinafter Kojima], in view of Mahajan et al. (US-20160030752-A1)[hereinafter Mahajan], in view of SULLIVAN et al. (US-20070156031-A1)[hereinafter Sullivan].
As per Claim 6, Kojima and Mahajan disclose the determination apparatus according to claim 1.
Kojima and Mahajan do not disclose the following limitations. However, Sullivan discloses wherein the at least one processor is configured to execute the processing instructions to estimate the cause for the error based on connection condition information indicating a connection condition between apparatuses present between the sensor configured to acquire the data used when the agitation state is determined and the determination apparatus, the connection condition information indicating whether a communicable connection is established between the sensor and a bed terminal and between the bed terminal and the determination apparatus in paragraphs [0009] and [0041] and [0059] and [0069] and Figure 8 (determines UTM situation to be non-latching or latching, wherein the UTM situation includes sensor disconnection or sensor failure between the sensor and the intelligent vigilance monitor (synonymous to connection condition information a connection condition between apparatuses present between the sensor and determination apparatus), wherein the sensor is configured to measure heart rate, respiration rate, blood pressure, temperature, cardiac output, and movement (synonymous to the data used when the agitation state is determined), the connection condition information indicating whether a connection is established between the sensor and the bedside unit (synonymous to a bed terminal) and between the bedside unit and the intelligent vigilance monitor).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention of a determination apparatus, as disclosed by Kojima and Mahajan, to be combined with estimating the cause for the error based on connection condition information, as disclosed by Sullivan, for the purpose of providing a less expensive and more accurate method for noninvasive vital sign monitoring of significant negative conditions and reporting the events [0004-0008].
As per Claim 7, Kojima and Mahajan disclose the determination apparatus according to claim 1.
Kojima and Mahajan do not disclose the following limitations. However, Sullivan discloses wherein the at least one processor is configured to execute the processing instructions to issue a restart instruction according to the result of the estimation by an estimation unit in paragraphs [0071] and [0074] (the non-latching and latching alarms are automatically re-enabled (synonymous to a restart instruction) after a period of time ends if the condition that caused the alarm remains in effect, wherein the condition that caused the alarm includes the type of alert, the values that triggered the alert, and the time the alert was raised (Examiner notes that automatically re-enabling the alarm indicates that a restart instruction was issued)).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention of a determination apparatus, as disclosed by Kojima and Mahajan, to be combined with issuing a restart instruction according to the result of the estimation by an estimation unit, as disclosed by Sullivan, for the purpose of providing a less expensive and more accurate method for noninvasive vital sign monitoring of significant negative conditions and reporting the events [0004-0008].
As per Claim 8, Kojima and Mahajan disclose the determination apparatus according to claim 1.
Kojima and Mahajan do not disclose the following limitations. However, Sullivan discloses wherein the at least one processor is configured to execute the processing instructions to: determine a priority serving as an index indicating importance of the notification according to information indicating a result of the determination about agitation determined in paragraphs [0075-0076] (displays the alert message in a priority-based queue with the highest priority messages being displayed indicating a latching alert message, wherein the latching alert indicates the activation of the alarm signal that continues until stopped by a responder, according to the heart rate and respiration values raising the alarms, wherein the alarms are raised when the heart rate and respiration rate values exceed a threshold) including an agitation determination-use score in paragraphs [0074-0076] (including values that triggered the alert of the occurrence of a clinically significant negative condition (Examiner notes that the values that triggered the alert of a clinically significant negative condition occurring is synonymous to an agitation determination score)); and issue the notification according to the determined priority in paragraphs [0075-0076] (the alert message is displayed, wherein the highest priority messages are displayed at any given time).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention of a determination apparatus, as disclosed by Kojima and Mahajan, to be combined with determining a priority serving as an index indicating importance of the notification including an agitation determination use score, and issue the notification according to the determined priority, as disclosed by Sullivan, for the purpose of providing a less expensive and more accurate method for noninvasive vital sign monitoring of significant negative conditions and reporting the events [0004-0008].
As per Claim 9, Kojima and Mahajan disclose the determination apparatus according to claim 8.
Kojima and Mahajan do not disclose the following limitations. However, Sullivan discloses wherein the at least one processor is configured to execute the processing instructions to determine the priority based on attribute information indicating an attribute of a target in paragraphs [0081] (the priority assignments are set based on the hard limits and soft limits (synonymous to attribute information) of the heart rate and respiration rate, wherein the hard limits include the measured values of the heart rate and respiration rate and the soft limits include the warning values of the heart rate and respiration rate, wherein hard limits are assigned a higher priority than soft limits (Examiner notes that the hard and soft limits indicates physiological attributes of a target or a person)).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention of a determination apparatus, as disclosed by Kojima and Mahajan, to be combined with determine the priority based on attribute information indicating an attribute of a target, as disclosed by Sullivan, for the purpose of providing a less expensive and more accurate method for noninvasive vital sign monitoring of significant negative conditions and reporting the events [0004-0008].
As per Claim 11, Kojima discloses compute, from time-series data used when an agitation state is determined, one or more objective indices of data quality including at least one of: a timestamp-difference index, an out- of-range ratio, a data-availability ratio relative to an ideal number of data points, and a matching- rate index in paragraphs [0013] and [0023] (compute, from vital and non-vital signals (synonymous to time-series data) used when noise occurs (synonymous to when an agitation state is determined), the amount of times the amplitude is larger than the threshold in a predetermined time (synonymous to an out-of-range ratio)); estimate a cause for an error based on the time-series data used when the agitation an state is determined and the one or more objective indices in paragraphs [0013] and [0023] (estimate a noise generation condition (synonymous to a cause of error) based on the vital and non-vital signals used when noise occurs and the amount of times the amplitude is larger than the threshold)
Kojima discloses estimating a cause for an error but does not disclose the process being done by applying machine learning. However, Mahajan discloses estimate a cause for an error based on the time-series data used when the agitation an state is determined and the one or more objective indices, by applying machine learning in paragraphs [0024] and [0032-0033] and [0042-0043] and [0072] (estimate the cause of noise (synonymous to a cause for an error) based on physiological data (synonymous to time series data) used when noise occurs (synonymous to when an agitation state is determined) and the first or second noise detection criteria (synonymous to one or more objective indices), by applying algorithms); and issue, via a communication interface, a notification according to a result of the estimation, the notification being selected by decision making logic implemented by the at least one processor in paragraphs [0024] and [0028] and [0045] (display, via a user interface, an alert representing potential lead failure (synonymous to a result of the estimation), the alert selected by alert modules (synonymous to decision making logic) implemented by the processing circuitry).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention of computing one or more objective indices of data quality and estimating a cause for an error based on the time series data and one or more objective indices, as disclosed by Kojima, to be combined with estimating a cause for an error based on the time series data and one or more objective indices by applying machine learning and issuing a notification according to a result of the estimation, as disclosed by Mahajan, for the purpose of accurately identifying a problematic lead with the information available [0004].
Kojima and Mahajan do not disclose the following limitations. However, Sullivan discloses a notification method for causing a computer in paragraphs [0082-0083] (alert messages operation (synonymous to a notification method) for implemented through an intelligent medical vigilance system (synonymous to a computer)).
It would have been obvious to a person of ordinary skill in the art before the effective filling date of the applicant’s invention of computing one or more objective indices of data quality and estimating a cause for an error based on the time series data and one or more objective indices, as disclosed by Kojima and Mahajan, to be combined a notification method, as disclosed by Sullivan, for the purpose of providing a less expensive and more accurate method for noninvasive vital sign monitoring of significant negative conditions and reporting the events [0004-0008].
Response to Arguments
Applicant’s arguments, see Page 7, “Claim Rejections – 35 USC § 112(b)”, filed 10/06/2025, with respect to claim 7 has been fully considered and are persuasive. The claim rejection of claim 7 has been withdrawn.
Applicant's arguments, see Pages 7-10, “Claim Rejections – 35 USC § 101”, filed 10/06/2025 with respect to claims 1, 11, and 12 have been fully considered but they are not persuasive.
Applicant argues that the amended claim integrates the judicial exception into a practical application by improving the reliability of a physiological monitoring system. Examiner respectfully disagrees. The claims do not recite an improvement to the reliability of a physiological monitoring system. The claims merely recite compute objective indices of data quality, estimate a cause for an error, and issue a notification, which are a part of the abstract idea. An improvement to the abstract ideas of compute objective indices of data quality, estimate a cause for an error, and issue a notification does not amount to an improvement to technology or a technical field (see MPEP § 2106.05(a)(II) stating “it is important to keep in mind that an improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology."). The courts indicated in TLI Communications, 823 F.3d at 612-13, 118 USPQ2d at 1747-48, that gathering and analyzing information using conventional techniques and providing the output is not sufficient to show an improvement to technology. The claim language and instant application fails to provide details regarding how a computer aids the method, the extent to which the computer aids the method, or the significance of a computer to the performance of the method. Here, the improvement is to compute objective indices of data quality, estimate a cause for an error, and issue a notification. There is no indication in the disclosure that the involvement of a computer assists in improving the technology for the outlined problem statement. Merely adding generic computer components to perform the method is not sufficient.
Applicant argues that independent claim 1 recites significantly more than the abstract idea. Examiner respectfully disagrees. The amended claim limitations are directed to compute objective indices of data quality, estimate a cause for an error, and issue a notification. The use of the determination apparatus, at least one memory configured to store processing instructions, at least one processor configured to execute the processing instructions, applying machine learning, via a communication interface, the notification being selected by decision making logic implemented by the at least one processor, computer, and non-transitory computer readable recording medium recording a program for causing a computer to realize processing to carry out the steps of the abstract idea is merely applying the abstract idea to general purpose computer components which amounts to mere instructions to apply the exceptions, see MPEP 2106.05(f)(2). The courts indicated in Alice Corp., 573 U.S. at 225-26, 110 USPQ2d at 1984, that “a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer” is not enough to qualify as significantly more.
Applicant's arguments, see Pages 10-12, “Claim Rejections – 35 USC § 102”, filed 10/06/2025 with respect to claims 1-12 have been fully considered.
With regards to Claims 1-12, Applicant argues that Sullivan does not teach or suggest the amended limitations recited in Claims 1, 11, and 12. Examiner finds this persuasive. Therefore, the rejection of 06/04/2025 has been withdrawn. However, upon further consideration a new grounds of rejection is made over Kojima, in view of Mahajan.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Watanabe (US 20180153482 A1) teaches a medical monitoring apparatus that monitors that status of a patient and determines whether to issue an alert about an abnormality under a condition
Vass, Catherine D et al. (“REFINE (Reducing Falls in In-patient Elderly)--a randomised controlled trial.”) teaches patient monitoring technologies that include bedside monitor equipment to alert staff, outside of the immediate vicinity, to a potential problem and prevent a fall
THIS ACTION IS MADE FINAL. 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KRYSTEN N WRIGHT whose telephone number is (571)272-5116. The examiner can normally be reached Monday thru Friday 8 - 5 pm, ET.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Fonya Long can be reached on (571)270-5096. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/K.N.W./Examiner, Art Unit 3682
/JORDAN L JACKSON/Primary Examiner, Art Unit 3682