Detailed Action
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
The Office Action is in response to claims filed on 1/23/2025 where claims 1-12 are pending and ready for examination.
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more.
Claim 1 recites the abstract ideal of mathematically analyzing sensor data to classify a period as normal or anomalous. Specifically, the claim receives sensor data, preprocesses or smooths the data, processes the smoothed data through a model to produce recovery data, calculates an error with a threshold, and determines whether the data represents a normal period pattern or anomaly period pattern. These limitations recites mathematical calculations and the evaluation of information, which, at the level of generality claimed, may be performed mentally or with pen and paper. Thus claim 1 recites both mathematical concepts and a mental process.
The additional elements do not integrate the abstract ideal into a practical application communication circuit merely receives the data, the memory merely stores the data and model, and the processor merely executes the recited mathematical analysis. The claim does not recite any particular improvement to the operation of the server, processor, memory, communication circuit, sensor, smoothing process, or anomaly-detection model. Nor does the claim use the normal or anomalous determination to control the sensor, modify the operation of the another device, initiate a corrective action, or otherwise produce a technologic result beyond the calculated classification itself. The generic computer components therefore merely provide an environment for carrying out the abstract idea.
Considered individually and as an ordered combination, the additional elements do not amount to significantly more than the abstract idea. The communication circuit performs its ordinary data-receiving function, the memory performs its ordinary data storage function, and the processor performs its ordinary data-processing function. The claim recites no particular computer architectures, unconventional hardware arrangement, or other technical feature that transforms these generic components into an inventive concept. Their ordered combination merely automates the abstract mathematical analysis on a generic server device. Accordingly claim1 is directed to patent-ineligible subject matter.
Independent claim 7 is rejected based on the same rationale as set forth above.
The Examiner has reviewed and analyzed all of the dependent claims (2-6 and 8 -12) The dependent claims do not amount to significantly more than the recited abstract idea.
Accordingly claims 1-12 are rejected under 35 U.S.C. 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 1-3 and 7-9 are rejected under 35 USC 103 as being unpatentable over Soma Bandyopadhyay (US 20190200935), hereinafter referred to as Soma, in further view of Tajima (US 20180275642)
Regarding claim 1, Soma discloses a server device supporting anomaly period detection, comprising:
a communication circuit configured to receive sensor data from a sensor (Soma; As Soma teaches acquiring signals from a sensor for further processing, a communication circuit is necessarily present in order to receive the signals and/or sensor data from the sensor;
see e.g. [0038] “... The system 100 may comprise of the one or more sensors, which are capable of acquiring (i.e., sensing, detecting, or gathering) cardiovascular sound signals from the user when placed on or near the user ...” )
a memory configured to store the received sensor data and an anomaly period detection model (Soma;
[0037] FIG. 2, with reference to FIG. 1, illustrates an exemplary flow diagram of a method for detecting the anomaly in the cardiovascular signal using hierarchical extremas and repetitions. In an embodiment the system 100 comprises one or more data storage devices of the memory 102 operatively coupled to the one or more hardware processors 104 and is configured to store instructions for execution of steps of the method by the one or more processors 104. ); and
at least one processor functionally connected to the communication circuit and the memory, the at least one processor configured to (Soma ;
see e.g. [0037] ):
receive the sensor data from the sensor, produce smoothing period data by performing preprocessing on the sensor data based on the anomaly period detection model corresponding to the sensor (Soma; Soma teaches receiving cardiovascular sensor data form the senso ([0038] – [0039]) and preprocessing the received sensor data by smoothing it with a filter as a prescribed first step of the anomaly-period-detection model before the model derives hierarchical extrema and detects an anomaly from the smoothed data ([0009]). Thus, the smoothing preprocessing is performed based on the anomaly-period-detection model corresponding to the sensor;
[0038] “According to an embodiment of the present disclosure, at step 201, the cardiovascular signal acquired may be smoothened for filtering the cardiovascular signal. According to an embodiment, the cardiovascular signal of the user may be acquired by the system 100 using one or more sensors or devices (not shown in the figure). ...”
[0009] In an embodiment of the present disclosure, there is provided a system for detecting an anomaly in a cardiovascular signal using hierarchical extremas and repetitions, the system comprising one or more processors; one or more data storage devices operatively coupled to the one or more processors and configured to store instructions configured for execution by the one or more processors to: smoothen, using a filter, the cardiovascular signal acquired for filtering the cardiovascular signal; derive ...”);
acquire recovery data by inputting the smoothing period data into the anomaly period detection model (Soma; Soma teaches acquiring recovery data by inputting the smoothing-period-data- the smoothed cardiovascular signal—into the anomaly detection model, which processes the smoothed signal using different detection window sizes and outputs one or more sets of hierarchical extrema representing the detected maximum and minimum points of the signal;
see e.g. [0009] “... derive, using a window detection technique, one or more sets of hierarchical extremas, based upon the smoothened cardiovascular signal, wherein the one or more sets of hierarchical extremas comprises maximum points and minimum points based on rising edges and falling edges of the cardiovascular signal, and wherein each level of hierarchy in the one or more sets of hierarchical extremas represents a different window size of detection; identify, one or more elements of signal patterns, based upon the one or more sets of hierarchical extremas, wherein the one or more elements of signal patterns comprise multiple frequencies and significance associated with the cardiovascular signal for defining a plurality of physiological events of the user or noise; determine, occurrences and randomness of occurrences of the one or more elements of signal patterns, by computing an entropy of occurrences of the one or more elements of signal patterns, wherein the entropy comprises randomness of the one or more elements of signal patterns computed based upon probabilities of repetitions of the one or more elements of signal patterns and identify, significance of repetitions of the one or more elements of signal patterns, based upon the occurrences and randomness of occurrences to detect the anomaly in the cardiovascular signal; determine the occurrences and randomness of occurrences of the one or more elements of signal patterns by obtaining one or more threshold values based upon an equi-probable occurrence of the one or more elements of signal patterns to classify the one or more elements of signal patterns; identify the significance of the one or more elements of signal patterns and the significance of repetitions by obtaining a lower triangular matrix based upon a hierarchy of extremas, wherein the lower triangular matrix comprises number of occurrences of the one or more elements of signal patterns to identify variability in the cardiovascular signal; identify the significance of the one or more elements of signal patterns by evaluating entropy of elements of a lower triangular matrix based upon frequencies and number of points in the one or more elements of signal patterns to detect randomness of the one or more elements of signal patterns; detect, one or more zero patterns in the cardiovascular signal based upon the one or more sets of hierarchical extremas and filter, the one or more zero patterns, based upon a comparison of the one or more zero patterns and a predefined threshold for identifying the one or more elements of signal patterns; identify the one or more elements of signal patterns by identifying uni-modal and multi-modal patterns in the cardiovascular signal based upon the occurrences of the one or more elements of signal patterns; obtain the one or more threshold values by computing an upper threshold value based upon occurrences and henceforth entropy of the one or more elements of signal patterns to detect the anomaly”
Examiner’s note: One of ordinary skill in the art would have found it obvious, through routine design optimization, to selecting the smoothing period in relation to the detection window periods used by Soma’s anomaly detection model so that the smoothed sensor data corresponds to the temporal interval being analyzed. Thus the resulting data constitutes smoothing period data, and the determination made for that detection window constitutes a normal period pattern or anomaly-period pattern),
Soma does not expressly disclose:
determine a normal period pattern or an anomaly period pattern by comparing an error calculated between the smoothing period data and the recovery data with a predetermined threshold.
Tajima discloses:
determine a normal period pattern or an anomaly period pattern by comparing an error calculated between the smoothing period data and the recovery data with a predetermined threshold (Tajima, Tajima permits low pass filtered data to be used a s the model data ([0084]), calculates an anomaly score from the differences between the data before reconstruction and the corresponding reconstructed data ([0126]), determines a normal pattern when the anomaly score is not below the threshold ([0128]). Tajima further teaches that the threshold y is predetermined from the anomaly scores of normal operational data ([0129];
see e.g. [0084] In addition, although the present embodiment uses a predictive model that takes operation data directly as its input or output, operational data to that a low-pass filter has been applied or data such as a difference between operational data sets may be used as the input and output
see e.g. [0126] Next, the detection unit 112 uses an error reconstruction model to reconstruct the prediction error sequence obtained above and calculates an anomaly score based on the sum of the absolute values of the differences (reconstruction errors) between the reconstruction error sequence and the prediction error sequence before the reconstruction (Step 2F202).
[0128] On the other hand, if it is determined as a result of the above check that the anomaly score is not below the threshold γ (Step 2F203: no), the detection unit 112 determines that an anomaly or a sign thereof is detected and proceeds to Step 2F204 (Step 1F203).
[0129] Here, the threshold γ is set to μ+2σ where μ and σ are respectively the mean and standard deviation of anomaly scores of normal operational data, but may be set to another value. )
Therefore it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Tajima’s processing scheme. The motivation being the combined solution provides for implementing a known technique resulting increased efficiencies of data processing.
Regarding claim 2, Soma in view of Tajima disclose The server device of claim 1, wherein the at least one processor is configured to determine the threshold by summing up an average and a standard deviation of the errors between the smoothing period data and the recovery data, and wherein the error includes a mean absolute error per element of a set of the recovery data and the smoothing period data (Tajima calculates the anomaly score as a mean absolute error obtained from the element by element differences between the data before reconstruction and the reconstructed data. ([0126]) Tajima then set the threshold to mu plus two sigma, where mu and sigma are the average and standard deviation of the anomaly scores calculated from normal operation data ([0129]). Thus Tajima teaches determines the threshold from the average and the standard deviation of the errors and calculating the error as a mean absolute error per element of the smoothing-period data and the recovery data)
Therefore it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Tajima’s processing scheme. The motivation being the combined solution provides for implementing a known technique resulting increased efficiencies of data processing
Regarding claim 3, Soma in view of Tajima disclose The server device of claim 1, wherein the at least one processor is configured to determine a case where a value of the error is greater than the threshold as occurrence of the anomaly period pattern, and determine a case where the value of the error is less than the threshold as occurrence of the normal period pattern (The combined solution per Tajima, as Tajima teaches determining occurrence of a normal period pattern when the error vale is below the threshold ([0127]) and determining occurrence of an anomaly-period pattern when the error value is ot below the threshold ([0128]). Thus, an error greater than the threshold is identified as anomalous, while and error less than the threshold is identified as normal)
Therefore it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Tajima’s processing scheme. The motivation being the combined solution provides for implementing a known technique resulting increased efficiencies of data processing
Regarding claim 7, claim 7 comprises the same and/or similar subject matter as claim 1 and is considered an obvious variation. Therefore it is rejected under the same rationale.
Regarding claim 8, claim 8 comprises the same and/or similar subject matter as claim 2 and is considered an obvious variation. Therefore it is rejected under the same rationale.
Regarding claim 9, claim 9 comprises the same and/or similar subject matter as claim 3and is considered an obvious variation. Therefore it is rejected under the same rationale.
Claims 4 and 10 are rejected under 35 USC 103 as being unpatentable over Soma in view of Tajima and in further view of Ogawa (US 2021/0125083)
Regarding claim 4, Soma in view of Tajima disclose the server device of claim 3, Soma does not expressly disclose wherein the at least one processor is configured to create a detection alarm message indicating the anomaly period pattern in response to the occurrence of the anomaly period pattern, and transmit the detection alarm message to a user terminal of an administrator who manages the sensor.
Ogawa discloses:
a detection alarm message indicating the anomaly period pattern in response to the occurrence of the anomaly period pattern, and transmit the detection alarm message to a user terminal of an administrator (Ogawa;
See e.g. [0072] “... an intelligent message alert can be sent to a person or an administrator for deeper analysis or the system may be configured to automatically analyze and diagnose such anomalies ...”)
Therefore it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention incorporate Ogawa’s alarm scheme. The motivation being the combined solution provides for incorporating a known technique resulting in increased efficiencies of processing anomalies.
Soma in view of Tajima and in further view of Ogawa disclose:
create a detection alarm message indicating the anomaly period pattern in response to the occurrence of the anomaly period pattern, and transmit the detection alarm message to a user terminal of an administrator who manages the sensor (The combined solution per Ogawa)
Therefore it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Tajima’s processing scheme. The motivation being the combined solution provides for implementing a known technique resulting increased efficiencies of data processing
Regarding claim 10, claim 10 comprises the same and/or similar subject matter as claim 4 and is considered an obvious variation. Therefore it is rejected under the same rationale.
Claims 5 and 11 are rejected under 35 USC 103 as being unpatentable over Soma in view of Tajima and in further view of Owhadi (US 20160352767)
Regarding claim 5, Soma in view of Tajima disclose The server device of claim 1, Soma does not expressly disclose wherein the at least one processor is configured to create a detection report on the anomaly period detection, and transmit the detection report to a user terminal of an administrator who manages the sensor.
Owhadi discloses:
create a detection report on the anomaly period detection, and transmit the detection report to a user terminal of an administrator who manages the sensor (Owhadi;
See e.g. [0010] “... A report may be generated that includes a column for the calculated probability density and a column for the identified outlier metric to assist an end-user in investigate system anomalies and determine the root cause of the anomaly”
See e.g. [0026] “... the anomaly detection manager 110 may generate a report including a column for the calculated probability density ...”)
Therefore it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date to incorporate Ohwadi’s reporting scheme. The motivation being the combined solution provides for implementing a known technique resulting in increased efficiencies of managing sensors.
Therefore it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Tajima’s processing scheme. The motivation being the combined solution provides for implementing a known technique resulting increased efficiencies of data processing
Regarding claim 11, claim 11 comprises the same and/or similar subject matter as claim 5 and is considered an obvious variation. Therefore it is rejected under the same rationale.
Claims 6 and 12 are rejected under 35 USC 103 as being unpatentable over Soma in view of Tajima and in further view of George (US 20190197146)
Regarding claim 6, Soma in view of Tajima disclose the server device of claim 1, Soma does not expressly disclose wherein the at least one processor is configured to perform a validity check on the sensor data, upon receiving the sensor data, and then store the sensor data in the memory.
George discloses:
perform a validity check on the sensor data, upon receiving the sensor data, and then store the sensor data in the memory (George;
see e.g. [0020] “... A method includes receiving data from one or more sensors; validating the data to yield validated data; storing the validated data in a database of a non-volatile memory”)
Therefore It would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate George’s validation scheme. The motivation being the combined solution provides for implementing a known technique resulting in increased efficiencies of sensor data processing.
Therefore it would have been prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Tajima’s processing scheme. The motivation being the combined solution provides for implementing a known technique resulting increased efficiencies of data processing
Regarding claim 12, claim 12 comprises the same and/or similar subject matter as claim 6 and is considered an obvious variation. therefore it is rejected under the same rationale.
Any inquiry concerning this communication or earlier communications from the Examiner should be directed to TODD L. BARKER whose telephone number is (571) 270 0257. The Examiner can normally be reached on Monday through Friday, 7:30am to 5:00pm.
If attempts to reach the Examiner by telephone are unsuccessful, the Examiner's supervisor Vivek Srivastava can be reached on (571) 272 7304
/TODD L BARKER/Primary Examiner, Art Unit 2449
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