# US 2021/0275046 A1 · Peak Detection System and Method for Calculation of Signal-Derived Metrics > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2021/0275046 A1 - Document ID: US20210275046A1 - Status: Published application - Kind: A1 - Application number: 17/319,915 - Filed: 2021-05-13 - Published: 2021-09-09 - Earliest claimed: 2014-08-14 - Assignees: The Government of the United States, as represented by the Secretary of the Army - Applicants: The Government of the United States as represented by the Secretary of the Army - Inventors: Nehemiah T. Liu; Jose Salinas - Web page: https://patentgrep.com/patent/US20210275046A1 ## CPC - A61B 5/02405: {Determining heart rate variability} - A61B 5/0245: by using sensing means generating electric signals, {i.e. ECG signals} - A61B 5/346: Analysis of electrocardiograms - A61B 5/352: Detecting R peaks, e.g. for synchronising diagnostic apparatus; Estimating R-R interval - A61B 5/7203: {for noise prevention, reduction or removal} - A61B 5/7221: {Determining signal validity, reliability or quality (preventing, reducing or removing noise induced by motion artefacts A61B5/7207; noise originating from a therapeutic or surgical apparatus A61B5/7217)} - A61B 5/021: Measuring pressure in heart or blood vessels - A61B 5/7264: {Classification of physiological signals or data, e.g. using neural networks, statistical classifiers, expert systems or fuzzy systems} - A61B 5/7282: {Event detection, e.g. detecting unique waveforms indicative of a medical condition (cough events A61B5/0823; seizures A61B5/4094; sleep apnoea A61B5/4818)} - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) ## Abstract The invention in at least one embodiment includes a method for providing a beat determination based on signals from a plurality of medical sensors in substantially real time, said method including: receiving in at least two analysis modules at least one signal (including an ECG signal and/or a pulse signal) from at least one medical sensor such that at least one analysis module receives one ECG signal and at least one analysis module receives one pulse signal; in each analysis module processing one signal through a plurality of detection algorithm modules to produce at least one quantitative decision, fusing the quantitative decisions together with a fusion module, and outputting at least one detected peak from the fusion module to an aggregation module; and producing from the aggregation module a series of detected peaks based on detected peaks received from the analysis modules. In a further embodiment, the detected peaks produced by the aggregation module are used to determine heart rate variability/complexity. At least one embodiment includes a system for performing any of the above methods. ## Claims ### Claim 1 A method for providing a beat determination based on signals from a plurality of medical sensors attached to one patient in substantially real time, said method comprising: receiving in at least two analysis modules at least one signal from at least one medical sensor, wherein the signal includes at least one of an ECG signal and a pulse signal such that at least one analysis module receives the one ECG signal and at least one analysis module receives the one pulse signal; in each analysis module processing the one signal through a plurality of detection algorithm modules with each detection algorithm module producing at least one quantitative decision, fusing the quantitative decisions from the detection algorithm modules together with a fusion module, and outputting at least one detected peak from the fusion module to an aggregation module in communication with the at least two analysis modules; and producing from the aggregation module a series of detected peaks representing heartbeats of the patient based on a series of detected peaks received from the analysis modules. ### Claim 2 (depends on 1) The method according to claim 1, wherein producing the series of detected peaks is further based on a beat signal quality index for each analysis module with the analysis module with the highest beat signal quality index being selected to supply the detected peaks for output by the aggregation module. ### Claim 3 (depends on 2) The method according to claim 2, wherein the beat signal quality index equals the beats detected by that analysis module over a predetermined time period divided by an average of the total number of beats detected by all of the analysis modules over the predetermined time period. ### Claim 4 (depends on 1) The method according to claim 1, wherein fusing the quantitative decisions together includes receiving quantitative decisions in a buffer of the fusion module from the decision algorithm modules in communication with the fusion module; determining whether quantitative decisions have been received from all of the decision algorithm modules; determining whether a most recently received quantitative decision is a second consecutive decision from one detection algorithm module; when either determination is true, fusing the received quantitative decisions, and determining an existence of a peak and outputting any peak that exists; and when neither determination is true, waiting for the next quantitative decision to be received from the detection algorithm modules. ### Claim 5 (depends on 4) The method according to claim 4, wherein fusing the quantitative decisions occurs after elapse of a refractory period after the last peak is determined to exist. ### Claim 6 (depends on 1) The method according to claim 1, wherein each detection algorithm module pre-processes the one signal to at least one of filter the signal and extract features from the signal to provide at least one processed signal, and analyzes the at least one processed signal to detect whether a beat is present in the processed signal. ### Claim 7 (depends on 6) The method according to claim 6, wherein at least one analysis module includes at least two detection algorithm modules that share at least one processed signal. ### Claim 8 (depends on 1) The method according to claim 1, wherein aggregating by the aggregation module includes receiving detected peaks in a buffer from the analysis modules; determining whether detected peaks have been received from all of the analysis modules; determining whether a most recent received detected peak is a second consecutive detected peak from one analysis module; when either determination is true, fusing the received detected peaks, and determining an existence of a peak and outputting any peak that exists; and when neither determination is true, waiting for the next detected peak to be received from the analysis modules. ### Claim 9 (depends on 8) The method according to claim 8, wherein fusing the received detected peaks by the fusion module includes analyzing the detected peaks using centroid analysis to detect output agreement. ### Claim 10 (depends on 9) The method according to claim 9, wherein output agreement is based on K-nearest neighbor. ### Claim 11 (depends on 1) The method according to claim 1, further comprising: receiving the series of detected peaks from the aggregation module into a heart rate complexity module; determining heart rate complexity by the heart rate complexity module based on the received detected peaks; and triggering an alarm when the heart rate complexity is outside a predetermined range. ### Claim 12 (depends on 11) The method according to claim 11, wherein the heart rate complexity based on an entropy measure. ### Claim 13 (depends on 1) The method according to claim 1, further comprising selecting the analysis module with a highest best signal quality index using a signal validation model. ### Claim 14 (depends on 1) The method according to claim 1, wherein the receiving analysis module is selected based on the detection algorithm modules present in the receiving analysis module being configured to process the at least one signal. ### Claim 15 (depends on 1) The method according to claim 1, wherein each detection algorithm module is configured to use different logic to detect a beat in the input signal as the quantitative decision. ### Claim 16 (depends on 1) The method according to claim 1, wherein the plurality of detection algorithm modules in each analysis module numbers at least four. ### Claim 17 (depends on 1) The method according to claim 1, wherein the plurality of medical sensors includes at least one ECG lead and a pulse oximeter. ### Claim 18 A method for providing a beat determination based on signals from a plurality of medical sensors attached to one patient in substantially real time, said method comprising: receiving in at least two analysis modules at least one signal from at least one medical sensor, wherein the signal includes at least one of an ECG signal and a pulse signal such that at least one analysis module receives the one ECG signal and at least one analysis module receives the one pulse signal; in each analysis module processing the one signal through a plurality of detection algorithm modules with each detection algorithm module producing at least one quantitative decision, fusing the quantitative decisions from the detection algorithm modules together with a fusion module, and outputting at least one detected peak from the fusion module to an aggregation module in communication with the at least two analysis modules; and producing from the aggregation module a series of detected peaks representing heartbeats of the patient based on a series of detected peaks received from the analysis module having a highest beat signal quality index for each analysis module with the analysis module with the highest best signal quality index being selected to supply the detected peaks for output by the aggregation module, and wherein the beat signal quality index equals the beats detected by that analysis module over a predetermined time period divided by an average of the total number of beats detected by all of the analysis modules over the predetermined time period. ### Claim 19 (depends on 18) The method according to claim 18, wherein fusing the quantitative decisions together includes receiving quantitative decisions in a buffer of the fusion module from the decision algorithm modules in communication with the fusion module; determining whether quantitative decisions have been received from all of the decision algorithm modules; determining whether a most recent received quantitative decision is a second consecutive decision from one detection algorithm module; when either determination is true, fusing the received quantitative decisions, and determining an existence of a peak and outputting any peak that exists; and when neither determination is true, waiting for the next quantitative decision to be received from the detection algorithm modules, fusing the quantitative decisions occurs after elapse of a refractory period after the last peak is determined to exist, each detection algorithm module pre-processes the one signal to at least one of filter the signal and extract features from the signal to provide at least one processed signal, analyzes the at least one processed signal to detect whether a beat is present in the processed signal, and at least two detection algorithm modules in at least one of the at least two analysis modules share at least one processed signal. ### Claim 20 A computer program product for detecting peaks in a plurality of biomedical signals, the computer program product comprising: a computer readable storage medium having encoded thereon: first program instructions executable by a processor to cause the processer to receive a plurality of biomedical signals originating from a plurality of medical sensors; second program instructions executable by a processor to cause the processer to assign each signal to a particular analysis module based on a type of signal that the signal is; third program instructions executable by a processor to cause the processer to use each analysis module to analyze one signal with a plurality of algorithms; fourth program instructions executable by a processor to cause the processer to use each analysis module to fuse the outputs of the plurality of algorithms to provide an output; fifth program instructions executable by a processor to cause the processer to select the highest quality output from the plurality of analysis modules; and sixth program instructions executable by a processor to cause the processer to use the selected output to determine at least one of heart rate complexity and heart rate variability.