# US 11,992,344 B2 · Discrimination of cheyne stokes breathing patterns > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 11,992,344 B2 - Document ID: US11992344B2 - Status: Granted - Kind: B2 - Application number: 17/097,092 - Filed: 2020-11-13 - Published: 2021-05-06 - Granted: 2024-05-28 - Earliest claimed: 2012-01-27 - Assignees: ResMed Pty Ltd - Applicants: ResMed Pty Ltd - Inventors: Jeffrey Peter Armitstead; Dinesh Ramanan - Web page: https://patentgrep.com/patent/US11992344B2 ## CPC - 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 5/0816: {Measuring devices for examining respiratory frequency (measuring frequency of electric signals G01R23/00)} - A61B 5/0826: {Detecting or evaluating apnoea events (sleep apnoea A61B5/4818)} - A61B 5/087: Measuring breath flow - A61B 5/091: Measuring volume of inspired or expired gases, e.g. to determine lung capacity - A61B 5/7275: {Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor} - A61M 16/0003: {Accessories therefor, e.g. sensors, vibrators, negative pressure} - A61M 16/0069: {the speed thereof being controlled by respiratory parameters, e.g. by inhalation} - A61M 16/026: {specially adapted for predicting, e.g. for determining an information representative of a flow limitation during a ventilation cycle by using a root square technique or a regression analysis} - A61B 5/4818: {Sleep apnoea} - A61M 16/0666: {Nasal cannulas or tubing (devices for improving normal breathing through the nose A61F5/08; nose filters A62B23/06; outside holding devices A61M25/02)} - A61M 2016/003: {with a flowmeter} - A61M 2016/0033: {electrical} - A61M 2205/3303: Using a biosensor - A61M 2205/52: with memories providing a history of measured variating parameters of apparatus or patient - A61M 2230/005: Parameter used as control input for the apparatus - A61M 2230/205: partial oxygen pressure (P-O2) - A61M 2230/40: Respiratory characteristics - A61B: DIAGNOSIS; SURGERY; IDENTIFICATION (usefulness limited to only animals A61D) - A61M: DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY (introducing media into or onto the bodies of animals A61D7/00; means for inserting tampons A61F13/26; devices for administering food or medicines orally A61J; containers for collecting, storing or administering blood or medical fluids A61J1/05); DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY (surgery A61B; chemical aspects of surgical articles A61L); DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR {(Electrotherapy, e.g. producing anaesthesia by the use of alternating or intermittent currents A61N1/36021)} ## Abstract A method of a processor for detecting a presence of Cheyne-Stokes respiration from a respiration signal includes accessing data representative of a respiration signal. Data is assessed to detect apnea and/or hypopnea events. A cycle length histogram is determined based on the events and an incident of Cheyne-Stokes respiration is detected based on the cycle length histogram. ## Claims ### Claim 1 A method implemented by a processor for detecting a presence of Cheyne-Stokes respiration from a respiratory signal generated by a respiration sensor, the method comprising: accessing respiratory data representative of the respiratory signal; assessing the accessed respiratory data to detect apnea and/or hypopnea events; evaluating respiratory data directly following the detected events to estimate a jump feature representing a change in the respiratory data, wherein the jump feature is calculated by selecting a first peak of the respiratory data, selecting a second peak at a predetermined ratio of the first peak, and calculating a gradient between the first peak and the second peak; detecting an incident of Cheyne-Stokes respiration based on the jump feature; and responding to the detection of an incident of Cheyne-Stokes respiration, the responding comprising controlling an adjustment of a therapeutic pressure delivered by a respiratory treatment apparatus. ### Claim 2 (depends on 1) The method of claim 1, wherein evaluating the respiratory data comprises calculating inspiratory tidal volumes during at least a portion of time between two adjacent apnea and/or hypopnea events. ### Claim 3 (depends on 1) The method of claim 1, wherein evaluating the respiratory data comprises calculating a product of peak inspiratory flow data and inspiratory tidal volume and storing them in a morphology vector. ### Claim 4 (depends on 3) The method of claim 3, wherein evaluating the respiratory data further comprises computing a mean squared error between the morphology vector and an approximating function. ### Claim 5 (depends on 3) The method of claim 3, wherein evaluating the respiratory data comprises integrating the peak inspiratory flow data between apnea and/or hypopnea events and storing them in the morphology vector. ### Claim 6 (depends on 5) The method of claim 5, wherein evaluating the respiratory data further comprises computing a mean squared error between the morphology vector and an approximating function. ### Claim 7 (depends on 1) The method of claim 1, wherein the jump feature represents at least one of a rise and a fall of a breathing drive of a patient. ### Claim 8 (depends on 1) The method of claim 1, further comprising scaling the gradient between the first peak and the second peak. ### Claim 9 (depends on 1) The method of claim 1, wherein detecting the incident of Cheyne Stokes respiration comprises determining a Cheyne Stokes respiration probability using the jump feature. ### Claim 10 An apparatus for detecting a presence of Cheyne-Stokes respiration from a respiratory signal generated by a respiration sensor, the apparatus comprising: a memory for storing respiratory data associated with the respiratory signal; and a processor, coupled with the memory, the processor being configured to assess the respiratory data to detect apnea and/or hypopnea events; evaluate peaks in the respiratory data directly following the detected events to estimate a jump feature representing a change in the respiratory data, wherein the jump feature is calculated by selecting a first peak of the respiratory data, selecting a second peak at a predetermined ratio of the first peak, and calculating a gradient between the first peak and the second peak; detect an incident of Cheyne-Stokes respiration based on the jump feature; and generate a response to the detection of an incident of Cheyne-Stokes respiration, the response comprising an adjustment to therapeutic pressure delivered by a respiratory treatment apparatus. ### Claim 11 (depends on 10) The apparatus of claim 10, wherein the data associated with the respiratory signal comprises flow data and tidal volume data and the processor is further configured to: calculate peak inspiratory flow data and inspiratory tidal volume; and calculate a product of the peak inspiratory flow data and inspiratory tidal volume and storing them in a morphology vector. ### Claim 12 (depends on 11) The apparatus of claim 11, wherein the processor is configured to normalize the morphology vector by converting it into 0 to 1 probability space. ### Claim 13 (depends on 11) The apparatus of claim 11, wherein the processor is configured to evaluate the peaks in the flow data by computing a mean squared error between the morphology vector and an approximating function. ### Claim 14 (depends on 11) The apparatus of claim 11, wherein the processor is configured to evaluate the peaks in the flow data by integrating the flow data between apnea and/or hypopnea events and storing them in the morphology vector. ### Claim 15 (depends on 14) The apparatus of claim 14, wherein the processor is configured to evaluate the peaks in the flow data by computing a mean squared error between the morphology vector and an approximating function. ### Claim 16 (depends on 10) The apparatus of claim 10, wherein the jump feature represents at least one of a rise and a fall of a breathing drive of a patient. ### Claim 17 (depends on 10) The apparatus of claim 10, wherein the processor is configured to scale the gradient between the first peak and the second peak. ### Claim 18 (depends on 1) The method of claim 1, wherein the accessed respiratory data comprises values of respiratory flow. ### Claim 19 (depends on 1) The method of claim 1, wherein the accessed respiratory data comprises values of ventilation. ### Claim 20 (depends on 1) The method of claim 1, wherein the accessed respiratory data comprises values of tidal volume.