# US 10,863,949 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 10,863,949 B2 - Document ID: US10863949B2 - Status: Granted - Kind: B2 - Application number: 14/374,761 - Filed: 2013-01-25 - Published: 2015-02-05 - Granted: 2020-12-15 - 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/US10863949B2 ## 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 respiration signal generated by a respiration sensor, the method comprising: accessing data representative of the respiration signal, the accessed data comprising respiratory data; assessing the accessed data to detect apnea and/or hypopnea events; evaluating the respiratory data directly following the detected events to estimate a shape feature representing a change in the respiratory data; generating a cycle length histogram based on the detected events, wherein the cycle length histogram includes a plurality of bins associated with a plurality of cycle lengths, each cycle length of the plurality being determined from the detected apnea and/or hypopnea events; detecting an incident of Cheyne-Stokes respiration based on the cycle length histogram and the estimated shape feature, wherein detecting the incident of Cheyne-Stokes respiration comprises calculating power over a combination of bins covering a select set of cycle lengths; 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 each of the plurality of bins has a midpoint and a bin width. ### Claim 3 (depends on 1) The method of claim 1, wherein the plurality of bins are evenly spaced. ### Claim 4 (depends on 1) The method of claim 1 wherein assessing the accessed data to detect apnea and/or hypopnea events comprises determining a duration of each event. ### Claim 5 (depends on 1) The method of claim 1, wherein the shape feature represents at least one of a rise and a fall of a breathing drive of a patient. ### Claim 6 (depends on 1) The method of claim 1, wherein the shape feature is a jump feature. ### Claim 7 (depends on 6) The method of claim 6, 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. ### Claim 8 (depends on 7) The method of claim 7, further comprising scaling the gradient between the first peak and the second peak. ### Claim 9 (depends on 5) The method of claim 5, wherein the shape feature is estimated by fitting an approximating function to the respiratory data. ### Claim 10 (depends on 1) The method of claim 1, wherein the respiratory data comprises values of respiratory flow peaks or values of tidal volumes. ### Claim 11 A method implemented by a processor for detecting a presence of Cheyne-Stokes respiration from a respiration signal generated by a respiration sensor, the method comprising: accessing respiratory flow data representative of the respiration signal; assessing the accessed respiratory flow data to detect apnea and/or hypopnea events; determining a cycle length histogram based on the detected events, wherein the cycle length histogram includes a plurality of bins associated with a plurality of cycle lengths, each cycle length of the plurality being determined from the detected apnea and/or hypopnea events; evaluating peaks in the flow data directly following the detected events to estimate a shape feature representing a change in the peaks of the flow data; detecting an incident of Cheyne-Stokes respiration based on the cycle length histogram and the shape feature, wherein detecting the incident of Cheyne Stokes respiration comprises calculating power over a combination of bins covering a select set of cycle lengths; and responding to the detecting of an incident of Cheyne-Stokes respiration, the responding comprising controlling an adjustment to a therapeutic pressure delivered by a respiratory treatment apparatus. ### Claim 12 (depends on 11) The method of claim 11, further comprising normalizing the cycle length histogram and the shape feature by converting them into a probability space with a range of values between 0 and 1. ### Claim 13 (depends on 11) The method of claim 11, wherein assessing the accessed respiratory flow data to detect apnea and/or hypopnea events comprises calculating duration of at least one apneic period and at least one cycle length and further comprising calculating a duty cycle based on the duration of the at least one apneic period and the at least one cycle length. ### Claim 14 (depends on 11) The method of claim 11, wherein detecting the incident of Cheyne-Stokes respiration comprises determining a Cheyne-Stokes respiration probability using the shape feature, cycle length and the power. ### Claim 15 (depends on 14) The method of claim 14, further comprising determining an overall Cheyne-Stoke respiration probability over an entire sleep period by combining weighted Cheyne-Stokes respiration probability for multiple selected periods. ### Claim 16 (depends on 11) The method of claim 11, wherein the shape feature represents at least one of a rise and a fall of a breathing drive of a patient. ### Claim 17 (depends on 1) The method of claim 1 wherein detecting of the incident of Cheyne-Stokes respiration comprises applying the estimated shape feature and the cycle length histogram to a classifier implemented by the processor. ### Claim 18 (depends on 1) The method of claim 1 wherein the controlling an adjustment of a therapeutic pressure delivered by a respiratory treatment apparatus further comprises automatically controlling a blower of a flow generator in response to the detecting of the incident of Cheyne-Stokes respiration that is based on the cycle length histogram and the estimated shape feature. ### Claim 19 (depends on 1) The method of claim 1 wherein calculating power evaluates a histogram power transformation function that determines a first count of a first bin of the plurality of bins as a maximum count and a second count of a second bin of the plurality of bins as a second highest count, and adds the first count and second count when midpoints of first bin and the second bin are each within a predefined range. ### Claim 20 (depends on 19) The method of claim 19 wherein the histogram power transformation function determines a square root of an addition of a square of the first count and a square of the second count when a midpoint of the first bin is within the predefined range and a midpoint of the second bin is outside the predefined range. ### Claim 21 (depends on 11) The method of claim 11 wherein detecting of the incident of Cheyne-Stokes respiration comprises applying the estimated shape feature and the cycle length histogram to a classifier implemented by the processor. ### Claim 22 (depends on 11) The method of claim 11 wherein the controlling the adjustment to a therapeutic pressure delivered by a respiratory treatment apparatus further comprises automatically controlling a blower of a flow generator in response to the detecting of the incident of Cheyne-Stokes respiration that is based on the cycle length histogram and the estimated shape feature. ### Claim 23 (depends on 11) The method of claim 11 wherein calculating power evaluates a histogram power transformation function that determines a first count of a first bin of the cycle length histogram as a maximum count and a second count of a second bin of the cycle length histogram as a second highest count, and adds the first count and second count when midpoints of first bin and the second bin are each within a predefined range. ### Claim 24 (depends on 23) The method of claim 23 wherein the histogram power transformation function determines a square root of an addition of a square of the first count and a square of the second count when a midpoint of the first bin is within the predefined range and a midpoint of the second bin is outside the predefined range. ### Claim 25 (depends on 1) The method of claim 1 wherein the responding further comprises generating and displaying an incident report upon a monitor. ### Claim 26 (depends on 11) The method of claim 11 wherein the response further comprises generating and displaying an incident report upon a monitor.