Respiratory cycle onset detection

A method comprising:

• providing a machine learning model trained to provide an estimated respiratory waveform based on one or more features of heart pulse samples;
• receiving, from a wearable physiological monitor worn by a user, pulse data including a plurality of heart pulse samples of the user during a time window;
• receiving accelerometer data from the wearable physiological monitor during the time window;
• extracting the one or more features from the pulse data;
• obtaining the estimated respiratory waveform for the user during the time window with the machine learning model based on the extracted features;
• and
• calculating a plurality of respiratory onsets for the user during the time window based on a plurality of local extrema of the estimated respiratory waveform for the user and local extrema determined from the accelerometer data obtained from the wearable physiological monitor during the time window.

A computer program product comprising executable code embodied in a non-transitory computer readable medium that, when executing on one or more computing devices, performs the steps of:

• receiving, from a wearable physiological monitor worn by a user, pulse data including a plurality of heart pulse samples of the user during a time window;
• mapping the pulse data into a feature space, wherein the feature space encodes individual heart pulse samples according to respiratory cycle stage;
• generating a first estimated respiratory waveform of the user during the time window from the pulse data mapped to the feature space;
• and
• calculating a plurality of respiratory onsets for the user during the time window based on a plurality of local extrema of the first estimated respiratory waveform.

A system comprising:

• a wearable physiological monitor configured to acquire pulse data from a user during a time window, the pulse data including a plurality of heart pulse samples of the user during the time window;
• and
• one or more processors configured to:
• map the pulse data into a feature space, wherein the feature space encodes individual heart pulse samples according to respiratory cycle stage,
• generate a first estimated respiratory waveform of the user during the time window from the pulse data mapped to the feature space, and
• calculate a plurality of respiratory onsets for the user during the time window based on a plurality of local extrema of the first estimated respiratory waveform.