ResMed Sensor Technologies Limited

A system includes a memory device storing machine-readable instructions and a control system including one or more processors configured to execute the machine-readable instructions to receive initial physiological data associated with a user, determine, based at least in part on initial physiological data, an initial sleepiness level for the user, prompt the user, via an electronic device, to perform a first activity, receive subsequent physiological data associated with the user, determine, based at least in part on the subsequent physiological data, a subsequent sleepiness level for the user, and determine a first activity score based at least in part on the initial sleepiness level and the subsequent sleepiness level, the first activity score being indicative of an effectiveness of the first activity in modifying the sleepiness of the user.

Disclosed is a method of managing risk, of a subject, of suffering an adverse condition relating to a physiological system of the subject. The method includes a. providing a wearable acoustic sensor, b. providing a data processor, and c. causing the processor to i. monitor the output from the sensor, ii. apply a predictive numerical model to generate a prediction, iii. compare the prediction with the sensor output, and iv. determine a response on the basis of the comparison.

Methods and devices provide physiological movement detection, such as gesture, breathing, cardiac and/or gross body motion, with active sound generation such as for an interactive audio device. The processor may evaluate, via a microphone coupled to the interactive audio device, a sensed audible verbal communication. The processor may control producing, via a speaker coupled to the processor, a sound signal in a user's vicinity. The processor may control sensing, via a microphone coupled to the processor, a reflected sound signal. This reflected sound signal is a reflection of the generated sound signal from the vicinity or user. The processor may process the reflected sound, such as by a demodulation technique, to derive a physiological movement signal. The processor may generate, in response to the sensed audible verbal communication, an output based on an evaluation of the derived physiological movement signal.

Methods and devices provide physiological movement detection with active sound generation. In some versions, a processor may detect breathing and/or gross body motion. The processor may control producing, via a speaker coupled to the processor, a sound signal in a user's vicinity. The processor may control sensing, via a microphone coupled to the processor, a reflected sound signal. This reflected sound signal is a reflection of the sound signal from the user. The processor may process the reflected sound, such as by a demodulation technique. The processor may detect breathing from the processed reflected sound signal. The sound signal may be produced as a series of tone pairs in a frame of slots or as a phase-continuous repeated waveform having changing frequencies (e.g., triangular or ramp sawtooth). Evaluation of detected movement information may determine sleep states or scoring, fatigue indications, subject recognition, chronic disease monitoring/prediction, and other output parameters.

Methods and devices provide physiological movement detection with active sound generation. In some versions, a processor may detect breathing and/or gross body motion. The processor may control producing, via a speaker coupled to the processor, a sound signal in a user's vicinity. The processor may control sensing, via a microphone coupled to the processor, a reflected sound signal. This reflected sound signal is a reflection of the sound signal from the user. The processor may process the reflected sound, such as by a demodulation technique. The processor may detect breathing from the processed reflected sound signal. The sound signal may be produced as a series of tone pairs in a frame of slots or as a phase-continuous repeated waveform having changing frequencies (e.g., triangular or ramp sawtooth). Evaluation of detected movement information may determine sleep states or scoring, fatigue indications, subject recognition, chronic disease monitoring/prediction, and other output parameters.

Methods and devices provide physiological movement detection, such as breathing, cardiac and/or gross body motion, with active sound generation using electronic processing device(s). The processor may control producing, via a speaker coupled to the processor, a sound signal in a user's vicinity. The processor may control sensing, via a microphone coupled to the processor, a reflected sound signal. This reflected sound signal is a reflection of the sound signal from the vicinity or user. The processor may process the reflected sound, such as by a demodulation technique. The sound signal may be produced as a dual tone frequency modulation continuous wave signal. Evaluation of detected movement information may determine sleep states or scoring, fatigue indications, subject recognition, chronic disease monitoring/prediction, and other output parameters.

Methods and devices provide physiological movement detection with active sound generation. In some versions, a processor may detect breathing and/or gross body motion. The processor may control producing, via a speaker coupled to the processor, a sound signal in a user's vicinity. The processor may control sensing, via a microphone coupled to the processor, a reflected sound signal. This reflected sound signal is a reflection of the sound signal from the user. The processor may process the reflected sound, such as by a demodulation technique. The processor may detect breathing from the processed reflected sound signal. The sound signal may be produced as a series of tone pairs in a frame of slots or as a phase-continuous repeated waveform having changing frequencies (e.g., triangular or ramp sawtooth). Evaluation of detected movement information may determine sleep states or scoring, fatigue indications, subject recognition, chronic disease monitoring/prediction, and other output parameters.

Methods and apparatus provide monitoring of a sleep disordered breathing state of a person such as for screening. One or more sensors may be configured for non-contact active and/or passive sensing. The processor(s) ( 7304, 7006 ) may extract respiratory effort signal(s) from one or more motion signals generated by active non-contact sensing with the sensor(s). The processor(s) may extract one or more energy band signals from an acoustic audio signal generated by passive non-contact sensing with the sensor(s). The processor(s) may assess the energy band signal(s) and/or the respiratory efforts signal(s) to generate intensity signal(s) representing sleep disorder breathing modulation. The processor(s) may classify feature(s) derived from the one or more intensity signals to generate measure(s) of sleep disordered breathing. The processor may generate a sleep disordered breathing indicator based on the measure(s) of sleep disordered breathing. Some versions may evaluate sensing signal(s) to generate indication(s) of cough event(s) and/or cough type.

A method and system for determining a positional sleep disordered breathing (pSDB) status associated with a respiratory device user is disclosed. Airflow data associated with the user is received. The airflow data is analyzed to identify a first time period of suspected arousal and a second time period of suspected arousal. A first time section between the identified first time period and the identified second time period is determined. The airflow data associated with the determined first time section is analyzed to identify (i) an indication of one or more respiratory events and/or (ii) an indication of one or more therapy events. Based at least in part on the (i) identified indication of one or more respiratory events and/or (ii) identified indication of one or more therapy events, the pSDB status of the user is determined, where the pSDB status is indicative of whether or not the user has pSDB.

Methods and devices provide physiological movement detection, such as breathing, cardiac and/or gross body motion, with active sound generation using electronic processing device(s). The processor may control producing, via a speaker coupled to the processor, a sound signal in a user's vicinity. The processor may control sensing, via a microphone coupled to the processor, a reflected sound signal. This reflected sound signal is a reflection of the sound signal from the vicinity or user. The processor may process the reflected sound, such as by a demodulation technique. The sound signal may be produced as a dual tone frequency modulation continuous wave signal. Evaluation of detected movement information may determine sleep states or scoring, fatigue indications, subject recognition, chronic disease monitoring/prediction, and other output parameters.