Abstract: 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.

Abstract: A method includes generating acoustic data representative of at least one or more reflections of an acoustic signal. The one or more reflections are indicative of a length and/or a diameter of a conduit coupled to a respiratory therapy device. The method further includes analyzing the acoustic data to determine the length and/or diameter of the conduit. In some cases, analyzing the acoustic data includes determining a resonant frequency of the conduit, and determining the length of the conduit based at least in part on the resonant frequency. In some cases, analyzing the acoustic data includes comparing the acoustic data to predetermined sets of acoustic data that each correspond to a known length and/or diameter of the conduit, and selecting one of the predetermined sets of acoustic data that best matches the generated acoustic data. The selected set of acoustic data corresponds to the length and/or diameter of the conduit.

Abstract: 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.

Abstract: A method for analyzing physical features of an individual comprises directing an acoustic signal toward a mouth of the individual, receiving a reflected acoustic signal from the interior of the mouth of the individual, generating a structural profile of at least the interior of the mouth of the individual based at least in part on the reflected acoustic signal, and causing an action to be performed in response to generating the structural profile. The acoustic signal is configured to reflect off at least a portion of the interior of the mouth of the individual. The reflected acoustic signal is indicative of structural characteristics of the mouth of the individual. The structural profile can also be based on image data associated with the exterior of the head and neck of the individual, and image data associated with the interior of the mouth of the individual.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A system monitors fatigue of a user. The system (100) may include one or more data sources, such as a non-obtrusive sleep sensor, configured to generate objective sleep measures of the user. The system may also include a fatigue monitoring module, which may be configured to generate an assessment, such as in one or more processors, of the fatigue state of the user based on the data from the one or more data sources.

Abstract: Methods and apparatus provide physiological movement detection, such as gesture, breathing, cardiac and/or gross motion, such as with sound, radio frequency and/or infrared generation, by electronic devices such as vehicular processing devices. The electronic device in a vehicle may, for example, be any of an audio entertainment system, a vehicle navigation system, and a semi-autonomous or autonomous vehicle operations control system. One or more processors of the device, may detect physiological movement by controlling producing sensing signal(s) in a cabin of a vehicle housing the electronic device. The processor(s) control sensing, with a sensor, reflected signal(s) from the cabin. The processor(s) derive a physiological movement signal with the sensing signal and reflected signal and generate an output based on an evaluation of the derived physiological movement signal.

Abstract: A wearable device can automatically switch between modes of collecting sensor data when a docking event is detected between the wearable device and a docking device. In a first mode (e.g., when undocked), data can be collected using a first sensor configuration (e.g., a first set of sensors operating using a first set of sensing parameters). In a second mode (e.g., when docked), data can be collected using a second sensor configuration, which can include the use of one or more different sensors and/or the use of one or more different sensing parameters. The first mode may prioritize battery life, whereas the second mode may prioritize sensor data fidelity, such as by increasing sampling rates, using different sensors, and the like. Sensor data from the first and second modes can be used individually (e.g., to calibrate the other) and/or together (e.g., to determine physiological parameters).

Abstract: Devices, systems, and methods are disclosed. The devices, systems, and methods detect one or more parameters with respect to movement of a user, cardiac activity of the user, audio associated with the user, or a combination thereof during a sleep session of the user, process the one or more parameters to determine a sleep status of the user, the sleep status being at least one of awake, asleep, or a sleep stage; and calculate an apnea-hypopnea index for the user during the sleep session based, at least in part, on the sleep status.

Abstract: 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.

Abstract: A processing system includes methods to promote sleep. The system may include a monitor such as a non-contact motion sensor from which sleep information may be determined. User sleep information, such as sleep stages, hypnograms, sleep scores, mind recharge scores and body scores, may be recorded, evaluated and/or displayed for a user. The system may further monitor ambient and/or environmental conditions corresponding to sleep sessions. Sleep advice may be generated based on the sleep information, user queries and/or environmental conditions from one or more sleep sessions. Communicated sleep advice may include content to promote good sleep habits and/or detect risky sleep conditions. In some versions of the system, any one or more of a bedside unit 3000 sensor module, a smart processing device, such as a smart phone or smart device 3002, and network servers may be implemented to perform the methodologies of the system.

Abstract: Various implementations of the present disclosure are directed to systems and methods for characterizing a conduit coupled to a respiratory therapy device in a respiratory therapy system. The method includes generating a first airflow from the respiratory therapy device to the conduit by operating a motor of the respiratory therapy device at a first revolutions per minute. The method further includes receiving a first airflow parameter data associated with the first airflow, wherein the first airflow parameter data has a first pair of two distinct airflow parameter values. The method further includes determining a first relationship between the first airflow parameter data and the conduit, and characterizing the conduit based on the first relationship.

Abstract: Devices, systems, and methods are disclosed. The devices, systems, and methods detect one or more parameters with respect to movement of a user, cardiac activity of the user, audio associated with the user, or a combination thereof during a sleep session of the user; process the one or more parameters to determine a sleep status of the user, the sleep status being at least one of awake, asleep, or a sleep stage; and calculate an apnea-hypopnea index for the user during the sleep session based, at least in part, on the sleep status.

Abstract: A system monitors fatigue of a user. The system (100) may include one or more data sources, such as a non-obtrusive sleep sensor, configured to generate objective sleep measures of the user. The system may also include a fatigue monitoring module, which may be configured to generate an assessment, such as in one or more processors, of the fatigue state of the user based on the data from the one or more data sources.

Abstract: Methods and apparatus detect events of sleep disordered breathing from an input audio signal such as from a sound sensor. A processor may be configured to receive the audio signal that represents sounds of a user during a period of sleep. The processor determines reliable respiration epochs from the audio, such as on a frame-by-frame basis, that include periods of audible breathing and/or snoring. The processor detects presence of a sleep disordered breathing events, such as hypopnea, apnea, apnea snoring or modulated breathing, in the reliable respiration epoch(s) and generates output to indicate the detected event(s). Optionally, the apparatus may serve as a cost-effective screening device such as when implemented as a processor control application for a mobile processing device (e.g., mobile phone or tablet).

Abstract: 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.

Abstract: A method of detecting rainout in a respiratory therapy system that includes a conduit fluidly coupled to a user interface comprises generating, via at least one microphone, acoustic data representative of noise associated with the respiratory therapy system. The method further comprises analyzing the acoustic data to detect a presence of liquid in the respiratory therapy system. The method further comprises causing an action to be performed, based on the detected presence of the liquid.