Abstract: A system for predicting adoption of a prescribed treatment plan by an individual includes a data repository, a memory storing instruction, and a control system to execute the instructions. The data repository is communicatively coupled to a network and includes a plurality of storage devices storing data. The control system receives at least a portion of the data stored in the data repository. The at least a portion of the data is associated with the individual. The control system uses the machine learning adoption prediction algorithm to process the received at least a portion of the data to determine a likelihood that the individual will adopt the prescribed treatment plan. Based at least in part on (i) the prescribed treatment plan and (ii) the determined likelihood that the individual will adopt the prescribed treatment plan, the control system generates a personalized treatment adoption plan for the individual.

Abstract: A method and apparatus monitors chronic disease state of a patient. The method may include extracting, in a processor, for each of a plurality of monitoring sessions, a respiratory feature from a respiratory signal indicative of the patient's respiration during the monitoring session, the respiratory signal derived from at least one sensor; and computing, in a processor, a stability measure of the patient for a monitoring session, the stability measure representing an indication of a change point having occurred at the monitoring session in a statistical distribution of the respiratory feature.

Abstract: Systems and methods are provided for a multi-modal sleep system comprising a data processor for operating in a plurality of operating modes. The data processor may detect at least one sensor providing data to the data processor and determine a sensor type associated with each of the at least one sensor. The data processor may select a mode of operation based on the determined sensor type of the detected at least one sensor and of each of the at least one sensor. A first of the plurality of operating modes may be selected in response to determining that the at least one detected sensor includes a first sensor type or combination of sensor types. The data processor may be configured to receive data from the at least one detected sensor and process the received data according to the selected mode of operation to output a characterization of a user's sleep.

Abstract: An apparatus, system, and method are disclosed for monitoring the motion, breathing, heart rate of humans in a convenient and low-cost fashion, and for deriving and displaying useful measurements of cardiorespiratory performance from the measured signals. The motion, breathing, and heart rate signals are obtained through a processing applied to a raw signal obtained in a non-contact fashion, typically using a radio-frequency sensor. Processing into separate cardiac and respiratory components is described. The heart rate can be determined by using either spectral or time-domain processing. The respiratory rate can be calculated using spectral analysis. The sensor, processing, and display can be incorporated in a single device which can be worn or held close to the body while exercising, or alternately placed in a fixed piece of exercise equipment at some distance form the body, and may also be integrated with other sensors, such as position locators.

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: Disclosed are methods, systems, and devices for providing a personalized humidification level. A control system receives, from a first sensor, one or more environmental parameters regarding conditions of the environment. The control system receives, from a second sensor, one or more physiological parameters associated with a user within the environment. The control system determines an action associated with a desired change in the humidity within the environment based, at least in part, on the one or more environmental parameters and the one or more physiological parameters. The control system causes, at least in part, a performance of the action associated with the change in the humidity in the environment based, at least in part, on moisture outputted by a humidifier module. The methods and devices perform the same functionality as the control system.

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 sensor may be configured to detect periodic limb movement in a sleeping person. The sensor may be a non-contact sensor, such as a radar motion sensor. The sensor may include a radio frequency transmitter for emitting radio frequency signals toward the person. The sensor may include a receiver for receiving reflected ones of the emitted radio frequency signals and processing the reflected ones of the emitted radio frequency signals to produce motion signal(s). A processor, such as one integrated with or coupled to the sensor, may evaluate the motion signals, such as in-phase and quadrature motion signals, and generate an indicator to identify occurrence of periodic limb movement in the motion signals based on the evaluation of the motion signals.

Abstract: A method for generating a three-dimensional model of a head including at least a portion of a face, comprising: obtaining a distance image of the head using a distance-measuring device having an imaging position, the distance image comprising for each of a two-dimensional array of distance pixels, a respective distance value indicating a distance from the measuring position to a corresponding point in a field of view of the distance-measuring device, the distance image including a face portion corresponding to the at least a portion of a face; estimating the position, relative to the imaging position, of a longitudinal axis of the model of the head based on the at least one dimension; based on the longitudinal axis, generating the three dimensional model of the head based on the position of the longitudinal axis.

Abstract: Systems and methods are disclosed for categorizing and/or characterizing a user interface. The systems and methods include generating acoustic data associated with an acoustic reflection of an acoustic signal, the acoustic reflection being indicative of, at least in part, one or more features of a user interface coupled to a respiratory therapy device via a conduit. The systems and methods further include analyzing the generated acoustic data. The systems and methods further include categorizing and/or characterizing the user interface based, at least in part, on the analyzed acoustic data.

Abstract: Systems and methods assist with managing a chronic disease of a user such as a chronic respiratory or cardiac disease. The system may include a physiological monitor adapted to be carried by the user and operative to sense a physiological parameter of the user by generating one or more signals. The system may include a management device operatively coupled with the physiological monitor to receive the signal(s) and derive the physiological parameter(s) of the user. The management device, such as with an included processor, may be configured to analyze the physiological and/or environmental parameters to detect a trigger pattern of the parameters, the trigger pattern indicative of a probable event of exacerbation of the chronic respiratory and/or cardiac condition. The management device may then generate automated responses based on the trigger pattern such as by providing instructions for activities and/or treatment for the chronic condition.

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: 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: An apparatus, system, and method for monitoring a person suffering from a chronic medical condition predicts and assesses physiological changes which could affect the care of that subject. Examples of such chronic diseases include (but are not limited to) heart failure, chronic obstructive pulmonary disease, asthma, and diabetes. Monitoring includes measurements of respiratory movements, which can then be analyzed for evidence of changes in respiratory rate, or for events such as hypopneas, apneas and periodic breathing. Monitoring may be augmented by the measurement of nocturnal heart rate in conjunction with respiratory monitoring. Additional physiological measurements can also be taken such as subjective symptom data, blood pressure, blood oxygen levels, and various molecular markers. Embodiments for detection of respiratory patterns and heart rate are disclosed, together with exemplar implementations of decision processes based on these measurements.

Abstract: Methods and apparatus monitor health by detection of sleep stage. For example, a sleep stage monitor (100) may access sensor data signals related to bodily movement and/or respiration movements. At least a portion of the detected signals may be analyzed to calculate respiration variability. The respiration variability may include one or more of variability of respiration rate and variability of respiration amplitude. A processor may then determine a sleep stage based on one or more of respiration variability and bodily movement, such as with a combination of both. The determination of sleep stages may distinguish between deep sleep and other stages of sleep, or may differentiate between deep sleep, light sleep and REM sleep. The bodily movement and respiration movement signals may be derived from one or more sensors, such as non-invasive sensor (e.g., a non-contact radio-frequency motion sensor or a pressure sensitive mattress).

Abstract: A method for generating a three-dimensional model of a head including at least a portion of a face, comprising: obtaining a distance image of the head using a distance-measuring device having an imaging position, the distance image comprising for each of a two-dimensional array of distance pixels, a respective distance value indicating a distance from the measuring position to a corresponding point in a field of view of the distance-measuring device, the distance image including a face portion corresponding to the at least a portion of a face; estimating the position, relative to the imaging position, of a longitudinal axis of the model of the head based on the at least one dimension; based on the longitudinal axis, generating the three dimensional model of the head based on the position of the longitudinal axis.

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.