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 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: The present disclosure relates to a method for identifying a user interface. Flow data associated with air flowing in a respiratory therapy system is received. Acoustic data associated with the respiratory therapy system is received. The received flow data and the received acoustic data are analyzed. Based at least in part on the analysis, a mask type for the user interface is determined.

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 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 receiving data associated with a sleep session of a user. The method also includes determining that the user is experiencing or has experienced an event based at least in part on the data. The method also includes causing pressurized air to be directed from a respiratory device to a multi-compartment bladder in response to determining that the user is experiencing or has experienced the event to aid in modifying a position of a head of the user.

Abstract: An apparatus, system, and method monitors the motion, breathing, heart rate and sleep state of subjects, e.g., humans, in a convenient, non-invasive/non-contact, and low-cost fashion. More particularly, the motion, breathing, and heart rate signals are obtained through processing applied to a raw signal obtained in a non-contact fashion, typically using a radio-frequency sensor. Periods of sleep disturbed respiration, or central apnea can be detected through analysis of the respiratory signal. The mean heart rate, and derived information, such as the presence of cardiac arrhythmias can be determined from the cardiac signal. Motion estimates can be used to recognize disturbed sleep and periodic limb movements. The sleep state may be determined by applying a classifier model to the resulting streams of respiratory, cardiac and motion data. A means for display of the sleep state, respiratory, cardiac, and movement status may also be provided.

Abstract: A plurality of flow rate values associated with pressurized air directed to an airway of a user of a respiratory therapy system is received. A plurality of pressure values associated with the pressurized air directed to the airway of the user is received. A first time associated with a first breath of the user and a second time associated with a second breath of the user are identified. The plurality of flow rate values is filtered based at least in part on the identified first time and the identified second time. The filtering produces a subset of the plurality of flow rate values. An intentional leak characteristic curve for the respiratory therapy system is determined using at least two of the subset of the plurality of flow rate values and the corresponding pressure values for the at least two of the subset of the plurality of flow rate values.

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: Radio frequency motion sensors may be configured for operation in a common vicinity so as to reduce interference. In some versions, interference may be reduced by timing and/or frequency synchronization. In some versions, a master radio frequency motion sensor may transmit a first radio frequency (RF) signal. A slave radio frequency motion sensor may determine a second radio frequency signal which minimizes interference with the first RF frequency. In some versions, interference may be reduced with additional transmission adjustments such as pulse width reduction or frequency and/or timing dithering differences. In some versions, apparatus may be configured with multiple sensors in a configuration to emit the radio frequency signals in different directions to mitigate interference between emitted pulses from the radio frequency motion sensors.

Abstract: Methods and apparatus provide monitoring of coughing and/or a sleep disordered breathing state of a person. One or more sensors may be configured for non-contact active and/or passive sensing. The processor(s) 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 coughing and/or sleep disordered breathing.

Abstract: A method includes receiving physiological data associated with a user during a sleep session. The method also includes determining a sleep-wake signal for the user during the sleep session based at least in part on the received physiological data. The method also includes determining one or more sleep-related parameters for the user during the sleep session based at least in part on the sleep-wake signal. The method also includes determining that the user experienced insomnia during the sleep session based at least in part on at least one of the one or more sleep-related parameters. The method also includes identifying a type for the insomnia experienced by the user based at least in part on the one or more sleep-related 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: A system includes a respiratory device, a mask, a microphone, a speaker, and a control system. The respiratory device is configured to supply pressurized air. The mask is coupled to the respiratory device and configured to engage a user during a sleep session to aid in directing the supplied pressurized air to the user. The microphone is configured to generate audio data. The speaker is configured to emit sound. The control system is configured to analyze the audio data to determine if noise associated with air leaking from the mask is occurring. Responsive to (i) the analysis resulting in a determination that noise associated with air leaking from the mask is occurring, (ii) the respiratory device determining that air is leaking from the mask, or (iii) both, the speaker is caused to emit the sound to aid in masking the noise associated with the air leaking from the mask.

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: Method and apparatus obtain information about a patient and/or a respiratory therapy system that is configured to deliver respiratory therapy to the patient. The respiratory therapy system may include a flow generator configured to generate a supply of pressurized air along an air circuit to a patient interface. A sound signal representing a sound in the air circuit may be processed to obtain cepstrum data. A time series of delay estimates based on acoustic signatures of the cepstrum data may be generated. Each acoustic signature may represent a reflection of sound from a patient interface along the air circuit. Variation in the time series of delay estimates may be analysed. One or more output indicators based on the variation may be generated. The one or more output indicators may concern patient and/or system status.

Abstract: A sensor for motion or gesture sensing may be configured to emit radio frequency signals such as for pulsed range gated sensing. The sensor may include a radio frequency transmitter configured to emit the pulses and a receiver configured to receive reflected ones of the emitted radio frequency signals. The received pulses may be processed by a motion channel and/or a gesture channel. The gesture channel may produce signals for further processing for identification of one or more different motion gestures such as by calculating and evaluating features from any of the amplitude, phase and frequency of the output signals of the gesture channel. The sensing apparatus may optionally serve as a monitor for evaluating user activities, such as by counting activities. The sensor may optionally serve as a user control interface for many different devices by generating control signal(s) based on identification of one or more different motion gestures.

Abstract: Aspects of the of the disclosure relate to a non-contact physiological motion sensor and a monitor device that can incorporate use of the Doppler effect. A continuous wave of electromagnetic radiation can be transmitted toward one or more subjects and the Doppler-shifted received signals can be digitized and/or processed subsequently to extract information related to the cardiopulmonary motion in the one or more subjects. The extracted information can be used, for example, to determine apneic events and/or snoring events and/or to provide apnea or snoring therapy to subjects when used in conjunction with an apnea or snoring therapy device. In addition, methods of use are disclosed for sway cancellation, realization of cessation of breath, integration with multi-parameter patient monitoring systems, providing positive providing patient identification, or any combination thereof.

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: A sleep monitoring system includes an ECG device (2) and a respiration inductance plethysmogram (3) which monitor cardiac activity and physical (ribcage) respiration respectively and feed representative signals to a digital data processor. Operations (5-9) process the beat interval data, while in a second thread, operations (20-24) independently process the amplitude modulation of the ECG data caused by the respiratory motion of the subject. The inductance plethysmogram device (3) provides an input to the processor which represents respiration as directly monitored independently of the ECG. Operations (30-34) process this direct respiration data independently and in parallel, in a third thread. All extracted features are fed to a classifier which in step (10) combines selected combinations of features to make decisions in real time.