Abstract: A wireless communications enabled memory card (100) has a card interface (104) for wired communicating with a medical device. The memory card has a non-volatile memory (106) for storing therapy data provided by the medical device. The memory card may have a Wi-Fi transceiver (110) for joining a Wi-Fi network. The memory card may receive authentication information for joining the network from the medical device via the card interface or from a wireless device via a direct Wi-Fi connection. After joining the Wi-Fi network, the memory card may transmit the therapy data to a remote server (130).

Abstract: 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.

Abstract: 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.

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: The disclosure provides methods for diagnosis or prediction of the likelihood of a subject experiencing obstructive sleep apnea, determined at least in part by measuring the degree of tongue fat in a subject using, e.g., thermal imaging, THz imaging or other multispectral imaging.

Abstract: A data gathering system (100) has at least one processor configured to perform a compression scheme for wireless transmission. The compression scheme may include amplitude reduction, where a difference between every two consecutive values of a plurality of values is computed and stored in an array. Additionally, the compression scheme may include bit packing, where outlier values are output in a first bit length, and remaining values are output in a second bit length, where the second bit length is determined so as to minimize a total memory cost for all values. Further, the system may store data recorded at different points in time in an array of data chunks, and wirelessly transmit the array of data chunks simultaneously.

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 (i) and (ii), cause the speaker to emit the sound to aid in masking the noise associated with the air leaking from the mask.

Abstract: A system and method for providing a unique signature for proprietary data. The proprietary data may be transmitted to multiple trusted parties. Each of the trusted parties will have proprietary data with a unique signature to that trusted party. The signature allows a user to determine the source of the proprietary data breach via the signature.

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 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 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 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: 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: 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: 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 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.