Resmed Sensor Technologies Limited

Niall Fox

Conor Joseph Heneghan

Philip De Chazal

Conor M Hanley

Alberto Zaffaroni

Graeme Alexander Lyon

Redmond Shouldice

Stephen McMahon

Steven Paul Farrugia

Klaus Henry Schindhelm

Michael Waclaw Colefax

Stephen James Redmond

Faizan Javed

Emer O'Hare

Roxana Tiron

Rami Khushaba

Patrick Celka

Damien O'Rourke

Conor Heneghan

Anna Rice

Stephen Mcmahon

Stephen Dodd

Niall O'Mahony

Tony Fagan

Niall O'MAHONY

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.

Apparatus, system, and method for detecting physiological movement from audio and multimodal signals

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.

Apparatus, system, and method for monitoring physiological signs

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.

Systems and methods for categorizing and/or characterizing a user interface

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.

Sleep status detection for apnea-hypopnea index calculation

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.

Systems and methods for detecting rainout in a respiratory therapy system

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.

Systems and methods for identifying a user interface

Disclosed is a cardio-pulmonary health monitoring apparatus. The apparatus comprises a contactless motion sensor configured to generate one or more movement signals representing bodily movement of a patient during a monitoring session; a processor; and a memory storing program instructions configured to cause the processor to carry out a method of processing the one or more movement signals. The method comprises extracting one or more sleep disordered breathing features from the one or more movement signals, and predicting whether a clinical event is likely to occur during a predetermined prediction horizon based on the one or more sleep disordered breathing features.

Method and apparatus for monitoring cardio-pulmonary health

An apparatus, system, and method for the measurement, aggregation and analysis of data collected using non-contact or minimally-contacting sensors provides quality of life parameters for individual subjects, particularly in the context of a controlled trial of interventions on human subjects (e.g., a clinical trial of a drug, or an evaluation of a consumer item such as a fragrance). In particular, non-contact or minimal-contact measurement of quality-of-life parameters such as sleep, stress, relaxation, drowsiness, temperature and emotional state of humans may be evaluated, together with automated sampling, storage, and transmission to a remote data analysis center. One component of the system is that the objective data is measured with as little disruption as possible to the normal behavior of the subject. The system can also support behavioral and pharmaceutical interventions aimed at improving quality of life.

Contactless and minimal-contact monitoring of quality of life parameters for assessment and intervention

Systems and methods for monitoring quality of life parameters using non-contact sensors

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Tullamore, Ireland

Niall Fox