Techniques are disclosed for detecting arrhythmia episodes for a patient. A medical device may receive one or more sensor values indicative of motion of a patient. The medical device may determine, based at least in part on the one or more sensor values, an activity level of the patient. The medical device may determine a heart rate threshold for triggering detection of an arrhythmia episode based at least in part on the activity level of the patient. The medical device may determine whether to trigger detection of the arrhythmia episode for the patient based at least in part on comparing a heart rate of the patient with the heart rate threshold. The medical device may, in response to triggering detection of the arrhythmia episode, collect information associated with the arrhythmia episode.

A method is provided that includes determining a quality of a data portion of an input sensor data stream based, at least in part, on data of a first data type and determining between, at least, generation of two or more streams of a second, different data type including at least one synthesised data stream of the second data type. Determining between generation of two or more streams of a second, different data type is based, at least in part, on the determined quality. The synthesis is based, at least in part, on the data of the first data type. The method further includes causing generation of at least one stream of the second, different data type based, at least in part, on the determination between generation of two or more streams of the second, different data type.

The present invention provides an apparatus for protecting dental patient hearing through noise reduction, the apparatus comprising: a main body portion provided in a form that can be mounted on both ears of a user; a microphone module that is provided on one side of the main body portion and collects external sound signals generated from the outside; a noise filter module that is built in the main body portion and filters the external sound signals to block or reduces noise signals included in the external sound signals; and a speaker module that is built in the main body portion and provided on the other side of the main body portion corresponding to the ears of the user, and that outputs sound signals filtered by the noise filter module.

The exemplified methods and systems facilitate the use, for diagnostics, monitoring, or treatment, of one or more PPG waveform-based features or parameters determined from biophysical signals such as photoplethysmography signals that are acquired non-invasively from surface sensors placed on a patient while the patient is at rest. PPG waveform-based features or parameters may include PPG waveform features or parameters, VPG waveform features or parameters, and/or APG waveform features or parameters. The PPG waveform-based features or parameters can be used in a model or classifier to estimate metrics associated with the physiological state of a patient, including the presence or non-presence of a disease, medical condition, or an indication of either. The estimated metric may be used to assist a physician or other healthcare provider in diagnosing the presence or non-presence and/or severity and/or localization of diseases or conditions or in the treatment of said diseases or conditions.

A live subject tissue detection device includes a light source configured to emit light onto the tissue of a subject, a photodetector configured to receive light reflected from the tissue and light reflected from the blood flow, wherein the light reflected from the blood flow has a Doppler shift relative to the light reflected from the tissue, and generate a high frequency Doppler signal based on the Doppler shift, a detection circuitry configured to receive the high frequency Doppler signal from the photodetector and convert the high frequency Doppler signal into a low frequency signal, and at least one processor configured to compute parameters of the low frequency signal, compare the parameters of the low frequency signal to respective reference values, and determine a presence of live tissue based on the comparison.

A motion data processing method and a motion monitoring system provided in the present disclosure may process an electromyography (EMG) signal in the frequency domain or time domain to identify an abnormal signal in the EMG signal, such as an abrupt signal, a missing signal, a saturation signal, an oscillation signal, etc. caused by a high-pass filtering algorithm. The motion data processing method and the motion monitoring system may further perform a data sampling operation on the EMG signal through a data sampling algorithm, and predict data corresponding to the time point when the abnormal signal appears based on the sampling data, so as to obtain prediction data, and replace the abnormal signal by using the prediction data to correct the abnormal signal. The motion data processing method and the motion monitoring system may not merely accurately identify the abnormal signal, but further correct the abnormal signal, so that the corrected data may be more in line with an actual motion of a user, thereby improving user experience.

A method including the steps of receiving a first signal sensed from a patient, receiving a first physiological signal sensed from the patient, and processing the first signal based at least on the first physiological signal to obtain a second signal that is a measurement of the patient's Heart Rhythm.

A method for detecting cardiac arrhythmia based on a photoplethysmographic (PPG) signal is provided. The method includes: receiving a PPG signal and a motion signal corresponding to a motion made by a user; extracting PPG signal segments and motion signal segments corresponding to a time period from the PPG signal and the motion signal, respectively, at every time period; filtering out motion artifact noise in the PPG signal segments according to the PPG signal segments and the motion signal segments, and converting the PPG signal segments and the motion signal segments into PPG spectrum diagrams and motion spectrum diagrams, respectively; obtaining an estimated heart rate according to the PPG spectrum diagrams and the motion spectrum diagrams; and determining whether cardiac arrhythmia is present based on the filtered PPG signal segments and the estimated heart rate.

A device for monitoring a health parameter in a person is disclosed. The device includes a semiconductor substrate, at least one transmit antenna configured to transmit millimeter range radio waves over a 3D space below the skin surface of a person, multiple receive antennas configured to receive radio waves, the received radio waves including a reflected portion of the transmitted radio waves, wherein the semiconductor substrate includes circuits for processing signals received on the multiple receive antennas, wherein processing signals includes mixing signals of two different frequencies, and wherein the semiconductor substrate includes at least one output configured to output a signal that corresponds to a health parameter of a person in response to received radio waves.

A bed comprises substrate support members, each including a load bearing and a base configured to provide contact with a floor. The load bearing member is configured to move vertically relative to the base, while the base and the load bearing member are configured to fit together to maintain lateral alignment of the base and the load bearing member. A load sensor is positioned between the base and the load bearing member, the load bearing member configured to transmit a load from the substrate to the load sensor. A printed circuit board is in communication with the load sensor. A controller is in communication with the printed circuit board of each substrate support member and is configured to receive and process data output by the printed circuit boards.