A plurality of modules are simultaneously positioned at locations that correspond to different angiosomes. Each of these modules has a front surface shaped and dimensioned for contacting a person's skin, a plurality of different-wavelength light sources aimed in a forward direction, and a plurality of light detectors aimed to detect light arriving from in front of the front surface. Each module is supported by a support structure (e.g., a strap or a clip) that is shaped and dimensioned to hold the front surface adjacent to the person's skin at a respective position. Perfusion in each of the angiosomes is monitored using these modules, and the surgeon can rely on this information to guide his or her intervention.

A method is provided that includes receiving an accelerometer signal from an accelerometer in a headphone configured to be mounted in a user's ear canal and filtering the accelerometer signal to extract a cardiac signal. The method further includes detecting a plurality of peaks in the cardiac signal and determining a cardiac rate of the user based on the detected plurality of peaks.

This document discusses, among other things, systems and methods to determine an alert state for each of a plurality of patients using received physiologic information, determine an event rate for the plurality of patients for a specific alert state, and adjust a composite HF risk determination for the plurality of patients using the determined event rate.

This document discusses, among other things, systems and methods to determine an alert state for each of a plurality of patients using received physiologic information, determine an event rate for the plurality of patients for a specific alert state, and adjust a composite HF risk determination for the plurality of patients using the determined event rate.

This disclosure is directed to a medical system and technique for a filter-based approach to arrhythmia detection. In one example, the medical system comprises one or more sensors configured to sense physiological parameter(s); sensing circuitry configured to generate patient data based on the sensed physiological parameter(s), the patient data comprising signal data to represent cardiac activity of the patient; and processing circuitry configured to: detect a cardiac arrhythmia for the patient based on a classification of the signal data in accordance with a machine learning model, wherein the machine learning model comprises filter(s) for at least one portion of the signal data, wherein the at least one filter corresponds to a feature set that maps to the cardiac activity represented by the portion(s) of the signal data; and generate for display output data indicative of a positive detection of the cardiac arrhythmia.

This disclosure is directed to a medical system and technique for a filter-based approach to arrhythmia detection. In one example, the medical system comprises one or more sensors configured to sense physiological parameter(s); sensing circuitry configured to generate patient data based on the sensed physiological parameter(s), the patient data comprising signal data to represent cardiac activity of the patient; and processing circuitry configured to: detect a cardiac arrhythmia for the patient based on a classification of the signal data in accordance with a machine learning model, wherein the machine learning model comprises filter(s) for at least one portion of the signal data, wherein the at least one filter corresponds to a feature set that maps to the cardiac activity represented by the portion(s) of the signal data; and generate for display output data indicative of a positive detection of the cardiac arrhythmia.

The present invention provides a bio-electrode composition including a silicone bonded to a sulfonamide salt, wherein the sulfonamide salt is shown by the following general formula (1): ##STR00001##
wherein R.sup.1 represents a linear, branched, or cyclic alkylene group having 1 to 20 carbon atoms optionally having an aromatic group, an ether group, or an ester group, or an arylene group having 6 to 10 carbon atoms; Rf represents a linear, branched, or cyclic alkyl group having 1 to 4 carbon atoms and containing at least one fluorine atom; M.sup.+ is an ion selected from a lithium ion, a sodium ion, a potassium ion, and a silver ion. This can form a living body contact layer for a bio-electrode that is excellent in electric conductivity and biocompatibility, light-weight, manufacturable at low cost, and free from large lowering of the electric conductivity even though it is wetted with water or dried.

The invention relates to an active implantable medical device comprising a processing unit able to be alternately operated during a predetermined period of activity and on standby during a standby period in a cyclical manner, and means for acquiring data relating to physiological and/or physical activity. The device also comprises means for calculating a frequency analysis of the data acquired, said calculating means being capable of successively perform part of the frequency analysis during periods of activity of the processing unit.

The invention relates to an active implantable medical device comprising a processing unit able to be alternately operated during a predetermined period of activity and on standby during a standby period in a cyclical manner, and means for acquiring data relating to physiological and/or physical activity. The device also comprises means for calculating a frequency analysis of the data acquired, said calculating means being capable of successively perform part of the frequency analysis during periods of activity of the processing unit.

An apparatus for estimating a core body temperature of an object is provided. According to one embodiment, the apparatus includes a plurality of sensors configured to obtain data from an object and a processor configured to obtain a surface temperature, a heat flux, a skin blood flow rate, and a blood flow velocity by using the data obtained from the plurality of sensors, obtain a skin thermal conductivity based on the skin blood flow rate, and estimate a core body temperature of the object based on the surface temperature, the heat flux, the skin thermal conductivity, and the blood flow velocity of the object.