The present invention relates to a contactless intelligent monitor, including: a light source, a coupler, a concave-convex noise reduction unit, a first photodetector, a second photodetector, an MCU and a terminal; the light source, coupler and concave-convex noise reduction unit are connected in sequence; the output of the concave-convex noise reduction unit is connected to the MCU through the first photodetector and the second photodetector respectively; the MCU is connected to the terminal through a communication module. The present invention can effectively reduce the interference and false alarm caused by noises in the measurement process.

Embodiments of devices and methods for evaluating tissue are disclosed. In one embodiment, a method for measuring a characteristic of a tissue may include passing a current through the tissue, measuring a signal corresponding to the voltage resulting from passing the current through the tissue, analyzing current passed through the tissue and resulting voltage to determine the electrical characteristics of the tissue; and analyzing the electrical characteristics of the tissue to determine a status of the tissue. Methods for achieving relatively constant sensor application pressure are disclosed.

Disclosed herein is a physiological measurement system that can automatically adjust the number of wavelengths used based on the quality of a sensor signal that is reflective of an optical radiation detected at a sensor after tissue attenuation. The signal quality is examined to determine if it is sufficient to support the use of a full set of wavelengths. If it is determined to be insufficient to support the full set, a reduced number of wavelengths is used.

A set of training electrocardiograms (ECGs) for each of a plurality of subjects is processed using a machine learning model to generate an output for each training ECG of each of the plurality of subjects. Training ECGs for each subject are labeled with an identity of the subject. A machine learning model is trained by comparing the output generated for each training ECG to a corresponding label of the training ECG to generate an identity model to identify ECGs of a first subject of the plurality of subjects. A first ECG is received from an ECG sensor and input to the identity model, which generates an output indicating whether the first ECG corresponds to the first subject. In response to the output indicating that the first ECG does not correspond to the first subject, a condition that the first subject has or may develop is determined based on the output.

Methods, apparatus, and systems relating to a Wearable Cardioverter Defibrillator (WCD) system capable of logging event data and/or broadcasting state changes and/or system status information to external clients are described. In an embodiment, a processor stores data corresponding to one or more event markers in memory in response to occurrence of an event. Occurrence of the event is detected based at least in part on detection of one or more parameters by one or more sensors or a signal to be generated by one or more of electrodes of the WCD system. A communication device transmits at least a portion of the stored data to a remote device. A patient condition or a WCD system condition can then be detected based at least in part on analysis of the stored data and/or the transmitted portion of the stored data. Other embodiments are also disclosed and/or claimed.

An aspect of the present invention is a loss-of-consciousness estimation apparatus including: a ventricular state estimation unit configured to estimate whether or not a ventricular state of an estimation target is normal in a predetermined repetition cycle, based on a cerebral blood flow correlation amount time series, which is a time series of an amount correlated with a cerebral blood flow rate of the estimation target; a measurement reliability estimation unit configured to estimate reliability of the cerebral blood flow correlation amount time series; and a loss-of-consciousness probability acquisition unit configured to, based on the reliability, the estimation result of the ventricular state estimation unit, and elapsed time after a probability acquisition start time, which is a time at which it is first determined by the ventricular state estimation unit that the ventricular state is not normal after an estimation start time, which is a time of starting the repetition cycle, acquire a loss-of-consciousness probability indicating a probability that the estimation target has already lost consciousness.

A method of determining a measure of contact of an EMG sensor with the skin of a human or animal subject, the method comprising: receiving data captured by the EMG sensor; calculating a spectral entropy of the received data over a first time period in respect of a predetermined frequency band; determining a measure of contact for the first time period in dependence on the spectral entropy of the received data; and processing the received data of the first time period in dependence on the measure of contact.

A pulse sensor is capable of measuring a pulse rate of a wearer at a peripheral artery. In an embodiment, the pulse sensor includes a magnet supported to move responsive to an arterial pulse and a magnetometer configured to detect changes in a magnetic field produced by the magnet. The magnet may include a plurality of ferromagnetic particles disposed in or on a flexible substrate configured to be held adjacent to human skin subject to arterial palpation and a magnetic sensor configured to sense movement of the ferromagnetic particles. A system and method may measure hydration includes using a pulse sensor to measure pulse rate and modulation. The wearer is prompted when the pulse rate and pulse modulation indicate a response to dehydration of the wearer.

The system for cardiovascular parameter data quality determination can include a user device and a computing system, wherein the user device can include one or more sensors, the computing system, and/or any suitable components. The computing system can optionally include a data quality module, a cardiovascular parameter module, a storage module, and/or any suitable modules. The method for cardiovascular parameter data quality determination can include acquiring data and determining a quality of the data. The method can optionally include processing the data, and/or determining a cardiovascular parameter, training a data quality module, any suitable steps.

A body composition analysis system having image scanning function includes an image capturing device, a body composition analyzer having a stand platform with two first electrode sets, two handrails and a calculating unit electrically connected with the image capturing device, and a control panel. Each handrail has a telescopic rod and a handle having a second electrode set. An end of each telescopic rod is pivotably attached to the stand platform. Each handle is disposed at another end of each telescopic rod. The calculating unit includes a body shape module database and a calculational logic, receives resistance and reactance measured by the first and second electrode sets and image data obtained by the image capturing device, and after comparing the image data with the body shape module database, calculates by the calculational logic to obtain a body composition data to be shown on the control panel.