A highly accurate glucose sensor that detects glucose by transmitting and receiving sensing signals in a radio or microwave frequency range of the electromagnetic spectrum is provided. The glucose sensor has at least two antennas at least one of which operates as a transmit antenna to transmit one or more of the sensing signals and at least one of which operates as a receive antenna, and the glucose sensor has a mean absolute relative difference (MARD) value of about 5.0% to about 9.9%, or of about 5.0% to about 7.0%, or of about 5.0%.

Systems and methods for monitoring sleep using a sleep monitoring system includes a first component and a second component. The first component is configured to be coupled to a chest of the subject and the second component is configured to be concurrently coupled to an abdomen of the subject. Each component includes a housing, a pair of electrode pads mounted on an underside of the respective housing, and an ECG sensor circuit communicatively coupled to the respective pair of electrode pads. The first component further includes a photoplethysmogram sensor that includes at least one light source and at least one photodetector mounted on the underside of the housing of the first component at a location between the first pair of electrode pads.

Provided is a data processing method according to the present disclosure including: a scan data acquiring operation of acquiring scan data expressing an object, a reliability determining operation of determining a reliability of at least one evaluation area including at least one unit area for evaluating the scan data, and an indicating operation of indicating the evaluation area as a predetermined mark depending on the reliability of the evaluation area.

A stretch-deforming electrode includes a stretching portion. The stretching portion has a first stretching range and a second stretching range, in which the stretching portion has a first length variation and a first resistance variation in the first stretching range and a second length variation and a second resistance variation in the second stretching range. The first resistance variation remains substantially unchanged when the first length variation changes, the second resistance variation changes when the second length variation changes. The second resistance variation is represented by R2, the second length variation is represented by L2, and R2=A×L2, in which A is a positive number between 0.05 and 2.

An electrocardiogram information dynamic monitoring method and dynamic monitoring system. The method includes a dynamic monitoring device receiving monitoring reference data input by a user or issued by a server; the data collection on a tested object so as to obtain electrocardiogram data of the tested object; the characteristic identification on the electrocardiogram data so as to obtain characteristic signals of the electrocardiogram data, implementing cardiac activity classification on the electrocardiogram data according to the characteristic signals, obtaining cardiac activity classification information according to electrocardiogram basic rule reference data, and generating electrocardiogram event data, wherein the electrocardiogram event data comprises device ID information of the dynamic monitoring device; the dynamic monitoring device determining corresponding electrocardiogram event information according to the electrocardiogram event data, and determining whether the electrocardiogram event information is electrocardiogram abnormality event information; and outputting alarm information when the electrocardiogram event information is electrocardiogram abnormality event information.

The present specification describes systems and methods that enable the automatic detection, analysis and calculation of various processes and parameters associated with electromyography. The methods of the present specification include the automated modulation of analytical or recording states based on the nature of the signal, optimal reference fiber selection, modulating a trigger level, and determining firing parameters.

A computer implemented method and system for detecting premature ventricular contractions (PVCs) are provided. The method is under control of one or more processors configured with specific executable instructions. The method obtains a cycle length (CL) distribution metric that plots a series of cardiac beats into one of a set of transition types based on R-R interval (RRI) difference pairs associated with the cardiac beats. The CL distribution metric plots the cardiac beats based on a comparison between combinations of the RRI difference pairs for corresponding combinations of the cardiac beats. The method calculates a distribution characteristic for the cardiac beats, from the series of cardiac beats that exhibit a first transition type from the set of transition types and calculates a discrimination score based on the distribution characteristic of the cardiac beats across the CL distribution metric. The method designates the CA signals to include a predetermined level of PVC burden based on the discrimination score.

A device for measuring oxygen saturation includes circuitry configured to determine a series resistance for a light emitting diode based on a first diode voltage at the light emitting diode for a first current, a second diode voltage at the light emitting diode for a second current, and a third diode voltage at the light emitting diode for a third current. The circuitry is further configured to determine an intensity of a received photonic signal corresponding to an output photonic signal output using the light emitting diode. The circuitry is further configured to determine an oxygen saturation level based on the intensity of the received photonic signal and the series resistance.

The present invention is directed to system and method for effectively monitoring critical respiratory parameters including SpO.sub.2, PR, COHb, inspired CO.sub.2, expired CO.sub.2, respiration rate, respiration pattern, hyperventilation (hypocapnia), hypoventilation (hypercapnia), CO.sub.2 contamination, and CO.sub.2 rebreathing. The system according to the present invention comprises a pulse oximetry sensor and a CO.sub.2 sensor connected to a central portable unit. The central unit comprising a barometer, an accelerometer, a capnography circuit, and a control unit. The control unit including the method for effectively monitoring critical respiratory parameters.

A head-mounted device includes one or more eye-tracking cameras and one or more computer-readable hardware storage devices having stored thereon computer-executable instructions, including a machine-learned artificial intelligence (AI) model. The head-mounted device is configured to cause the one or more eye-tracking cameras to take a series of images of one or more areas of skin around one or more eyes of a wearer, and use the machine-learned AI model to analyze the series of images to extract a photoplethysmography waveform. A heart rate is then detected based on the photoplethysmography waveform.