A measuring apparatus as an aspect of the present invention includes: a first signal acquirer that acquires a pulse wave signal of a living body; a second signal acquirer that acquires a body motion signal of the living body; a frequency analyzer that converts the pulse wave signal and the body motion signal to a frequency domain to generate frequency domain signals, and estimates a frequency of a pulse wave of the living body on the basis of the frequency domain signals; and a time domain analyzer that calculates biological information about the living body on the basis of the frequency.

According to one embodiment, a light-emitting element includes a substrate, a first electrode, a second electrode, and a light-emitting layer. The substrate is light-transmissive. The second electrode is provided between the first electrode and a portion of the substrate. The second electrode is light-transmissive. A light-emitting layer is provided between the first electrode and the second electrode. The substrate includes a first region and a second region. The first region overlaps at least a portion of the light-emitting layer in a first direction, the first direction is from the second electrode toward the first electrode. The second region is provided around the first region along a plane perpendicular to the first direction. The substrate has an opening provided in at least a portion of the second region.

According to one embodiment, a detection device includes a substrate, a light detector, a light emitter. The substrate is light-transmissive. The light emitter is provided between the substrate and the light detector. The light emitter includes a first electrode, a light-emitting layer, and a plurality of second electrodes. The first electrode is provided between the light detector and the substrate. The first electrode is light-transmissive. The light-emitting layer is provided between the light detector and the first electrode. The second electrodes are provided between the light detector and the light-emitting layer.

This document describes assessing cardiovascular function using an optical sensor, such as through sensing relevant hemodynamics understood by pulse transit times, blood pressures, pulse-wave velocities, and, in more breadth, ballistocardiograms and pressure-volume loops. The techniques disclosed in this document use various optical sensors to sense hemodynamics, such as skin color and skin and other organ displacement. These optical sensors require little if any risk to the patient and are simple and easy for the patient to use.

An emotion analysis method and an electronic apparatus thereof are provided. The emotion analysis method is adapted to the electronic apparatus having a database or connected to the database in order to analyze an emotion of an examinee. The emotion analysis method includes: obtaining a heart rate signal of the examinee; defining a plurality of candidate emotions from the database; analyzing the heart rate signal to obtain a plurality of target emotion parameters; and analyzing the target emotion parameters to determine one of the candidate emotions corresponding to the heart rate signal by applying an emotion analysis model.

An abnormality processing system is provided capable of executing appropriate processing in cases where an abnormality occurs in a worker's living body. A management computer 300, if determining that an abnormality is present in a worker's living body, transmits an abnormality signal to an administrator terminal 100, a work device 200, a worker camera 20 and a surveillance camera 50. When receiving the abnormality signal, the administrator terminal 100 displays an image showing that an abnormality has occurred. When receiving the abnormality signal, the work device 200 stops operation. When receiving the abnormality signal, the worker camera 20 and the surveillance camera 50 transmit to the management computer 300 imaging data containing at least data of images before and after a timing at which the abnormality has occurred in the worker's living body.

An Internet of Thing (IoT) sport device includes a body with a processor, a camera and a wireless transceiver coupled to the processor.

Systems and methods for predicting exposure to an agent. One or more features are extracted from physiological data. For each respective classifier, (i) the respective classifier is identified, wherein the respective classifier is trained using training data for a respective physiological state, (ii) the respective classifier is applied to the one or more features to obtain a classifier output that represents a likelihood of exposure, (iii) a respective first threshold is applied to the classifier output to determine a patient state classification, and (iv) the patient state classifications are aggregated across a number of time intervals to obtain an aggregate patient state classification for each classifier. The aggregate patient state classifications are combined across the plurality of classifiers to obtain a combined classification, and an indication that the patient has been exposed to the agent is provided when the combined classification exceeds a second threshold.

Techniques and technologies for determining and enhancing productivity are described. In at least some embodiments, a system for includes a processing component operatively coupled to a memory; a productivity analyzer at least partially disposed in the memory, the productivity analyzer including one or more instructions that when executed by the processing component perform operations including: receive productivity data associated with usage of one or more productivity tools by at least one user during a time period; receive biometric data associated with one or more biometric aspects of the at least one user during the time period; analyze one or more aspects of the productivity data and the biometric data; and determine based on the analysis at least one productivity-related operation intended to enhance at least one productivity metric of the at least one user.

Provided is an electronic device to monitor a user's biological measurements, where a sensor is configured to acquire a first signal from a user, and a diagnostic processor is configured to pre-process the first signal to generate a second signal, segment the second signal to form signal segments, determine at least one event location for each of the signal segments, match adjacent signal segments for feature alignment, and provide a third signal using results of the feature alignment.