A method for test strip recognition and interpretation is provided. The method includes the following steps. A plurality of test strips are provided, wherein the test strips are configured to examine a plurality of physiologic parameters respectively, and the test strips respectively have a plurality of color characteristics corresponding to the physiologic parameters respectively. A plurality of physiologic parameter examinations are performed to the corresponding test strips respectively, so as to obtain a plurality of test reactions. An image of the test strips is captured. The color characteristics and the test reactions of the test strips are obtained according to the image. The physiologic parameters examined by the test strips respectively are obtained according to the color characteristics. The physiologic parameters examined by the test strips are matched with the test reactions to obtain a plurality of physiologic parameter examination results.

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 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.

A method for monitoring physical conditions of an operator of a driving apparatus is described. The method includes obtaining an identity of the operator, acquiring signals indicating a physical condition of the operator, and determining whether the physical condition as indicated by the signals has breached a predetermined threshold. Further, when it is determined that the physical condition as indicated by the signals has breached a predetermined threshold, the method includes generating a first status indicating the operator suffers an abnormal physical condition, obtaining a current location of the driving apparatus, generating a first notification based on the first status, the first notification indicating the identity of the operator and the current location of the driving apparatus, the first notification describing the first user suffers the abnormal physical condition, and transmitting the first notification to a data receiver in a healthcare facility.

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.

An arrangement may include a first system provided for processing physiological data representative of a beating heart. The first system may be adapted to execute a process for using at least one pattern to detect a notable finding in the physiological data and for sending the notable finding to a second system. The second system may be adapted to execute a process for analyzing the notable finding, for determining at least one new pattern to send to the first system, and for sending the at least one new pattern to the first system. The at least one new pattern may also include a rule that includes a set of conditions and an action to perform if the set of conditions is met.

In one example, an ambulatory medical device is provided. The ambulatory medical device includes a plurality of subsystems, at least one sensor configured to acquire data descriptive of a patient, a user interface and at least one processor coupled to the at least one sensor and the user interface. The at least one processor is configured to identify subsystem status information descriptive of an operational status of each subsystem of the plurality of subsystems and to provide a device health report for the ambulatory medical device via the user interface, the device health report being based on the operational status of each subsystem.

In one example, an ambulatory medical device is provided. The ambulatory medical device includes a plurality of subsystems, at least one sensor configured to acquire data descriptive of a patient, a user interface and at least one processor coupled to the at least one sensor and the user interface. The at least one processor is configured to identify subsystem status information descriptive of an operational status of each subsystem of the plurality of subsystems and to provide a device health report for the ambulatory medical device via the user interface, the device health report being based on the operational status of each subsystem.

A mobile device, methods and systems provide the invention mobile Personal Health Records (PHR) management platform solution. The platform enables secure PHR data management, measuring user's medical parameters, managing PHR secured depository containing user's health data on the user's invention combined phone & add-on sleeve device, while blocking none legitimate users access to the invention devices secured storage content. The invention device user's authentication is based on the combined weighted fusion of at least two different human biological sensors within the device and their weighted output analysis. The multi-sensors ensure bio-authentication secured memory entry only for the legitimate device user. In case of authentication success it activates various types of applications on the user PHR data depository content stored in device. The system supports the user's PHR remote health management, remotely monitoring the user's measured medical parameters, updating & managing user's health medical history depository in the user's electronic sleeve.