A cardiac health assessment system includes a memory, a circuit board, and a touchscreen controller integrated into a handheld electronic device (HED). The memory stores a classification model, a regression model, and instructions about a cardiac monitoring application. The circuit board includes a microphonic sensor, an Inertial Measurement Unit (IMU) sensor, a camera sensor, and a processor. The microphonic sensor captures cardiac sound wave signals indicative of the cardiac health of a user. The IMU sensor captures seismic signals indicative of the cardiac health of the user. The camera sensor enables visual data collection of tissue and photoplethysmography. The processor is configured to: execute the instructions, display commands to position the HED against the chest of the user, detect abnormal heart activity by deploying the classification model, and estimate intracardiac pressure by deploying the regression model. The touchscreen controller displays cardiac diagnostic information.

A current sensor may take measurements of electrical currents that flow between two limbs of a patient through at least a portion of the patient's torso. The current measurements may be taken during a single diagnostic session while the patient holds a ground electrode in a hand of one limb and a probe electrode is sequentially placed at different locations on the distal portions of other limbs. Each of the measurement locations may be an acupuncture point. An electrical current state for the diagnostic session may be calculated. This state may consist of current ranges for one or more electrical currents that are measured during the session. A lookup table may be employed to determine one or more medical conditions that are indicated by the current state. Alternatively, a trained machine learning model may predict, based on the measured currents, one or more medical conditions.

Techniques for providing health monitoring with mobile devices are discussed herein. Some embodiments may include a method including: receiving symptom data via a user interface of a mobile device over time, the symptom data defining symptoms and severities associated with the symptoms for a user; determining, by processing circuitry of the mobile device, time data associated with the symptom data; generating, by the processing circuitry, graph data based on the symptom data and the time data; generating, by the processing circuitry, a graph data report based on the graph data; and providing, by the processing circuitry, the graph data report to one or more servers via a network.

A method and a system for providing feedback to a user for adjusting sleep pattern of the user. The method includes collecting a set of information related to the user, receiving a set of measurement data related to the user from a wearable electronic device, defining circadian rhythm and duration of sleep of the user, determining sleep scores for a predefined number of days and associating each sleep score with a corresponding go-to-bed time or time of falling asleep of the user. A sleep score is determined for each of the predefined number of days from the collected set of information, the set of measurement data, the circadian rhythm and the duration of sleep of the user. The method further includes analysing the sleep scores and associated go-to-bed time or time of falling asleep of the user to determine an optimum bedtime window for the user and providing feedback to the user based on the analysed sleep scores and the optimum bedtime window.

A mobile-platform imaging device uses compression of the target region to generate an image of an object. A tactile sensor has an optical waveguide with a flexible, transparent first layer. Light is directed into the waveguide. Light is scattered out of the first layer when the first layer is deformed. The first layer is deformed by the tactile sensor being pressed against the object. A force sensor detects a force pressing the tactile sensor against the object and outputs corresponding force information. A first communication unit receives the force information from the force sensor. A receptacle holds a mobile device with a second communication unit and an imager that can generate image information using light scattered out of the first layer. The first communication unit communicates with the second communication unit and the mobile device communicates with an external network.

An apparatus for performing a remote test of range of motion of a person operating a user device includes a transceiver, a processor, and a display. The transceiver is configured to transmit a link to the user device and to receive motion data from the user device. The processor is configured to calculate in real time, based on the motion data, the position of the user device to enable real-time display to a test provider of the performance of the test and to determine in real time the quality of the test. The display is configured to show in real time a continuous indication of the performance of the test and quality results of the test. A method for performing a remote test of range of motion of a person operating a user device is also described and claimed.

An apparatus for estimating bio-information based on pulse wave signals of multiple wavelengths is disclosed. The bio-information estimating apparatus may include: a sensor part comprising a pulse wave sensor configured to measure a multi-wavelength pulse wave signal at a first point in time when a first pressure is applied from an object to the sensor part and at a second point in time when a second pressure is applied from the object to the sensor part; and a processor configured to estimate bio-information based on a difference between the multi-wavelength pulse wave signal measured at the first pressure and the multi-wavelength pulse wave signal measured at the second pressure.

An apparatus for estimating bio-information includes a pulse wave sensor configured to measure a pulse wave signal from an object, for a predetermined period of time, a processor configured to extract DC components of the pulse wave signal measured for the predetermined period of time, normalize the extracted DC components, based on at least one of the extracted DC components of the pulse wave signal measured at a time when a reference force is applied by the object to the pulse wave sensor, and estimate the bio-information, based on the normalized DC components.

A smart watch to detect a presence of an arrhythmia of a user is disclosed. The smart watch comprising: a processing device and a photoplethysmography (“PPG”) sensor operatively coupled to the processing device, an ECG sensor comprising two or more ECG electrodes and operatively coupled to the processing device, a display operatively coupled to the processing device, and a memory, operatively coupled to the processing device. The memory may have instructions stored thereon that, when executed by the processing device, cause the processing device to: receive PPG data from the PPG sensor, receive ECG data from the ECG sensor, detect, based on the PPG data and the ECG data simultaneously, the presence of an arrhythmia, and provide one or more recommendations to the user based on the PPG data and the ECG data.

A vital signs monitoring system, the system including: (a) an ear device including: a curved body adapted to a shape of an ear, an upper end, a lower end, two opposite facing sides, a first side adapted to be proximal a skull and a second side adapted to be proximal an earlobe, the ear device including: (i) a temperature sensor adapted to sense a body temperature from a depression between a lower, jawbone and skull; and (b) a control system, including a processor and a memory, configured and operable to control operation of the ear device, to collect signals received from at least one sensor including the temperature sensor, to process the signals to provide medically significant results.