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.

Provided according to embodiments of the present invention are methods of monitoring individuals that include securing a photoplethysmography probe to at least one of a pre-auricular region and a post-auricular region of the individual and obtaining photoplethysmography signals from the photoplethysmography probe. Photoplethysmography probes and helmets related to such methods are also described herein.

An exercise and communications system includes an interactive device, a remote device, and an external device, wherein the interactive device is configured to gather data relating to a user of the system and transmit the same to the remote device, and the remote device is configured to provide analyze the data and transmit a response to the interactive device, which in turn communicates the response to the user and additionally communication with an external device for retrieval of instructions, programs, and data, inter alia. An exercise and communications system facilitates communication between a plurality of users, each having an interactive device and a remote device.

The non-invasive blood glucose level measurement device (1) is provided with a pulse waveform measurement unit (2) having FBG sensors (4) for measuring an acceleration pulse wave of a test subject; and a data-processing unit (3) for calculating the blood glucose level of the test subject at the point in time of measurement of the acceleration pulse wave, from waveform information of the measured acceleration pulse wave, on the basis of a predetermined correlation. The correlation is a calibration curve constructed by carrying out a PLS regression analysis, using the blood glucose level measured by a non-invasive blood glucose method as the objective variable, and a simultaneously-measured acceleration pulse wave as the explanatory variable. A non-invasive blood glucose level measurement device capable of measuring blood glucose level at about the same measurement accuracy as an invasive blood glucose measurement device can be achieved thereby.

The present disclosure generally relates to user interfaces for health applications. In some embodiments, exemplary user interfaces for managing health and safety features on an electronic device are described. In some embodiments, exemplary user interfaces for managing the setup of a health feature on an electronic device are described. In some embodiments, exemplary user interfaces for managing background health measurements on an electronic device are described. In some embodiments, exemplary user interfaces for managing a biometric measurement taken using an electronic device are described. In some embodiments, exemplary user interfaces for providing results for captured health information on an electronic device are described. In some embodiments, exemplary user interfaces for managing background health measurements on an electronic device are described.

Methods and apparatus provide physiological movement detection, such as gesture, breathing, cardiac and/or gross motion, such as with sound, radio frequency and/or infrared generation, by electronic devices such as vehicular processing devices. The electronic device in a vehicle may, for example, be any of an audio entertainment system, a vehicle navigation system, and a semi-autonomous or autonomous vehicle operations control system. One or more processors of the device, may detect physiological movement by controlling producing sensing signal(s) in a cabin of a vehicle housing the electronic device. The processor(s) control sensing, with a sensor, reflected signal(s) from the cabin. The processor(s) derive a physiological movement signal with the sensing signal and reflected signal and generate an output based on an evaluation of the derived physiological movement signal. The output may control operations or provide an input to any of the entertainment system, navigation system, and vehicle operations control system.

A physiological sensor has light emitting sources, each activated by addressing at least one row and at least one column of an electrical grid. The light emitting sources are capable of transmitting light of multiple wavelengths and a detector is responsive to the transmitted light after attenuation by body tissue.

Provided are systems for measuring an electrocardiogram (ECG) using a wearable device. An example system includes the wearable device. The wearable device has a means for recording an electrical signal from a single wrist of a patient. The wearable device also has a means for detecting a pulse of the patient and recording a photoplethysmogram (PPG) signal, via a PPG optical sensor associated with the wearable device. The wearable device further has a means for generating the electrical signal segments being time-locked to the PPG signal by utilizing the PPG signal as a reference signal. Furthermore, the wearable device has a means for summing the electrical signal segments in a given time period and dividing by the number of segments to produce an average ECG waveform.

A method of presenting data from a remote sensor that is monitoring a subject includes obtaining a data stream from the remote sensor, wherein the data stream includes a sensor metric, a metric identifier, dynamically updated integrity information about an accuracy of the sensor metric, and a diagnostic assessment of a health condition of the subject, and then displaying, via a display associated with the client device, the diagnostic assessment of the health condition of the subject, a metric statistic associated with the diagnostic assessment, and a recommendation as to an action to be taken by the subject.

There is described a method and system for measuring a level of anxiety. Measured data comprising EEG data collected from a parietal (P) EEG electrode is received. A group 8 indicator based on a power, P-power (dt), associated with a delta-theta frequency band, dt, within a delta-theta frequency range is extracted. Based on said group 8 indicator, a level of anxiety, LoA, is determined which is a value indicative of the level of anxiety of the subject.