A method includes receiving a video signal that comprises a time series of images of a face of a human, wherein the images in the time series of images comprise a set of landmark points in the face, applying tracking processing to the video signal to reveal variations over time of at least one image parameter at the set of landmark points in the human face, generating a set of variation signals indicative of variations revealed at respective landmark points in the set of landmark points, applying processing to the set of variation signals, the processing comprising artificial neural network processing to produce a reconstructed PhotoPletysmoGraphy (PPG) signal, and estimating a heart rate variability of a variable heart rate of the human as a function of the reconstructed PPG signal.

A system and method for camera-based stress determination. The method includes: determining a plurality of regions-of-interest (ROIs) of a body part; determining a set of bitplanes in a captured image sequence for each ROI that represent HC changes using a trained machine learning model, the machine learning model trained with a hemoglobin concentration (HC) changes training set, the HC changes training set trained using bitplanes from previously captured image sequences of other human individuals as input and received cardiovascular data as targets; determining an HC change signal for each of the ROIs based on changes in the set of determined bitplanes; for each ROI, determining intervals between heartbeats based on peaks in the HC change signal; determining heart rate variability using the intervals between heartbeats; determining a stress level using at least one determination of a standard deviation of the heart rate variability; and outputting the stress level.

A method, system, and/or apparatus for automatically monitoring for possible mental or physical health concerns. The method or implementing software application uses or relies upon location information available on the mobile device from any source, such as cell phone usage and/or other device applications. The method and system automatically learns user activity patterns and detects significant deviations therefrom. The deviations are automatically analyzed for known correlations to mental or physical concerns, which can then be automatically communicated to a relevant friend, family member, and/or medical professional.

A mobile communication device-based corneal topography system includes an illumination system, a mobile communication device and a corneal topography optical housing. The illumination system is configured to generate an illumination pattern and to generate reflections of the illumination pattern off a cornea of a subject, wherein the illumination system is aligned along an axis of centers of the illumination pattern. The mobile communication device includes an image sensor to capture an image of the reflected illumination pattern. The corneal topography optical housing is coupled to the illumination system and the mobile communication device, wherein the corneal topography optical housing supports and aligns the illumination system with the image sensor of the mobile communication device. The corneal topography optical housing includes an imaging system coupled to the image sensor.

A method, system, and/or apparatus for automatically monitoring for possible infection or other physical health concerns, such as from Covid-19. The method or implementing software application uses or relies upon location information available on the mobile device from any source, such as cell phone usage and/or other device applications. The method and system automatically uses and/or learns user location and activity patterns and determines and infection risk that can be communicated as a warning to community members.

A display device includes: a display panel including a first area having a first light transmissivity and a second area having a second light transmissivity higher than the first light transmissivity; a pressure sensor overlapping the first area; a light emitter overlapping the second area; a light receiver overlapping the second area and spaced from the light emitter; and a processor to control the light emitter and the pressure sensor, and to output a blood pressure signal on a basis of a pressure sensing signal from the pressure sensor and a light sensing signal from the light receiver.

Methods and apparatuses, including devices and systems, for remote and detection and/or diagnosis of acute myocardial infarction (AMI). In particular, described herein are handheld and adhesive devices having an electrode configuration capable of recording three orthogonal ECG lead signals in an orientation-specific manner, and transmitting these signals to a processor. The processor may be remote or local, and it may automatically or semi-automatically detect AMI, atrial fibrillation or other heart disorders based on the analyses of the deviation of the recorded 3 cardiac signals with respect to previously stored baseline recordings.

An apparatus for measuring a signal is provided. The apparatus for measuring a signal may include a sensor configured to generate pixel data representing a fingerprint image of an object by detecting light scattered or reflected from the object and a processor configured to acquire the fingerprint image of the object based on the pixel data and acquire a pulse wave signal based on the fingerprint image and the pixel data.

A detection device detecting changes in positive and negative feelings related to mild cognitive impairment is provided. This detection device includes: a detector detecting heartbeat information of a subject; a calculating unit calculating a maximum Lyapunov exponent from the heartbeat information, the maximum Lyapunov exponent indicating to what extent heartbeat intervals vary; a feeling determination unit determining whether the subject has a negative feeling with brain fatigue, anxiety or depression, or a positive feeling without brain fatigue, anxiety and depression, based on the maximum Lyapunov exponent; a change determination unit determining whether the positive or negative feeling of the subject has changed, based on frequency of occurrence of the negative or positive feeling in a predetermined period; and an output unit outputting a result of determination by the change determination unit.

This relates to methods for measuring irregularities in a signal and corresponding devices. The devices can include a PPG sensor unit configured to detect multiple occurrences of a given event in the measured signal(s) over a sampling interval. In some instances, the device can register the occurrences of the events. In some examples, the device can include one or more motion sensors configured to detect whether the device is in a low-motion state. The device may delay initiating measurements when the device is not in a low-motion state to enhance measurement accuracy. Examples of the disclosure further include resetting the sample procedure based on one or more factors such as the number of non-qualifying measurements. In some examples, the device can be configured to perform both primary and secondary measurements, where the primary measurements can include readings using a set of operating conditions different from the secondary measurements.