According to certain embodiments, an electronic device comprises: a housing; a protrusion from a side surface of the housing including a first window and a second window; a first board disposed inside the housing; a second board connected to one surface of the first board; a first sensor circuit mounted on a first surface of the second board, disposed in the protrusion, and spaced apart from and under the first window; and a second sensor circuit mounted on a second surface of the second board facing in a direction opposite to the first surface of the second board, disposed in the protrusion, and spaced apart from and above the second window.

In one example, a display unit comprises a display panel that is configured to display digital images. The display unit further comprises an at least partially transparent protective layer that is arranged above the display panel. The display unit further comprises a controller that is communicatively attached onto an upper surface of the display panel. A biometric sensor pattern is integrated in the controller, and the controller is configured to control the biometric sensor pattern.

Provided herein are control and monitoring protocols for a virtual or augmented reality environment provided to patients, and which enable a trainer to have real-time monitoring and control of the virtual reality environment. In various embodiments, a virtual environment is provided to a first user at a first location. Data (e.g., biometric data) is collected based on the first user's interaction with the virtual environment while engaging in a training protocol. A real-time mirrored view of the virtual environment is provided to a second user via a network. The data and one or more control tools are provided to the second user. The control tools are configured to adjust one or more parameters of the virtual environment. A selection of at least one of the control tools is received form the second user and the virtual environment is adjusted based on the selection.

A biological information displaying apparatus according to an embodiment includes a picture obtaining apparatus and a processor. The picture obtaining apparatus obtains a picture signal of a predetermined site of a subject as a moving image. The processor generates a hue moving image by extracting a luminance or an image-based photoplethysmogram (iPPG) related to a pulse wave for each pixel of the moving image and assigning a hue in accordance with a value of luminance information or iPPG information. The processor displays the generated hue moving image such that the hue moving image is superimposed on an image of the subject.

A fatigue measurement method includes obtaining a face video of a target object, processing the facial video to obtain a plurality of quasi-heart rates and a plurality of quasi-vibration frequencies, selecting a target heart rate from the plurality of quasi-heart rates and a target vibration frequency from the plurality of quasi-vibration frequencies, detecting the target heart rate and the target vibration frequency, and determining, according to the detection result, that the target object is in a fatigue state. The quasi-heart is obtained through one or more of a region of interest (ROI) between eyebrows and an ROI of chin, and the quasi-vibration frequency obtained through one or more of an ROI of eyes and an ROI of mouth.

A context driven alerting system and method is described in accordance with one or more embodiments of the present disclosure. The alerting system and method may consider a pilot's physiological, psychological, and behavioral state during a given mission context. The system may include biometric information which is fused with a context of the flight. The context may be based on one or more of a mission profile data or an aircraft state data. The fused data may be time synchronized and provided to an alerting algorithm. The alerting algorithm may then provide an alert to the pilot which includes a priority, intensity, frequency, or modality determined based on the fused information.

A method and system may use machine learning analysis of audio data to automatically identify a user's biometric characteristics. A user's client computing device may capture audio of the user. Feature data may be extracted from the audio and applied to statistical models for determining several biometric characteristics. The determined biometric characteristic values may be used to identify individual health scores and the individual health scores may be combined to generate an overall health score and longevity metric. An indication of the user's biometric characteristics which may include the overall health score and longevity metric may be displayed on the user's client computing device.

A device for liveness detection is disclosed. The liveness detecting device has a simplest structure that principally comprises a light sensing unit and a signal processing module. Particularly, the signal processing module is configured for having a physiological feature extracting unit and a liveness detecting unit therein. The physiological feature extracting unit is adopted for extracting a first physiological feature from a PPG signal, or extracting a second physiological feature from the PPG signal that has been applied with a signal process. As such, through the first and second physiological features, the liveness detecting unit is able to determine whether a subject is a living body or not. The liveness detecting device does not use any camera unit and iPPG technology, such that the liveness detecting device has advantages of simple structure, low cost and immediately completing liveness detection.

An information processing method includes: obtaining first image data indicating an image of at least one portion of a face of a target person from a camera connected to or built into a first computer; obtaining cerebral blood flow information indicating a state of cerebral blood flow of the target person from a detector that is connected to or built into the first computer and that detects the cerebral blood flow information; and displaying, on a display connected to or built into a second computer connected to the first computer through a remote network, an output image including a first image based on the first image data and a second image based on the cerebral blood flow information. The first image is a moving image including the at least one portion of the face, and the second image indicates changes over time in the cerebral blood flow information.

There is provided a device for acquiring biometric electrical signals comprising at least two electrodes. The device also comprises a current supply comprising a direct current supply, an alternating current supply, and a switch actuatable to switch selectively between the direct current supply and the alternating current supply. The device further comprises a capacitive coupling to couple each electrode to the current supply, a direct coupling to couple each electrode to the current supply, and a switch actuatable to switch selectively between the direct coupling and the capacitive coupling. The device also comprises a data acquisition module.