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 gate apparatus includes an upper light that emits light from above a user, a lower light that emits light from below the user, a light control unit, and an acquisition unit. The acquisition unit acquires biological information about the user. The light control unit changes the luminance of the light emitted from the upper light and the luminance of the light emitted from the lower light when the biological information about the user is acquired.

A computer-based system and method for generating a current pain assessment of a neonate using facial expressions along with crying sounds, body movement, and vital signs changes and for using the current pain objective assessment to predict future pain objective assessment and assign a future pain probability score by incorporation spatiotemporal data into the multimodal assessment.

An imaging photoplethysmography (iPPG) system is provided. The iPPG system receives a sequence of images of different regions of the skin of the person, where each region including pixels of different intensities indicative of variation of coloration of the skin. The iPPG system further transforms the sequence of images into a multidimensional time-series signal, each dimension corresponding to a different region from the different regions of the skin. The iPPG system further processes the multidimensional time-series signal with a time-series U-Net neural network wherein the pass-through layers include a recurrent neural network (RNN) to generate a PPG waveform, where the vital sign of the person is estimated based on the PPG waveform, and the iPPG system further renders the estimated vital sign of the person.

The present disclosure provides systems and methods for performing an automated scan preparation for a scan of a target subject. The automated scan preparation may include, for example, identifying a target subject to be scanned, generating a target posture model of the target subject, causing a movable component of a medical imaging device to move to its target position, controlling a light field of the medical imaging device, determining a target subject orientation, determining a dose estimation, selecting at least one target ionization chamber, determining whether the posture of the target subject needs to be adjusted, determining one or more scanning parameters (e.g., a size of a light field), performing a preparation check, or the like, or any combination thereof.

Systems and methods are provided to monitor vital signs from a plurality of subjects simultaneously and in real-time. The systems and methods can utilize visible video signal or infrared (IR) video signals, or both, defining respective sequences of frames representative of a scene including the plurality of subjects. The systems and methods can analyze digital images corresponding to respective frames in a sequence of frames to generate a time series of image values. In an aspect, the systems and methods can analyze the time series to identify a characteristic frequency representing a value of a vital signal that is oscillatory in nature.

Techniques are described for cognitive analysis for directed control transfer for autonomous vehicles. In-vehicle sensors are used to collect cognitive state data for an individual within a vehicle which has an autonomous mode of operation. The cognitive state data includes infrared, facial, audio, or biosensor data. One or more processors analyze the cognitive state data collected from the individual to produce cognitive state information. The cognitive state information includes a subset or summary of cognitive state data, or an analysis of the cognitive state data. The individual is scored based on the cognitive state information to produce a cognitive scoring metric. A state of operation is determined for the vehicle. A condition of the individual is evaluated based on the cognitive scoring metric. Control is transferred between the vehicle and the individual based on the state of operation of the vehicle and the condition of the individual.

The present invention discloses a home infotainment system having function of non-contact imaging-based physiological signal measurement. In the present invention, an image-based physiological signal (IBPS) measuring device is integrated with a television, and is configured for capture at least one image frame of a user who is watching the television. As such, after detecting detects a face portion from the image frame, the IBPS measuring device is able to subsequently extract at least one physiological signal from the face portion. Consequently, after the physiological signal is applied with at least one signal process by a display processor of the television or the IBPS measuring device, physiological indices of the user are hence calculated, and are subsequently applied with data processes of data storing, data transmitting, and/or displaying the physiological indices by a form of graphs, or diagrams, and/or numeric values.

A wearable device can present virtual content to the wearer for many applications in a healthcare setting. The wearer may be a patient or a healthcare provider (HCP). Such applications can include, but are not limited to, access, display, and modification of patient medical records and sharing patient medical records among authorized HCPs.

A vehicle may include: a feedback device; a bio-signal sensor configured to measure a bio-signal of a user; and a controller operatively coupled to the feedback device and the bio-signal sensor, the controller including a memory configured to store at least one program instruction and processor configured to execute the at least one program instruction. The controller may be configured to: determine information characterizing a current emotional state of the user based on the bio-signal; calculate, based on a difference value between the current emotional state and a target emotional state, an operation ratio between a first mode for controlling operation of the feedback device to decrease a degree of excitability of the user and a second mode for controlling the operation of the feedback device to increase a degree of positivity of the user; and control the operation of the feedback device for a predetermined time based on the operation ratio.