A system and method for monitoring and auditing the patient's health care compliances in order to detect bedside patient's information such as bed sores, oral health care, insertion of invasive devices, patient positions etc. The system employs visual sensors such as lidars, IR cameras etc. for observing the patients. The system also uses machine learning algorithms that use the bedside patient information into pre-trained models so as to monitor, trace and diagnose patient histories by the caretakers.

A system for assessment of neurocognitive and neuromotor control performance, the system comprising a portable force plate configured to collect force plate data indicative of movement and postural control of a subject as the subject performs a task, a depth sensing device configured to, simultaneously with the collection of the force plate data, collect depth data of the subject as the subject performs the task, an interface board configured to, simultaneously with the collection of the force plate data and the collection of the depth data, generate stimuli to instruct the subject to perform a particular task and to generate interface board data indication of input received from the subject in response to the stimuli, and a computer-based controller configured to execute one or more neurocognitive and neuromotor control performance assessment program to analyze the force plate data, the depth data, and the interface board data.

This disclosure relates generally to health monitoring and assessment systems, and more particularly to perform postural stability assessment of a user and quantify the assessed postural stability. In an embodiment, the system, by monitoring specific actions (which are part of certain tests done for the postural stability assessment) being performed by a user, collects inputs which are then processed to determine SLS duration, the body joint vibration, and the body sway area of the user, while performing the tests. By processing the SLS duration, the body joint vibration, and the body sway area together, a postural stability index score for the user is determined, and based on this score, postural stability assessment for the user is performed.

Methods and systems are provided for obtaining cleaned sequences showing trajectories of movement of a center of gravity and for estimating a biometric information pattern or value of a target. One of the methods includes removing noises from initial sequences showing trajectories of movement of a center of gravity to obtain the cleaned sequences. Another one of the methods includes reading cleaned sequences of the target into a memory, extracting features from the cleaned sequences, and estimating a biometric information pattern or value of the target from the extracted features, using a classification or regression model of biometric information patterns or values. The biometric information pattern may be a pattern derived from respiratory or circulatory organs of a target.

A method includes causing display, during a first time period and via a first set of multiple smart mirrors, of live video depicting at least one user associated with the first set of multiple smart mirrors, without displaying a workout video. The method also includes causing display, during a second time period following and mutually exclusive of the first time period, and via a second set of multiple smart mirrors, of a workout video and a representation of at least one user associated with the second set of smart mirrors. The method also includes causing display, during a third time period following and mutually exclusive of the second time period, and via a third set of multiple smart mirrors, of live video depicting at least one user associated with the third set of multiple smart mirrors.

A method for determining one or more vital signs of a person includes recording video images of a scene with an egocentric camera coupled to the person's body, detecting and magnifying image frame-to-image frame movements in the video images of the scene, representing the magnified image frame-to-image frame movements in the video images of the scene by a one-dimensional (1D) amplitude-versus-time series, and transforming the 1D amplitude-versus-time series representation into a frequency spectrum. The method further includes identifying one or more local frequency maxima in the frequency spectrum as corresponding to one or more vital signs of the person.

Disclosed are systems and methods for generating wide-field optical coherence tomography angiography (OCTA) images. In embodiments, multiple OCTA scans of a sample are automatically acquired at overlapping locations. The systems and methods include functionality to adaptively control the scanning procedure such that eye blink and eye motion events are detected in real time and accounted for during 3D scan acquisition. Also disclosed are methods for detecting and correcting motion-related artifacts in OCTA datasets which allow for the longer scan times over larger fields of view required for wide-field imaging. These methods may include division of en face angiogram images into a set of motion-free parallel strips, and application of gross and fine registration methods to align overlapping strips into a motion- corrected composite image. A series of overlapping motion-corrected composite images may be combined into a larger montage to enable wide-field OCTA imaging using multiple OCTA scans.

A computer system for identifying a posture adopted by a subject is disclosed. The computer system includes a computer processor that is configured to execute the following functions: obtain a set of reference pressure images, each of the reference pressure images associated with a known posture; obtain a recorded pressure image of the subject; compare the recorded pressure image of the subject with a candidate pressure image from the set of reference pressure images; and repeat the comparing function until the recorded pressure image with the candidate pressure image.

Provided herein is a mechatronic simulator system that provides various types of unexpected perturbations to challenge the proactive and reactive balance control in subjects to thereby improve balance control of the subject. The system includes a motion capture unit and a processing unit capable of analyzing the subject’s response to the perturbations, provide real time feedback, adjust and/or determine training sessions.

This document discusses a computer-implemented method of machine recognition of a physiological condition of a subject. The computer-implemented method comprises obtaining a video stream of the subject using a video data source; identifying, using processing circuitry, one or more areas within image frames of the video stream that contain a physiological feature of the subject; analyzing video data of the identified one or more areas in the image frames using the processing circuitry to detect change of the physiological feature between a first frame of video data and a later frame of video data; determining one or more change parameters of the physiological feature from the video data; and generating an indication of a symptom of Parkinson's Disease according to a detection criterion applied to the one or more change parameters.