A method and system of training a machine learning neural network (MLNN) in anatomical degenerative conditions in accordance with anatomical dynamics. The method comprises receiving, in a first input layer of the MLNN, from a millimeter wave (mmWave) radar sensing device, a first set of mmWave radar point cloud data representing a first gait characteristic of a subject in motion, comprising an arm swing velocity, receiving, in a second layer, a second set of mmWave radar point cloud data representing a second gait characteristic comprising a measure of dynamic postural stability, the input layers being interconnected with an output layer of the MLNN via an intermediate layer, and training a MLNN classifier in accordance with a classification that increases a correlation between a degenerative condition of the subject as generated at the output layer and the sets of mmWave point cloud data.

A psychological stress estimation method includes obtaining a physiological signal of a user corresponding to a current moment, determining a first stress indicator of the user based on the current moment and a cyclic stress model of the user, determining a second stress indicator of the user based on the physiological signal of the user corresponding to the current moment and an instantaneous stress model of the user, where the physiological signal is an input of the instantaneous stress model, and determining the current stress indicator of the user based on the first stress indicator and the second stress indicator.

A healthcare apparatus includes a BCG sensor; a camera; and a processor configured: to detect a ROI) corresponding to the face from the color facial image; to convert the detected first color image into a black and white image to acquire a first black and white image; to convert the detected second color image into a black and white image to acquire a second black and white image; to apply the acquired first black and white image and the acquired second black and white image to a predetermined trained algorithm model to output a remote photoplethysmography (rPPG) signal waveform of the subject; to calculate a first stress index based on the first heart rate variability; to calculate a second stress index based on the second heart rate variability; and to output a stress index of the subject based on the first stress index and the second stress index.

A gait evaluation apparatus that evaluates a training gait of a paralyzed patient suffering from paralysis in a leg includes an acquisition unit configured to acquire a plurality of motion amounts of a paralyzed body portion according to a gait motion and an evaluation unit configured to evaluate that the gait motion is an abnormal gait in a case where at least one of the motion amounts acquired by the acquisition unit meets any one of a plurality of abnormal gait criteria set in advance. The abnormal gait criteria include at least two or more first criteria, which are criteria relevant to motion amounts of different parts of the paralyzed body portion, or at least two or more second criteria, which are criteria relevant to motion amounts of the same part of the paralyzed body portion in different directions.

A method and apparatus for monitoring a human or animal subject in a room using video imaging of the subject and analysis of the video image to detect and quantify movement of the subject and to derive an estimate of vital signs such as heart rate or breathing rate. The method includes techniques for de-correlating global intensity variations such as sunlight changes, compensating for noise, eliminating areas not of interest in the image, and quickly and automatically finding regions of interest for detecting subject movement and estimating vital signs. A logic machine is used for interpreting detected movement of the subject, and an artificial neural network is used to calculate a confidence measure for the vital signs estimates from signal quality indices. The confidence measure may be used with a normal density filter to output estimates of the vital signs.

A processing device receives, from a three-dimensional (3D) motion capture system, initial data representing an initial orientation of a subject user's body in an initial position. The processing device further receives x-ray data representing at least the portion of the subject user's body in the initial position. The processing device determines an actual orientation of at least one bone or joint from the portion of the subject user's body in the initial position as represented in the x-ray data and calibrates the initial orientation of the 3D motion capture system to reflect the actual orientation of the at least one bone or joint in the initial position.

The present invention relates to a device, system and method for determining a vital sign of a person. To improve accuracy and reliability of vital sign determination, the device comprises an input unit (20) for obtaining a vital sign related signal of at least a body part of the person, from which a vital sign can be derived, a body part position determining unit (21) for determining if said body part of the person is in contact with a support or not and generating a contact signal indicating if said body part is in contact with the support or not, a quality metric setting unit (22) for setting, based on said contact signal, a quality metric for use in the determination of a vital sign of the person, and a vital sign deriving unit (23) for deriving a vital sign from the obtained vital sign related signal, wherein the set quality metric is used in the derivation of the vital sign and/or in a judgment of the reliability of a derived vital.

A performance scanning system that operates to detect and measure surface parameters of a portion of an athlete and uses the surface parameters to determine the likelihood that the athlete's physical performance has been or will be impaired.

Systems, methods and media are disclosed for identifying the crossing of a virtual barrier. A person in a 3D image of a room may be circumscribed by a bounding box. The position of the bounding box may be monitored over time, relative to the virtual barrier. If the bounding box touches or crosses the virtual barrier, an alert may be sent to the person being monitored, a caregiver or a clinician. Bounding box tracking may be used in addition to or instead of an initial tracking process, such as skeletal tracking.

The disclosed embodiments provide systems and methods for predicting presence of one or more neurological deficits. The system may include a microphone, a camera, one or more memory devices storing instructions, and one or more processors configured to execute the instructions to extract audio information including a period density entropy coefficient and a mel frequency cepstral coefficient from an audio feed received from the microphone. Additionally, the instructions may cause the processor to determine position and depth information of eye movement from a video feed received from the camera and detect features of interest including facial landmarks, spatial orientation of limbs, and positional information of limb movements from the video feed. The one or more processors may further extract the features of interest from the video feed and process the extracted features of interest by aligning the extracted features of interest to a common reference.