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.

An apparatus, method and computer program is described comprising: receiving video data for a scene; determining a movement measurement for at least some of a plurality of subframes of the video data; weighting the movement measurements to generate a plurality of weighted movement measurements, wherein the weighting is dependent on the subframe; and generating a movement indication for the scene from a combination of some or all of the weighted movement measurements.

The system for cardiovascular parameter data quality determination can include a user device and a computing system, wherein the user device can include one or more sensors, the computing system, and/or any suitable components. The computing system can optionally include a data quality module, a cardiovascular parameter module, a storage module, and/or any suitable modules. The method for cardiovascular parameter data quality determination can include acquiring data and determining a quality of the data. The method can optionally include processing the data, and/or determining a cardiovascular parameter, training a data quality module, any suitable steps.

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.

Provided is a video-based method and system for accurately estimating heart rate and facial blood volume distribution, and the method mainly comprises the following steps: firstly, carrying out face detection of video frame containing human face, and extracting face image sequence and face key position points sequence in time dimension; secondly, compressing these sequence of face image and face key position points to obtain the facial signals in time dimension; thirdly, estimating facial blood volume distribution by facial signals mentioned in third step; finally, estimating heart rate values by using model based on deep learning technology and the spectrum analysis method respectively, then fusing the estimation results by Kalman filter to promote the accuracy of heart rate estimation.

A health management system using contactless physiological measurement technology is disclosed. The health management system principally comprises a camera and a first processor, of which the camera is faced to a user for capturing a user image. The first processor is particularly configured to have a face detection unit and an activity index calculating unit therein. By such arrangement, after receiving the user image from the camera, the first processor detects a face portion from the user image, thereby subsequently extracting a PPG signal from the face portion. Consequently, after completing at least one process of the PPG signal, multiple indexes for describing a user's health activity are generated. The health activity indexes include health index, activity index, stability index, relaxation index, metabolism index, and balance index. Therefore, the first processor achieves an evaluation of the user's health activity state according to the forgoing health activity indexes.

The present application discloses a method of adjusting a parameter, the parameter being used to derive a physiological characteristic of an individual from an image of the user, the method comprising the steps of: obtaining the parameter for the individual; obtaining a corresponding parameter for a plurality of other individuals within a cohort of the individual; comparing the parameter for the individual with a statistically significant parameter for the plurality of other individuals; and adjusting the parameter for the individual in accordance with the difference between the parameter for the individual and the statistically significant parameter for the plurality of other individuals.

The present invention relates to a device, system and method for improved non-invasive and objective detection of pulse of a subject. The device comprises an input unit (2a) configured to obtain a series of images of a skin region of the subject and a processing unit (2b) for processing said series of images by detecting pulse-related motion of the skin within the skin region from the series of images, generating a motion map of the skin region from the detected pulse-related motion, comparing the generated motion map with an expected motion map of the skin region, and determining the presence of pulse within the skin region based on the comparison.

An information processing apparatus is described. This determines a physiological parameter of an individual, the apparatus comprising: image circuitry configured to obtain a series of images of a skin exposed region of the individual; and processing circuitry configured to perform a periodogram on at least one of the red, green and blue channels of the skin exposed region of the series of images to obtain frequency components of the channel; and to determine the physiological parameter based on the periodogram.

A remote photoplethysmography (RPPG) system for estimating vital signs of a person is provided. The RPPG system is configured to receive a set of imaging photoplethysmography (iPPG) signals measured from different regions of a skin of a person. The RPPG system is further configured to determine frequency coefficients at the frequency bins of the quantized frequency spectrum of the measured iPPG signals by minimizing a distance between the measured iPPG signals and corresponding iPPG signals reconstructed from the determined frequency coefficients, while enforcing joint sparsity of the determined frequency coefficients subject to the sparsity level constraint, such that the determined frequency coefficients of different iPPG signals have the non-zero values at the same frequency bins; and output one or a combination of the determined frequency coefficients, the iPPG signals reconstructed from the determined frequency coefficients, and a vital sign signal corresponding to the reconstructed iPPG signals.