Systems and methods are described herein for monitoring and capturing information associated with target subjects, such as babies. For example, the systems and methods provide a capture device, such as a camera, that captures capture time of flight (TOF) data from a target subject. Using the TOF data, the systems and methods, via a display device associated with (e.g., paired to) the capture device, present information about the target subject, such as information indicating movement of the target subject, information indicating a breathing rate of the target subject, information indicating a heart rate of the target subject, and so on.

The present invention relates to a device, system and method for skin detection. To enable a reliable, accurate and fast detection the proposed device comprises an input interface (30) for obtaining image data of a scene, said image data comprising a time sequence of image frames, an extraction unit (31) for extracting a photoplethysmography (PPG) signal from a region of interest of said image data, a transformation unit (32) for transforming said PPG signal into a spectral signal, a sorting unit (33) for sorting said spectral signal to obtain a sorted spectral signal representing a descriptor, and a classifier (34) for classifying said region of interest as skin region of a living being or as non-skin region based on the descriptor.

A method and apparatus for estimating heart rate of a subject from a video image of the subject. Regions of interest are generated by: detecting and tracking feature points through the video image sequence, triangulating the feature points and generating square regions of interest corresponding to the in-circles of the triangles; or, according to size and location probability distributions which are defined to have a high probability for image areas away from strong intensity gradients and which generate good quality signals. In an alternative embodiment, the intensity variations from the square regions of interest through the frame sequence are taken as time series signals and those signals which have a strong peak in the power spectrum are selected and subject to principal component analysis. The principal component with a highest signal quality is selected and its frequency is found and used to estimate the heart rate.

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.

In a method of video monitoring of a subject, for example a driver of a vehicle, the video image is motion compensated by image registration techniques so that the subject's position in each frame of the video image is stable. A region of interest is defined on the skin of the subject and used to obtain a PPG signal. To compensate for variations in illumination of the subject caused by the subject's movement in the vehicle, the parameters of the calculated motion transformation used in the image registration are used to form an illumination model representing how the illumination of the subject would have changed because of the subject's motion. The illumination model is a linear or quadratic function fitted to the image intensity in the region of interest. Residuals between the fitted model and the image intensity form an illumination-compensated signal in which the photoplethysmographic signal is more clearly present. The illumination-compensated signal is analysed to obtain a PPG signal and from this estimates of one or more vital signs such as heart rate or breathing rate are obtained.

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 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 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.

The exemplified methods and systems employs non-invasively acquired biophysical measurements of a subject in a residue analysis that is structured as a three-dimensional volumetric object to which machine extractable features associated with a geometric associated aspect of the three-dimensional volumetric object may be derived and used for in the training and/or prediction of a disease state. The system generates a residue model from a point-cloud residue generated from an analysis of the plurality of biophysical signal data sets. The system generates a three-dimensional volumetric object from the point-cloud residue from which machine extractable features associated with the point-cloud residue maybe extracted.

A method for video evaluation of the heart rate and/or respiratory rate of a baby, in particular under dim or nocturnal conditions, in a device comprising a video camera and a source of infrared light, the method comprising the steps of: A1illuminating the baby with the infrared source, A2capturing video images of the baby, B1determining the position of the baby's head by finding an ellipse forming an outline of the head, B2identifying an area of interest centered on a selected ellipse, Cevaluating, by plethysmographic analysis of the area of interest, the heart rate and/or respiratory rate of the baby, and associated system.