Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A method and apparatus for extracting a breathing rate estimate from video images of a respiring subject. Signals corresponding to the spatial coordinates of feature points tracked through the video sequence are filtered and excessively large changes are attenuated to reduce movement artefacts. The signals are differentiated and signals which correlate most strongly with other signals are selected. The selected signals are subject to principal component analysis and the best quality of the top five principal components is selected and its frequency is used to calculate and output a breathing rate estimate. The method is particularly suitable for detecting respiration in subject in secure rooms where the video image is of substantially the whole room and the subject is only a small part of the image, and maybe covered or uncovered.

Abstract: 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 derive an estimate of vital signs such as heart rate or breathing rate. The method includes determination of whether the subject in the images is still or moving, and whether any of the regions from which vital signs are being detected are not on the subject. The subject's movement may be manually or automatically detected, and the determination of whether regions from which vital signs are being detected are not on the subject can be input manually, by displaying the regions to the user in a visually distinguishable manner, or automatically. Vital signs measurements are only displayed if the subject is determined as being still and if there are no regions in the image which are returning vital signs signals but are not determined as being on the subject.

Abstract: A method and apparatus for detecting fine movement of a subject in video images, and for distinguishing over noise and other image artefacts. The video images are processed to detect movement of image features through the sequence and to calculate how spatially distributed those moving features are across the image. The movement tracks of the features may be subject to principal component analysis and a spatial dispersion measure calculated by the product of the distance between tracked image features and the contributions of those image features to the most significant principal components. If the spatial dispersion measure is high then this is indicative of feature movement being dispersed widely across the image, whereas if it is low, it is indicative of the main feature movements being concentrated in one part of the image, and thus more likely to represent subject movement than noise.

Abstract: 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.

Abstract: A method and apparatus which combines multiple simultaneous signals thought to contain a common periodic component by performing principal component analysis on each of the multiple signals, finding the weight of the first principal component, and then adding the multiple signals together in a weighted sum according to the weight of the first principal component. The method and apparatus further includes a way of combining signals from successive overlapping time windows in real time by differentiating the signal and forming as each output signal sample the value of the preceding signal sample summed with the differential of the signal, weighted by weights based on the amplitude of the differential signal at that time point.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A method and apparatus for detecting fine movement of a subject in video images, and for distinguishing over noise and other image artefacts. The video images are processed to detect movement of image features through the sequence and to calculate how spatially distributed those moving features are across the image. The movement tracks of the features may be subject to principal component analysis and a spatial dispersion measure calculated by the product of the distance between tracked image features and the contributions of those image features to the most significant principal components. If the spatial dispersion measure is high then this is indicative of feature movement being dispersed widely across the image, whereas if it is low, it is indicative of the main feature movements being concentrated in one part of the image, and thus more likely to represent subject movement than noise.

Abstract: 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 derive an estimate of vital signs such as heart rate or breathing rate. The method includes determination of whether the subject in the images is still or moving, and whether any of the regions from which vital signs are being detected are not on the subject. The subject's movement may be manually or automatically detected, and the determination of whether regions from which vital signs are being detected are not on the subject can be input manually, by displaying the regions to the user in a visually distinguishable manner, or automatically. Vital signs measurements are only displayed if the subject is determined as being still and if there are no regions in the image which are returning vital signs signals but are not determined as being on the subject.

Abstract: A method and apparatus for extracting a breathing rate estimate from video images of a respiring subject. Signals corresponding to the spatial coordinates of feature points tracked through the video sequence are filtered and excessively large changes are attenuated to reduce movement artefacts. The signals are differentiated and signals which correlate most strongly with other signals are selected. The selected signals are subject to principal component analysis and the best quality of the top five principal components is selected and its frequency is used to calculate and output a breathing rate estimate. The method is particularly suitable for detecting respiration in subject in secure rooms where the video image is of substantially the whole room and the subject is only a small part of the image, and maybe covered or uncovered.

Abstract: 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.

Abstract: A method and apparatus which combines multiple simultaneous signals thought to contain a common periodic component by performing principal component analysis on each of the multiple signals, finding the weight of the first principal component, and then adding the multiple signals together in a weighted sum according to the weight of the first principal component. The method and apparatus further includes a way of combining signals from successive overlapping time windows in real time by differentiating the signal and forming as each output signal sample the value of the preceding signal sample summed with the differential of the signal, weighted by weights based on the amplitude of the differential signal at that time point.

Abstract: 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.