Abstract:
What is disclosed is a system and method for determining respiration rate from a video of a subject. In one embodiment, a video is received comprising plurality of time-sequential image frames of a region of a subject's body. Features of pixels are extracted from that region from each image frame and vectors formed from these features. Each image frame has an associated feature vector. A N×M video matrix of the vectors of length N is constructed such that a total number of columns M in the video matrix correspond to a time duration over which the subject's respiration rate is to be determined. The video matrix is processed to obtain a matrix of eigenvectors where principal axes of variations due to motion associated with respiration are contained in a first few eigenvectors. One eigenvector is selected from the first few eigenvectors. A respiration rate is obtained from the selected eigenvector.
Abstract:
What is disclosed is a system and method for compensating for motion induced artifacts in physiological signals extracted from a video of a subject being monitored for a physiological function in a non-contact, remote sensing environment. The present method identifies a center frequency from a physiological signal obtained from processing a prior video segment. Since a moment to moment change in pulse frequency from one video segment to a next is not very large, signals obtained from sequential video segments can be repeatedly processed and an adaptive band-pass filter repeatedly re-configured and used to filter a next video segment, and so on. Using the teachings disclosed herein, a motion-compensated continuous cardiac signal can be obtained for the subject for continuous monitoring of the subject's cardiac function via video imaging. The teachings hereof provide an effective means for compensating for movement by the subject during video acquisition. Various embodiments are disclosed.
Abstract:
What is disclosed is a system and method for compensating for motion during processing of a video of a subject being monitored for physiological function assessment. In one embodiment, image frames are received. Successive batches of N video frames are processed to isolate pixels associated with a body region of the subject where a physiological signal is registered by the camera. The pixels are processed to obtain a time-series signal for each batch. A determination is made whether movement during video acquisition of this batch of image frames exceeds a threshold level. If so then a size N of the next batch of image frames is changed to: N=N+M1, where N+M1≦Nmax. Otherwise, a size N of a next batch is changed to: N=N−M2, where N−M2≧Nmin. Thereafter, processing repeats in a real-time continuous manner as the next batch of the N image frames is received. Various embodiments are disclosed.
Abstract:
What is disclosed is a system and method for determining a subject of interest's arterial pulse transit time from time-varying source signals generated from video images. In one embodiment, a video imaging system is used to capture a time-varying source signal of a proximal and distal region of a subject of interest. The image frames are processed to isolate localized areas of a proximal and distal region of exposed skin of the subject. A time-series signal for each of the proximal and distal regions is extracted from the source video images. A phase angle is computed with respect to frequency for each of the time-series signals to produce respective phase v/s frequency curves for each region. Slopes within a selected cardiac frequency range are extracted from each of the phase curves and a difference is computed between the two slopes to obtain an arterial pulse transit time for the subject.
Abstract:
What is disclosed is a system and method for estimating cardiac pulse rate from a video of a subject being monitored for cardiac function. In one embodiment, batches of overlapping image frames are continuously received and processed by isolating regions of exposed skin. Pixels of the isolated regions are processed to obtain a time-series signal per region and a physiological signal is extracted from each region's time-series signals. The physiological signal is processed to obtain a cardiac pulse rate for each region. The cardiac pulse rate for each region is compared to a last good cardiac pulse rate from a previous batch to obtain a difference. If the difference exceeds a threshold, the cardiac pulse rate is discarded. Otherwise, it is retained. Once all the regions have been processed, the retained cardiac pulse rate with a minimum difference becomes the good cardiac pulse rate for comparison on a next iteration.