Abstract:
What is disclosed is a video system and method that accounts for differences in imaging characteristics of differing video systems used to acquire video of respective regions of interest of a subject being monitored for a desired physiological function. In one embodiment, video is captured using N video imaging devices, where N≧2, of respective regions of interest of a subject being monitored for a desired physiological function (i.e., a respiratory or cardiac function). Each video imaging device is different but has complimentary imaging characteristics. A reliability factor f is determined for each of the devices in a manner more fully disclosed herein. A time-series signal is generated from each of the videos. Each time-series signal is weighted by each respective reliability factor and combined to obtain a composite signal. A physiological signal can be then extracted from the composite signal. The processed physiological signal corresponds to the desired physiological function.
Abstract:
What is disclosed is a system and method for detecting an arrhythmic or non-arrhythmic event from a cardiac signal obtained from a subject. In one embodiment, a plurality of different cardiac signals are received and are transformed into frequency domain signals which, in turn, are changed such that a dominant frequency in each of the signals is substantially aligned to form a matrix of feature vectors. The feature matrix is used to train a classifier. A cardiac signal from the subject is received and transformed to a frequency domain signal. The frequency domain signal is changed such that a dominant is substantially aligned with a dominant frequency of signals used to train the classifier. The subject's frequency domain signal is provided as a new feature vector to the classifier. The classifier uses the new feature vector to classify the subject as having an arrhythmic or a non-arrhythmic event.
Abstract:
What is disclosed is a system and method identifying a type of cardiac event from cardiac signals obtained from a subject. In one embodiment, at least two clusters are formed. Each cluster is associated with a different cardiac event based on features of interest identified from various cardiac signal segments. At least one of the clusters is associated with a cardiac event which is an arrhythmia and one of the clusters is associated with a non-arrhythmia. A new cardiac signal segment of a subject is received. The signal segment is analyzed to identify features of interest. A distance is calculated between each of the clusters and the identified features of interest obtained from having analyzed the subject's cardiac signal segment. A cardiac event is identified for the subject based on the type of cardiac event associated with the cluster which the subject's features of interest had a shortest distance to.
Abstract:
What is disclosed is a system and method for increasing the accuracy of physiological signals obtained from video of a subject being monitored for a desired physiological function. In one embodiment, image frames of a video are received. Successive batches of image frames are processed. For each batch, pixels associated with an exposed body region of the subject are isolated and processed to obtain a time-series signal. If movement occurred during capture of these image frames that is below a pre-defined threshold level then parameters of a predictive model are updated using this batch's time-series signal. Otherwise, the last updated predictive model is used to generate a predicted time-series signal for this batch. The time-series signal is fused with the predicted time-series signal to obtain a fused time-series signal. The time-series signal for each batch is processed to obtain a physiological signal for the subject corresponding to the physiological function.
Abstract:
What is disclosed is a system and method for determining a pulse transit time for a subject. In one embodiment, the system comprises a handheld wireless cellular device configured with a sensor to acquire an electrocardiogram (ECG) signal from the subject and a photodetector generating a time-series signal in response to continuously sensing a reflection of source light off a region of exposed skin of the subject where a photoplethysmographic (PPG) signal can be detected by the photodetector. In one embodiment, the time-series signal is a PPG signal. In another embodiment, the time-series signal is processed to extract a PPG signal. A temporally overlapping segment of the PPG and ECG signals is analyzed to obtain a pulse transit time between a reference point on the PPG signal and a reference point on the ECG signal. The pulse transit time is used to assess pathologic conditions such as peripheral vascular disease.
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 determining arterial pulse transit time (PTT) for a subject. In one embodiment, time-series signals are received for each of a proximal and distal arterial site of a subject's body which represent blood volume changes in the microvascular tissue at each site. A proximal and distal analytic signal is obtained which has a first component being a waveform of the respective time-series signal and a second component being a transform of the respective waveform. A phase function is determined for the first and second components of each analytic signal. The phase function obtained for the proximal waveform is then subtracted from the phase function obtained for the distal waveform to get a phase difference. The phase difference is analyzed with the subject's heart rate to determine an arterial pulse wave transit time between the two proximal and distal sites.
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.
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 novel system and method for extracting photoplethysmographic (PPG) signals (i.e., cardiac signals) on a continuous basis from signals generated from video images captured of a subject being monitored for cardiac function in a non-contact remote sensing environment. In one embodiment, a time-series signal is received. The time-series signal is generated from video images captured of a region of exposed skin where a PPG signal of a subject of interest can be registered. The time-series signal is then divided into batches for processing, with successive batches having at least a 95% overlap with a previous batch. Each of the batches of time-series signals is processed to obtain a PPG signal from each batch. A mid-point of each of these PPG-signals is stitched together to obtain a continuous PPG signal for the subject. The continuous PPG signal for the subject can then viewed on a display device.