# US 9,436,984 B2 · Compensating for motion induced artifacts in a physiological signal extracted from a single video > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 9,436,984 B2 - Document ID: US9436984B2 - Status: Granted - Kind: B2 - Application number: 13/923,588 - Filed: 2013-06-21 - Published: 2014-12-25 - Granted: 2016-09-06 - Earliest claimed: 2013-06-21 - Assignees: Xerox Corporation - Applicants: Xerox Corporation - Inventors: Beilei Xu; Lalit Keshav Mestha; Survi Kyal; Himanshu J. Madhu - Web page: https://patentgrep.com/patent/US9436984B2 ## CPC - G06T 5/50: using two or more images, e.g. averaging or subtraction - G06T 5/73: Deblurring; Sharpening - G06T 2207/10016: Video; Image sequence - G06T 2207/10024: Color image - G06T 2207/20201: Motion blur correction - G06T 2207/30088: Skin; Dermal - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ## Abstract What is disclosed is a system and method for compensating for motion induce artifacts in a physiological signal obtained from a video. In one embodiment, a video of a first and second region of interest of a subject being monitored for a desired physiological function is captured by a video device. The first region is an area of exposed skin wherein a desired signal corresponding to the physiological function can be registered. The second region is an area where movement is likely to induce motion artifacts into that signal. The video is processed to isolate pixels in the image frames associated with these regions. Pixels of the first region are processed to obtain a time-series signal. A physiological signal is extracted from the time-series signal. Pixels of the second region are analyzed to identify motion. The physiological signal is processed to compensate for the identified motion. ## Claims ### Claim 1 A method for compensating for motion induced artifacts in physiological signals obtained from a single video captured by a single video imaging device of a subject being monitored for a desired physiological function in a non-contact, remote sensing environment, the method comprising: receiving a video comprising a plurality of time-sequential image frames captured by a video imaging device of at least a first and second region of interest of a subject being monitored for a desired physiological function, said first region being an area of exposed skin wherein a desired signal corresponding to said physiological function can be registered by the video imaging device, said second region being an area where a movement by said subject is likely to induce motion artifacts into said signal; processing said video to isolate pixels in said image frames associated with each of said first and second regions of interest; processing pixels of said isolated first region to generate a time-series signal; extracting, from said time-series signal, a physiological signal corresponding to said desired physiological function; analyzing pixels of said isolated second region to identify time intervals when movement by said subject has occurred; and for each of said identified time intervals when movement has occurred: determining an amount of movement over the current interval; and in response to said movement being above a maximum threshold, discarding a segment of said physiological signal corresponding to said current interval, otherwise in response to said movement being below a minimum threshold, leaving a segment of said physiological signal corresponding to the current interval as-is, otherwise replacing said segment with a default segment. ### Claim 2 (depends on 1) The method of claim 1, wherein said video device is any of: a RGB video device, a 3D video device, an infrared video device, a multi-spectral video device, a hyperspectral video device, and a hybrid device comprising any combination hereof. ### Claim 3 (depends on 1) The method of claim 1, wherein said video device is mounted on a robot. ### Claim 4 (depends on 1) The method of claim 1, wherein said first and second regions of interest are any of: the same region, and overlapping regions. ### Claim 5 (depends on 1) The method of claim 1, wherein said second region of interest is any of: hands, arms, legs, arm with or without covers. ### Claim 6 (depends on 1) The method of claim 1, wherein said first and second regions of interest are isolated in said image frames using any of: pixel classification, object identification, facial recognition, color, texture, spatial features, spectral information, pattern recognition, and a user input. ### Claim 7 (depends on 1) The method of claim 1, wherein analyzing pixels of said isolated second region to identify time intervals when a movement occurred is performed by any of: object tracking, object detection, frame differencing, and a user input. ### Claim 8 (depends on 1) The method of claim 1, wherein analyzing pixels of said isolated second region to identify at least one time interval when movement occurred comprises any of: a change in center pixel locations of said isolated second region relative to a fixed position; a change in sizes of said isolated second region relative to a fixed size; a change in shapes of said isolated second region; and a residual from frame differencing. ### Claim 9 (depends on 1) The method of claim 1, wherein said desired physiological function is a cardiac function, and said processed physiological signal is a cardiac signal. ### Claim 10 (depends on 9) The method of claim 9, further comprising analyzing said cardiac signal to determine any of: heart rate variability, cardiac pulse frequency, and pulse transit time. ### Claim 11 (depends on 9) The method of claim 9, further comprising using said cardiac signal to determine an occurrence of any of: Cardiac Arrhythmia, Cardiac Stress, Cardiac Failure, and Heart Disease. ### Claim 12 (depends on 1) The method of claim 1, wherein said desired physiological function is a respiratory function and said processed physiological signal is a respiratory signal. ### Claim 13 (depends on 12) The method of claim 12, further comprising analyzing said respiratory signal to determine any of: pulmonary volume, minute ventilation, and respiration rate. ### Claim 14 (depends on 12) The method of claim 12, further comprising using said respiratory signal to determine an occurrence of any of: Sudden Infant Death Syndrome, Respiratory Distress, Respiratory Failure, and Pulmonary Disease. ### Claim 15 (depends on 1) The method of claim 1, wherein said video is a live streaming video and said processed physiological signal is generated in real-time. ### Claim 16 (depends on 1) The method of claim 1, further comprising communicating said processed physiological signal to any of: a storage device, a display device, and a remote device over a network. ### Claim 17 A system for compensating for motion induced artifacts in physiological signals obtained from a single video captured by a single video imaging device of a subject being monitored for a desired physiological function in a non-contact, remote sensing environment, the system comprising: a video imaging device for capturing video comprising a plurality of time-sequential image frames; and a processor in communication with a memory and said storage device, said processor executing machine readable program instructions for performing the steps of: receiving a video captured by said video imaging device of at least a first and second region of interest of a subject being monitored for a desired physiological function, said first region being an area of exposed skin wherein a desired signal corresponding to said physiological function can be registered by the video imaging device, said second region being an area where a movement by said subject is likely to induce motion artifacts into said signal; processing said video to isolate pixels in said image frames associated with each of said first and second regions of interest; processing pixels of said isolated first region to generate a time-series signal; extracting, from said time-series signal, a physiological signal corresponding to said desired physiological function; analyzing pixels of said isolated second region to identify time intervals when movement by said subject has occurred; and for each of said identified time intervals when movement has occurred: determining an amount of movement over the current interval; and in response to said movement being above a maximum threshold, discarding a segment of said physiological signal corresponding to said current interval, otherwise in response to said movement being below a minimum threshold, leaving a segment of said physiological signal corresponding to the current interval as-is, otherwise replacing said segment with a default segment. ### Claim 18 (depends on 17) The system of claim 17, wherein said video device is any of: a RGB video device, a 3D video device, an infrared video device, a multi-spectral video device, a hyperspectral video device, and a hybrid device comprising any combination hereof. ### Claim 19 (depends on 17) The system of claim 17, wherein said video device is mounted on a robot. ### Claim 20 (depends on 17) The system of claim 17, wherein said first and second regions of interest are any of: the same region, and overlapping regions. ### Claim 21 (depends on 17) The system of claim 17, wherein said second region of interest is any of: hands, arms, legs, arm with or without covers. ### Claim 22 (depends on 17) The system of claim 17, wherein said first and second regions of interest are isolated in said image frames using any of: pixel classification, object identification, facial recognition, color, texture, spatial features, spectral information, pattern recognition, and a user input. ### Claim 23 (depends on 17) The system of claim 17, wherein analyzing pixels of said isolated second region to identify time intervals when a movement occurred is performed by any of: object tracking, object detection, frame differencing, and a user input. ### Claim 24 (depends on 17) The system of claim 17, wherein analyzing pixels of said isolated second region to identify at least one time interval when movement occurred comprises any of: a change in center pixel locations of said isolated second region relative to a fixed position; a change in sizes of said isolated second region relative to a fixed size; a change in shapes of said isolated second region; and a residual from frame differencing. ### Claim 25 (depends on 17) The system of claim 17, wherein said desired physiological function is a cardiac function, and said processed physiological signal is a cardiac signal. ### Claim 26 (depends on 25) The system of claim 25, further comprising analyzing said cardiac signal to determine any of: heart rate variability, cardiac pulse frequency, and pulse transit time. ### Claim 27 (depends on 25) The system of claim 25, further comprising using said cardiac signal to determine an occurrence of any of: Cardiac Arrhythmia, Cardiac Stress, Cardiac Failure, and Heart Disease. ### Claim 28 (depends on 17) The system of claim 17, wherein said desired physiological function is a respiratory function and said processed physiological signal is a respiratory signal. ### Claim 29 (depends on 28) The system of claim 28, further comprising analyzing said respiratory signal to determine any of: pulmonary volume, minute ventilation, and respiration rate. ### Claim 30 (depends on 28) The system of claim 28, further comprising using said respiratory signal to determine an occurrence of any of: Sudden Infant Death Syndrome, Respiratory Distress, Respiratory Failure, and Pulmonary Disease. ### Claim 31 (depends on 17) The system of claim 17, wherein said video is a live streaming video and said processed physiological signal is generated in real-time. ### Claim 32 (depends on 17) The system of claim 17, further comprising communicating said processed physiological signal to any of: a storage device, a display device, and a remote device over a network.