Researchers at MIT’s Computer Science and Artificial Intelligence Laboratory have developed a new algorithm that can accurately measure the heart rates of people depicted in ordinary digital video by analyzing imperceptibly small head movements that accompany the rush of blood caused by the heart’s contractions.
In tests, the algorithm gave pulse measurements that were consistently within a few beats per minute of those produced by electrocardiograms (EKGs). It was also able to provide useful estimates of the time intervals between beats, a measurement that can be used to identify patients at risk for cardiac events.
The algorithm works by combining several techniques common in the field of computer vision. First, it uses standard face recognition to distinguish the subject’s head from the rest of the image. Then it randomly selects 500 to 1,000 distinct points, clustered around the subjects’ mouths and noses, whose movement it tracks from frame to frame.
A video-based pulse-measurement system could be useful for monitoring newborns or the elderly, whose sensitive skin could be damaged by frequent attachment and removal of EKG leads.
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Transcript
00:00:00 in this video we demonstrate that it's possible to analyze cardiac pulse from regular videos by extracting the imperceptible motions of the head caused by blood flow recent work has enabled the extraction of pulse from videos based on color changes in the skin due to blood circulation if you've seen someone blush you know that pumping blood to the face can produce a color
00:00:20 change in contrast our approach leverages a perhaps more surprising effect the inflow of blood doesn't just change the Skin's color it also causes the head to move this movement is too small to be visible with the naked eye but we can use video amplification to reveal it believe it or not we all move like bobbleheads with different motions at
00:00:42 our heart rate but at a much smaller amplitude than this now you might wonder what causes the head to move like this at each cardiac cycle the heart's left ventricle contracts and ejects blood at high speed to the aorta during the cycle roughly 12 gr of blood flow to the Head from the aorta by the cded artery on either side of the neck it is this influx of blood that generates a force
00:01:04 on the head due to Newton's third law the force of the blood on the head equals the force of the head acting on the blood causing a reactionary cyclical head movement to demonstrate this process we created a toy model using a transparent mannequin head with rubber tubes stand for simplified arteries instead of pumping blood we will pump compressed air provided by this air tank
00:01:26 and I can release the air using this valve now watch what happens as I open and close close the valve once a second similar to a normal heart rate ready here this motion is fairly similar to the Amplified motion of real heads that we've seen before we exploit this effect to develop a technique that can analyze pulse and regular videos of a person's head our method takes an input video of
00:01:48 a stationary person and returns a one-dimensional signal corresponding to the Head motions from this signal we can extract an average pulse rate as well as beat locations for deeper clinical analysis we Begin by locating the face using a face detector and selecting feature points within the area the feature points are tracked from frame to frame of the video using the Lucas Kady
00:02:10 tracking algorithm we use the vertical or Y component of each of the feature point trajectories for our analysis next we temporarily filter the signals to a pass band encompassing a normal pulse range while excluding extraneous Motions like respiration we decompose the multi-dimensional motion of the head described by the trajectories into sub
00:02:30 motions using principal component analysis or PCA PCA Returns the main directions along which the head moves we project the motion of the head onto each component and choose the signal with the clearest dominant frequency we use the dominant frequency to obtain an average pulse rate finally we perform Peak detection on the chosen signal to obtain beat locations for further analysis such
00:02:52 as heart rate variability we tested our method on different people varying in skin tone and gender and were're able to get nearly exact pulse rates compared to an ECG device in addition our method produced similar beat length distributions to the ECG an exciting result that shows that we can capture more subtle information about the heart
00:03:11 than just an average rate finally our method is robust to different views of the head we obtained a pulse from a sleeping newborn from the back of a subject's head and even when a person is wearing a mask
