Optical heartrate tracking
First Claim
1. One or more hardware-based computer-readable memory devices not consisting of propagated signals having computer readable instructions stored thereupon that, when executed by a computer, implement:
- a face alignment and preparation pipeline configured to receive respective streams of infrared video frames and visible light video frames which include a facial image of a human subject and simultaneously process the received infrared video frames and visible light video frames to output a decomposed, frame-aligned, facial skin-only signal measurement comprising spatially-corresponding infrared light and visible light graphs that are phase-shifted so that as values in the infrared light graph are increasing, values in the spatially-corresponding visible light graph are decreasing, and vice-versa;
a signal-finding pipeline configured to;
i) receive the decomposed, frame-aligned, facial skin-only signal measurement, ii) compare the signal measurement in a current frame to a cached decomposed version of a head image in a previous frame, iii) sum up and average pixels having deltas between head images in the current frame and previous frame that trend in a consistent direction, and are within a set number of standard deviations of brightness, iv) generate a measurement of noisiness per pixel, v) apply at least one filter to the summed and averaged pixels, the filter being weighted by the noisiness measurement, vi) create a time-space representation of low-amplitude deltas in a skin-only facial image;
a signal-extracting pipeline configured to a) apply time-space smoothing or frequency-space smoothing to the time-space representation, b) apply a discrete Fourier transform to transform the time-space representation into a frequency-space representation for each of the infrared and visible streams, c) merge the frequency-space representations weighted by graph noise level; and
a heartrate identification pipeline configured to identify a heartrate of the human subject from the merged frequency-space representations.
2 Assignments
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Accused Products
Abstract
Heartrate tracking is performed entirely optically without the subject being required to wear any monitoring equipment by processing a combination of signals representing frames of video of the sinusoidal motion of a subject'"'"'s facial skin color changes captured by both IR and visible light (e.g., RGB—red/green/blue) cameras. The IR and RGB graphs that result from the processing are perfectly phase-shifted so that when the IR signal is going down in amplitude, the RGB signal is going up. Such phase-shifting enables the optical heartrate tracking to utilize diverse input feeds so that a tracked signal is accepted as the user'"'"'s true heartrate when both IR and RGB signals are well correlated.
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Citations
9 Claims
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1. One or more hardware-based computer-readable memory devices not consisting of propagated signals having computer readable instructions stored thereupon that, when executed by a computer, implement:
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a face alignment and preparation pipeline configured to receive respective streams of infrared video frames and visible light video frames which include a facial image of a human subject and simultaneously process the received infrared video frames and visible light video frames to output a decomposed, frame-aligned, facial skin-only signal measurement comprising spatially-corresponding infrared light and visible light graphs that are phase-shifted so that as values in the infrared light graph are increasing, values in the spatially-corresponding visible light graph are decreasing, and vice-versa; a signal-finding pipeline configured to;
i) receive the decomposed, frame-aligned, facial skin-only signal measurement, ii) compare the signal measurement in a current frame to a cached decomposed version of a head image in a previous frame, iii) sum up and average pixels having deltas between head images in the current frame and previous frame that trend in a consistent direction, and are within a set number of standard deviations of brightness, iv) generate a measurement of noisiness per pixel, v) apply at least one filter to the summed and averaged pixels, the filter being weighted by the noisiness measurement, vi) create a time-space representation of low-amplitude deltas in a skin-only facial image;a signal-extracting pipeline configured to a) apply time-space smoothing or frequency-space smoothing to the time-space representation, b) apply a discrete Fourier transform to transform the time-space representation into a frequency-space representation for each of the infrared and visible streams, c) merge the frequency-space representations weighted by graph noise level; and a heartrate identification pipeline configured to identify a heartrate of the human subject from the merged frequency-space representations. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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Specification