Advancements in Noncontact, Multiparameter Physiological Measurements Using a Webcam

• Published in: IEEE transactions on biomedical engineering Vol. 58; no. 1; pp. 7 - 11
• Main Authors: Poh, Ming-Zher, McDuff, Daniel J., Picard, Rosalind W.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.01.2011; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Adult; Algorithms; Autonomic nervous system; Biological and medical sciences; Biomedical measurements; blood volume pulse (BVP); Female; Frequency measurement; Fundamental and applied biological sciences. Psychology; Hafnium; Heart rate; Heart rate variability; heart rate variability (HRV); Humans; Image Processing, Computer-Assisted - methods; independent component analysis (ICA); Internet; Male; Monitoring, Physiologic - instrumentation; Monitoring, Physiologic - methods; noncontact; Peripheral nervous system. Autonomic nervous system. Neuromuscular transmission. Ganglionic transmission. Electric organ; photoplethysmography (PPG); Physiology; remote sensing; Resonant frequency; respiration; Sensors; Telemedicine - instrumentation; Telemedicine - methods; Vertebrates: nervous system and sense organs; Video Recording - instrumentation; Human; noncontact; Image interpretation; blood volume pulse (BVP); Variability; Independent component analysis; heart rate variability (HRV); photoplethysmography (PPG); Colorimetry; respiration; Video recording; Remote sensing; Heart rate; Blood volume; Autonomic nervous system; independent component analysis (ICA); Respiratory frequency; Photoplethysmography; Measurement method; Face; Biomedical engineering; Non contact measurement
• ISSN: 0018-9294; 1558-2531; 1558-2531
• DOI: 10.1109/TBME.2010.2086456

We present a simple, low-cost method for measuring multiple physiological parameters using a basic webcam. By applying independent component analysis on the color channels in video recordings, we extracted the blood volume pulse from the facial regions. Heart rate (HR), respiratory rate, and HR variability (HRV, an index for cardiac autonomic activity) were subsequently quantified and compared to corresponding measurements using Food and Drug Administration-approved sensors. High degrees of agreement were achieved between the measurements across all physiological parameters. This technology has significant potential for advancing personal health care and telemedicine.