Non-contact, automated cardiac pulse measurements using video imaging and blind source separation

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Abstract

Remote measurements of the cardiac pulse can provide comfortable physiological assessment without electrodes. However, attempts so far are non-automated, susceptible to motion artifacts and typically expensive. In this paper, we introduce a new methodology that overcomes these problems. This novel approach can be applied to color video recordings of the human face and is based on automatic face tracking along with blind source separation of the color channels into independent components. Using Bland-Altman and correlation analysis, we compared the cardiac pulse rate extracted from videos recorded by a basic webcam to an FDA-approved finger blood volume pulse (BVP) sensor and achieved high accuracy and correlation even in the presence of movement artifacts. Furthermore, we applied this technique to perform heart rate measurements from three participants simultaneously. This is the first demonstration of a low-cost accurate video-based method for contact-free heart rate measurements that is automated, motion-tolerant and capable of performing concomitant measurements on more than one person at a time. (c) 2010 Optical Society of America.

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Most cited references 19

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T P Jung, S Makeig, C. Humphries … (2000)

Eye movements, eye blinks, cardiac signals, muscle noise, and line noise present serious problems for electroencephalographic (EEG) interpretation and analysis when rejecting contaminated EEG segments results in an unacceptable data loss. Many methods have been proposed to remove artifacts from EEG recordings, especially those arising from eye movements and blinks. Often regression in the time or frequency domain is performed on parallel EEG and electrooculographic (EOG) recordings to derive parameters characterizing the appearance and spread of EOG artifacts in the EEG channels. Because EEG and ocular activity mix bidirectionally, regressing out eye artifacts inevitably involves subtracting relevant EEG signals from each record as well. Regression methods become even more problematic when a good regressing channel is not available for each artifact source, as in the case of muscle artifacts. Use of principal component analysis (PCA) has been proposed to remove eye artifacts from multichannel EEG. However, PCA cannot completely separate eye artifacts from brain signals, especially when they have comparable amplitudes. Here, we propose a new and generally applicable method for removing a wide variety of artifacts from EEG records based on blind source separation by independent component analysis (ICA). Our results on EEG data collected from normal and autistic subjects show that ICA can effectively detect, separate, and remove contamination from a wide variety of artifactual sources in EEG records with results comparing favorably with those obtained using regression and PCA methods. ICA can also be used to analyze blink-related brain activity.

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Analysis of fMRI data by blind separation into independent spatial components

Martin McKeown, Scott Makeig, Greg G. Brown … (1998)

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Absorption spectra of human fetal and adult oxyhemoglobin, de-oxyhemoglobin, carboxyhemoglobin, and methemoglobin.

Jacobus P. van Wouwe, A R Buursma, W Zijlstra (1991)

We determined the millimolar absorptivities of the four clinically relevant derivatives of fetal and adult human hemoglobin in the visible and near-infrared spectral range (450-1000 nm). As expected, spectral absorption curves of similar shape were found, but the small differences between fetal and adult hemoglobin absorptivity were important enough that they should be taken into account in multicomponent analysis of hemoglobin derivatives. Common pulse oximeters, however, involving light of 660 and 940 nm, are so insensitive to the presence of fetal hemoglobin that they can be used safely in neonates. The error in pulse oximetry caused by the presence of carboxyhemoglobin is insubstantial, but methemoglobin gives either an understimation or an overestimation at high or low oxygen saturation, respectively, the turning point being near 70% saturation.