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      Robust Pulse Rate From Chrominance-Based rPPG

      IEEE Transactions on Biomedical Engineering
      Institute of Electrical and Electronics Engineers (IEEE)

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

          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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            Heart rate measurement based on a time-lapse image.

            Using a time-lapse image acquired from a CCD camera, we developed a non-contact and non-invasive device, which could measure both the respiratory and pulse rate simultaneously. The time-lapse image of a part of the subject's skin was consecutively captured, and the changes in the average image brightness of the region of interest (ROI) were measured for 30s. The brightness data were processed by a series of operations of interpolation as follows a first-order derivative, a low pass filter of 2 Hz, and a sixth-order auto-regressive (AR) spectral analysis. Fourteen sound and healthy female subjects (22-27 years of age) participated in the experiments. Each subject was told to keep a relaxed seating posture with no physical restriction. At the same time, heart rate was measured by a pulse oximeter and respiratory rate was measured by a thermistor placed at the external naris. Using AR spectral analysis, two clear peaks could be detected at approximately 0.3 and 1.2 Hz. The peaks were thought to correspond to the respiratory rate and the heart rate. Correlation coefficients of 0.90 and 0.93 were obtained for the measurement of heart rate and respiratory rate, respectively.
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              Motion-compensated noncontact imaging photoplethysmography to monitor cardiorespiratory status during exercise.

              With the advance of computer and photonics technology, imaging photoplethysmography [(PPG), iPPG] can provide comfortable and comprehensive assessment over a wide range of anatomical locations. However, motion artifact is a major drawback in current iPPG systems, particularly in the context of clinical assessment. To overcome this issue, a new artifact-reduction method consisting of planar motion compensation and blind source separation is introduced in this study. The performance of the iPPG system was evaluated through the measurement of cardiac pulse in the hand from 12 subjects before and after 5 min of cycling exercise. Also, a 12-min continuous recording protocol consisting of repeated exercises was taken from a single volunteer. The physiological parameters (i.e., heart rate, respiration rate), derived from the images captured by the iPPG system, exhibit functional characteristics comparable to conventional contact PPG sensors. Continuous recordings from the iPPG system reveal that heart and respiration rates can be successfully tracked with the artifact reduction method even in high-intensity physical exercise situations. The outcome from this study thereby leads to a new avenue for noncontact sensing of vital signs and remote physiological assessment, with clear applications in triage and sports training.
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                Journal
                10.1109/TBME.2013.2266196

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