308 research outputs found

    Noncontact imaging photoplethysmography to effectively access pulse rate variability

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    Noncontact imaging photoplethysmography (PPG) can provide physiological assessment at various anatomical locations with no discomfort to the patient. However, most previous imaging PPG (iPPG) systems have been limited by a low sample frequency, which restricts their use clinically, for instance, in the assessment of pulse rate variability (PRV). In the present study, plethysmographic signals are remotely captured via an iPPG system at a rate of 200 fps. The physiological parameters (i.e., heart and respiration rate and PRV) derived from the iPPG datasets yield statistically comparable results to those acquired using a contact PPG sensor, the gold standard. More importantly, we present evidence that the negative influence of initial low sample frequency could be compensated via interpolation to improve the time domain resolution. We thereby provide further strong support for the low-cost webcam-based iPPG technique and, importantly, open up a new avenue for effective noncontact assessment of multiple physiological parameters, with potential applications in the evaluation of cardiac autonomic activity and remote sensing of vital physiological signs

    A remote approach to measure blood perfusion from the human face

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    A CMOS camera-based imaging photoplethysmography (PPG) system has been previously demonstrated for the contactless measurement of skin blood perfusion over a wide tissue area. An improved system with a more sensitive CCD camera and a multi-wavelength RCLED ring light source was developed to measure blood perfusion from the human face. The signals acquired by the PPG imaging system were compared to signals captured concurrently from a conventional PPG finger probe. Experimental results from eight subjects demonstrate that the camera-based PPG imaging technique is able to measure pulse rate and blood perfusion

    Motion-compensated noncontact imaging photoplethysmography to monitor cardiorespiratory status during exercise

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    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

    Heart Rate Extraction from Novel Neck Photoplethysmography Signals.

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    This paper demonstrates for the first time how heart rate (HR) can be extracted from novel neck photoplethysmography (PPG). A novel algorithm is presented, which when tested in neck PPG signals recorded from 9 subjects at different respiratory rates, obtained good precision with respect to gold standard ECG signals. Mean absolute error (MAE), standard deviation error (SDAE) and root-mean-square error (RMSE) resulted in 1.22, 1.54 and 1.98 beats per minute (BPM), respectively. HRneck estimation showed strong correlation (R=0.94) with reference HRECG. Good agreement between both techniques was also demonstrated by Bland-Altman analysis. The bias between mean HR paired differences was -0.16 BPM and 95% limits of agreement (LoA) were (-4.7, 4.4). Comparatively, for widely used finger PPG, errors were slightly smaller (MAE=0.38 BPM, SDAE=0.48 BPM, RMSE=0.62BPM) and the correlation with reference ECG was also very close to 1 (R=0.99). Bias of -0.04 BPM and 95% LoA (-1.5, 1.4), also showed high degree of agreement. However, these findings show the potential the neck could have as an alternative body location for wearable monitors, aiming to reduce the number of sensing sites whilst still providing access to a wide variety of physiological parameters

    DistancePPG: Robust non-contact vital signs monitoring using a camera

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    Vital signs such as pulse rate and breathing rate are currently measured using contact probes. But, non-contact methods for measuring vital signs are desirable both in hospital settings (e.g. in NICU) and for ubiquitous in-situ health tracking (e.g. on mobile phone and computers with webcams). Recently, camera-based non-contact vital sign monitoring have been shown to be feasible. However, camera-based vital sign monitoring is challenging for people with darker skin tone, under low lighting conditions, and/or during movement of an individual in front of the camera. In this paper, we propose distancePPG, a new camera-based vital sign estimation algorithm which addresses these challenges. DistancePPG proposes a new method of combining skin-color change signals from different tracked regions of the face using a weighted average, where the weights depend on the blood perfusion and incident light intensity in the region, to improve the signal-to-noise ratio (SNR) of camera-based estimate. One of our key contributions is a new automatic method for determining the weights based only on the video recording of the subject. The gains in SNR of camera-based PPG estimated using distancePPG translate into reduction of the error in vital sign estimation, and thus expand the scope of camera-based vital sign monitoring to potentially challenging scenarios. Further, a dataset will be released, comprising of synchronized video recordings of face and pulse oximeter based ground truth recordings from the earlobe for people with different skin tones, under different lighting conditions and for various motion scenarios.Comment: 24 pages, 11 figure
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