Photoplethysmography imaging: a new noninvasive and noncontact method for mapping of the dermal perfusion changes

Wu, Ting; Blažek, Vladimír; Schmitt, H. J.

doi:10.1117/12.407646

Cited by 89 publications

(54 citation statements)

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“…Conceptually, it is a camera-based remote measurement method for the visualization of dermal blood vessels and for detecting perfusion in different skin areas. Among the pioneering studies, Wu and colleagues presented a charge coupled device (CCD) based IPPG system and proved its feasibility in assessing local changes of dermal blood volume [9]. Since then, there has been rapid growth in the literature pertaining to IPPG techniques.…”

Section: Imaging Photoplethysmographymentioning

confidence: 99%

“…Many reviews and books have been written on LDI, LSI, and PAT (for reviews, see [5]– [8]), which will not be repeated in this paper. Compared to LDI and LSI, IPPG has a relatively short history [9], [10]. With the recent evolution of these optical blood perfusion imaging technologies, it was soon realized that PPG could be extended to imaging as well.…”

Section: Introductionmentioning

confidence: 99%

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Photoplethysmography Revisited: From Contact to Noncontact, From Point to Imaging

Sun

Thakor

2016

IEEE Trans. Biomed. Eng.

425

238

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Photoplethysmography (PPG) is a non-invasive optical technique for detecting microvascular blood volume changes in tissues. Its ease of use, low cost and convenience make it an attractive area of research in the biomedical and clinical communities. Nevertheless, its single spot monitoring and the need to apply a PPG sensor directly to the skin limit its practicality in situations such as perfusion mapping and healing assessments or when free movement is required. The introduction of fast digital cameras into clinical imaging monitoring and diagnosis systems, the desire to reduce the physical restrictions, and the possible new insights that might come from perfusion imaging and mapping inspired the evolution of conventional PPG technology to imaging PPG (IPPG). IPPG is a noncontact method that can detect heart-generated pulse waves by means of peripheral blood perfusion measurements. Since its inception, IPPG has attracted significant public interest and provided opportunities to improve personal healthcare. This study presents an overview of the wide range of IPPG systems currently being introduced along with examples of their application in various physiological assessments. We believe that the widespread acceptance of IPPG is happening, and it will dramatically accelerate the promotion of this healthcare model in the near future.

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Section: Imaging Photoplethysmographymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Photoplethysmography Revisited: From Contact to Noncontact, From Point to Imaging

Sun

Thakor

2016

IEEE Trans. Biomed. Eng.

425

238

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show abstract

“…In 2000, Wu, Blazek, and Schmitt employed modern technology in the form of near infrared lighting and a monochrome CCD imager and near-infrared filter to examine perfusion and vascular structure at several locations including the leg, foot, arm, and hand. Again, technological limitations prevented the group from extracting hemodynamic or cardiovascular activity information over large surface areas; though, the team was able to observe power spectrum peaks corresponding with respiration and pulse activity resulting from hemodynamic changes observed in images of a finger which had been transilluminated 4 . In 2007, Takano and Ohta showed evidence of the ability to measure pulse rate using a consumer, visual spectrum video camera pointed at the face with ambient illumination 5 .…”

Section: Introductionmentioning

confidence: 99%

Effects of frame rate and image resolution on pulse rate measured using multiple camera imaging photoplethysmography

Blackford¹,

Estepp

2015

SPIE Proceedings

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Non-contact, imaging photoplethysmography uses cameras to facilitate measurements including pulse rate, pulse rate variability, respiration rate, and blood perfusion by measuring characteristic changes in light absorption at the skin's surface resulting from changes in blood volume in the superficial microvasculature. Several factors may affect the accuracy of the physiological measurement including imager frame rate, resolution, compression, lighting conditions, image background, participant skin tone, and participant motion. Before this method can gain wider use outside basic research settings, its constraints and capabilities must be well understood. Recently, we presented a novel approach utilizing a synchronized, nine-camera, semicircular array backed by measurement of an electrocardiogram and fingertip reflectance photoplethysmogram. Twenty-five individuals participated in six, five-minute, controlled head motion artifact trials in front of a black and dynamic color backdrop. Increasing the input channel space for blind source separation using the camera array was effective in mitigating error from head motion artifact. Herein we present the effects of lower frame rates at 60 and 30 (reduced from 120) frames per second and reduced image resolution at 329x246 pixels (one-quarter of the original 658x492 pixel resolution) using bilinear and zero-order downsampling. This is the first time these factors have been examined for a multiple imager array and align well with previous findings utilizing a single imager. Examining windowed pulse rates, there is little observable difference in mean absolute error or error distributions resulting from reduced frame rates or image resolution, thus lowering requirements for systems measuring pulse rate over sufficient length time windows.

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“…To extract the photoplethysmographic information from the video-stream, several approaches are described in the literature [9,19]. Recent developments include the use of independent component analysis (ICA, [1]), PCA [20] or a combination of the RGB-channels and were implemented and evaluated on our data.…”

Section: (E)mentioning

confidence: 99%

“…Most of those, however, are based on single modalities or do not allow HRV analysis with beat-to-beat accuracy. According to the definition introduced above, the video signal obtained from a subjects head is by itself a multimodal biosignal, as it contains the involuntary head motion [8] that originates from the mechanical impulse of the heart as well as the changes in optical property of the skin [9] caused by the superficial perfusion. Noise and artifacts might influence channels by varying degrees: While the BCG and the pulse-related head oscillations are very susceptible to motion artifacts, advanced video processing methods allow the extraction of PPG signals even if the subject is moving [10].…”

Section: Introductionmentioning

confidence: 99%

Beat-to-beat heart rate estimation fusing multimodal video and sensor data

Antink

Gao

Brüser

et al. 2015

Biomed. Opt. Express

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Coverage and accuracy of unobtrusively measured biosignals are generally relatively low compared to clinical modalities. This can be improved by exploiting redundancies in multiple channels with methods of sensor fusion. In this paper, we demonstrate that two modalities, skin color variation and head motion, can be extracted from the video stream recorded with a webcam. Using a Bayesian approach, these signals are fused with a ballistocardiographic signal obtained from the seat of a chair with a mean absolute beat-to-beat estimation error below 25 milliseconds and an average coverage above 90% compared to an ECG reference.

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Photoplethysmography imaging: a new noninvasive and noncontact method for mapping of the dermal perfusion changes

Cited by 89 publications

References 0 publications

Photoplethysmography Revisited: From Contact to Noncontact, From Point to Imaging

Photoplethysmography Revisited: From Contact to Noncontact, From Point to Imaging

Effects of frame rate and image resolution on pulse rate measured using multiple camera imaging photoplethysmography

Beat-to-beat heart rate estimation fusing multimodal video and sensor data

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