Reliability of Pulse Measurements in Videoplethysmography

Rumiński, Jacek

doi:10.1515/mms-2016-0040

Cited by 23 publications

(10 citation statements)

References 13 publications

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“…In 2016, Rumiński [39] demonstrated the possibility of estimating HR from rPPG signals in the YCrCb (YUV) space using both ICA-based and PCA-based methods. The experimental results showed that the best HR estimation performance can be achieved by applying PCA to the V channel obtained from a forehead.…”

Section: Related Workmentioning

confidence: 99%

“…In the literature, numerous names and abbreviations of this method have evolved, such as rPPG [26], camera-based PPG (cbPPG) [16], non-contact PPG (ncPPG) [46], distance PPG (DistancePPG) [34], pulse camera (PulseCam) [47], videoplethysmography (VPG) [39], imaging PPG (iPPG/ IPPG) [49], PPG imaging (PPGi/PPGI) [49], and remote imaging PPG (RIPPG) [50]. In this paper, we will use the term rPPG.…”

Section: Related Workmentioning

confidence: 99%

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Optimizing Remote Photoplethysmography Using Adaptive Skin Segmentation for Real-Time Heart Rate Monitoring

2019

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Choosing a proper Region of Interest (ROI) for Remote Photoplethysmography (rPPG) is essential and a challenging first step, and it has a direct effect on the accuracy and reliability of the overall heart rate (HR) algorithm. Non-skin areas have no contribution to the HR information; however, few works have tackled the issue of non-skin pixels included in the ROI. First, this paper considers improving the quality of the rPPG signal by filtering out non-skin pixels included within the ROI. The feasibility of employing skin segmentation for ROI definition is demonstrated. Then, this technique is compared with our previous real-time rPPG-based method. Moreover, we explore the effect of extracting the HR from three ROIs using signal fusion. Second, we give a comprehensive account of the examined methods in our algorithm for face detection, face tracking, skin detection, and blind signal separation. Finally, we compare our rPPG measurements with ground truth values obtained from a commercial pulse oximeter. Based on the simulation results, the proposed algorrithm significantly improves the quality of the rPPG technique.INDEX TERMS Heart rate, remote photoplethysmography (rPPG), unobtrusive monitoring, skin segmentation, real-time.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Optimizing Remote Photoplethysmography Using Adaptive Skin Segmentation for Real-Time Heart Rate Monitoring

2019

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“…Camera-based pulse-rate measurement is an emerging topic. There are variety of abbreviations exist in the literature referring to the same or similar technology, such as remote PPG (rPPG) [6], camera-based PPG (cbPPG) [7], non-contact PPG (ncPPG) [8], imaging PPG (iPPG/IPPG) [9], PPG imaging (PPGi/PPGI) [10], remote imaging PPG (RIPPG) [11], distance PPG (DistancePPG) [12], pulse camera (PulseCam) [13], cardiovascular camera (CardioCam) [14], video PPG (vPPG) [15], video plethysmography (VPG) [16], video-based heart-rate (VHR) [17], vital signs camera (VSC) [18], etc. This may cause confusions when referring the relevant works in the literature, especially to new people entering this field.…”

Section: Rppg Systemmentioning

confidence: 99%

Heart Rate Measurement Based on Color Signal Extraction

Sinhal¹,

Singh²,

Raghuwanshi³

2019

IJITEE

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Photoplethysmography measures vital signs through to extraction of signals from the body. The paper explains the technique for extraction of pulse rate from the videos for three color channels namely; red, green and blue. The DMIMS database is used for experimentation which consists of total 720 videos out of which 25 videos are used for analysis. The results presented in this paper depict that our algorithm works best for blue channel followed by green and then red channel. The main focus of paper is to extract pulse rate from the recorded video and compare the output for different channels and find the best channel for heart rate extraction.

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“…In Ref. 18 , a study on the effectiveness of YUV color space in HR measurement based on PPGI was conducted. The YUV color space consists of a luma component (Y) and two chrominance components (U: B-Y, V: R-Y), and it is used as a default for the Android OS.…”

Section: Introductionmentioning

confidence: 99%

“…Comparing the channel signals between the sRGB and the YUV color spaces, it was found that using the V channel of the YUV color space had a better performance than either using all the channels of the sRGB color space or applying ICA or PCA to all the channels of the sRGB color space. 18 In the HR measurement based on PPGI, the CIE Lab color space is also used. It is composed of a lightness component (

) and two chromatic components (

and

), in which the Euclidean distance between two different colors is similar to the color difference perceived by the human eye.…”

Section: Introductionmentioning

confidence: 99%

Research on the combination of color channels in heart rate measurement based on photoplethysmography imaging

et al. 2021

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. Significance: The measurement of human vital signs based on photoplethysmography imaging (PPGI) can be severely affected by the interference of various factors in the measurement process; therefore, a lot of complex signal processing techniques are used to remove the influence of the interference. Aim: We comprehensively analyze several methods for color channel combination in the color spaces currently used in PPGI and determine the combination method that can improve the quality of the pulse signal, which results in a modified plane-orthogonal-to-skin based method (POS). Approach: Based on the analysis of the previous studies, 13 methods for color channel combination in the different color spaces, which can be seen as having potential abilities in measuring vital signs, were compared by employing the average value of signal-to-noise ratio (SNR) and the box-plot in the public databases UBFC-RPPG and PURE. In addition, the pulse signal was extracted through the dual-color space transformation (sRGB → intensity normalized RGB → YCbCr) and fine-tuning on the CbCr plane. Results: Among the 13 methods for color channel combination, the signal extracted by the Cb+Cr combination in the YCbCr color space includes the most pulse information. Furthermore, the average SNR of the modified POS for all the used databases is improved by 69.3% compared to POS. Conclusions: The methods using prior knowledge are not only simple to calculate but can significantly increase the SNR, which will provide a great help in the practical use of vital sign measurements based on PPGI.

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Reliability of Pulse Measurements in Videoplethysmography

Cited by 23 publications

References 13 publications

Optimizing Remote Photoplethysmography Using Adaptive Skin Segmentation for Real-Time Heart Rate Monitoring

Optimizing Remote Photoplethysmography Using Adaptive Skin Segmentation for Real-Time Heart Rate Monitoring

Heart Rate Measurement Based on Color Signal Extraction

Research on the combination of color channels in heart rate measurement based on photoplethysmography imaging

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