The blood perfusion mapping in the human skin by photoplethysmography imaging U. Rubins, R. Erts and V. Nikiforovs University of Latvia, Institute of Atomic physics and spectroscopy, Riga, Latvia Abstract— A CMOS camera-based imaging photoplethysmographic (PPGI) system is described to detect the blood pulsations in tissue. Attention of PPGI is drawn to the potential applications in visualized blood perfusion. Intensity variations of three wavelengths (620 nm, 520 nm and 432 nm) were detected and analyzed in each pixel of image. To obtain a twodimensional mapping of the dermal perfusion measurement, custom image-processing software has been developed. The high-resolution PPGI images were derived from human fingers (transmission mode) and face (reflection mode), evaluated at three wavelengths. The newly developed system can be usable in skin blood perfusion monitoring for clinical applications. Keywords— photoplethysmography imaging, PPGI, noncontact photoplethysmography, blood perfusion mapping, PPG mapping.
II. METHODS
A. The concept of PPGI Fig. 1 illustrates its basic concept of the technique of non-contact PPGI. The camcorder takes video from any part of the human body and stores it to computer disk. After that special imaging software splits video content to separate frames and calculates light intensity variations in selected region of interest (RoI) (Fig. 2). The next part of processing is visualizing these intensity variations as PPG signal. Such measurement scheme looks promising for fast detection and monitoring of PPG signal waveform changes, as the blood flows from the heart to every location of the body [6].
I. INTRODUCTION
Photoplethysmography (PPG) is a non-invasive optical technique for detecting the blood volume pulsations in tissues by back-scattered or transmitted optical radiation. PPG is nowadays widely used because of its simple design and relatively low cost. A convenient PPG device consisted of light source and photo detector is able to detect blood pulsations from human tissue on the single spot of skin. PPG pulsations can be also registered by non-contact way using an ambient light and video camcorder [1-6]. As a result, PPG can be evaluated in each pixel of registered image. Amplitude of this signal reflects spatial distribution of blood perfusion in skin surface and can be reflected as twodimensional photoplethysmography image (PPGI) map. PPGI allows monitoring with larger field of view, so as to improve the ability to probe biologic interactions dynamically and to study disease over time. Combining this technique with original image processing algorithms can improve the quality and performance of evaluation of PPGI maps. In this paper, a non-contact PPGI system with original image processing software is presented that is capable of monitoring blood perfusion in human skin in hi-resolution images. The aim of study is testing of the new experimental technique for detection of PPGI maps at multiple wavelengths.
Fig. 1 The measurement technique of PPGI
Fig. 2 The concept of PPGI. The PPG signal is derived in time domain from any point of video frame
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The Blood Perfusion Mapping in the Human Skin by Photoplethysmography Imaging
B. The measurements and video processing Sony HDR-SR1 AVC hi-definition (HD) Handycam® Camcorder was used in experiments. As a source of light 60W light bulb lamp was used. Videos were taken from human fingers in light transmission mode and from face in light reflection mode with picture resolution of 1440x1080 pixels 50 frames per second (fps) interlaced mode. For minimizing the influence of automatic settings, Super Steady Shot (electronic image stabilization) system was switched off, white balance and exposure were in manual mode. Each measurement was performed 10 seconds when the patient was no moving. Both hands and face was immersed in hot water for 10 minutes before experiments. Video processing: Video content was exported from camcorder to computer. After that, AVC HD format video was converted to more convenient AVI format video and video resolution was down sampled to 640x360 pixels, 25fps progressive mode. Custom developed Matlab® computer program was used for video processing (Fig. 3). It consists of following main parts: •
The conversion of AVI format video to individual frames and loading into HxWxCxF matrix (where H is frame height, W is frame width, C – color in RGB space, N – number of frames)
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The selection of image area by choosing RoI in the video frame image and selection of RGB channel (R – red, G – green, B – blue)
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Evaluation of the regions of frames with too large intensity variations affected by motion. This procedure helps to avoid regions where skin surface moves
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Evaluation of maximal intensity variation for each pixel of frame. These values assumed as amplitudes of PPG signal in each pixel and stored in 2D PPGI matrix.
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Normalizing of PPGI matrix that the minimal value must be 0 and maximal value must be 255
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Graphical representation of PPGI map
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The PPGI map represents 2D distribution of the amplitude of blood pulsations in skin or skin blood perfusion. The pixels that affected by motion are excluded from map (dark areas, Fig 3a,b). III. RESULTS
Fig. 4a shows the image of the left arm fingers in penetrating light. Because red light penetrates through the tissue in several cm depth, red light (620 nm) channel is selected from RGB space. Fig. 4b shows the PPGI map evaluated from the video frames. Fig. 5 shows the signal of finger video evaluated from the averaged pixel values of selected RoI. Both the arterial pulsation and the slowly changing respiration rhythm can be seen clearly in the time domain. In frequency domain, the exact frequency value of the heartbeat (about 1.1 Hz) with its higher-order harmonic and the low frequency of respiration rhythm can be determined too.
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Fig. 4 Video frame of fingers in penetrating red light (a) and evaluated PPGI map (b)
Fig. 5 PPG signal of finger video evaluated from the averaged pixel values a
of selected RoI. Time domain (upper figure) and frequency domain (lower figure)
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Fig. 3 First frame of finger in penetrating red light (a) and its PPGI map (b)
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Fig. 6a-c shows the image of human face in transmitted light in three colors of RGB space: red (620 nm), green (520 nm) and blue (432nm). The PPGI maps (Fig. 7a-c ) show blood perfusion variations and depends of wavelength of light. It is because optical radiation of different wavelength penetrates and reaches vascular bed at different depths in skin layers. Red light reaches more deeper blood vessels in contrast of blue light that penetrates less than 1mm in deep. Therefore amount of blood detected by blue light is much smaller and PPGI is much more affected by noise (Fig. 7c). In both transmission mode and reflection mode PPGI maps are not affected by non-pulsatile component of skin surface reflection or tissue absorbtion and shows only pulsatile component of blood.
IV. CONCLUSIONS
We performed measurements of light variations on human skin surface and visualized skin blood perfusion in hiresolution PPG images using a camcorder. This technique showed sufficient sensitivity to the visible light spectra, it is non-invasive and easy to use, still it has some advantages and disadvantages. Advantages: For acquiring the PPGI maps consumer level camcorder can be used. As for light source electrical bulb light can be used. Disadvantages: For quality PPGI high power light source is needed. Electrical bulb light generates some noise. The volunteer should be in still position, even slightest movements generates artifacts. This feasibility study shows potential of two-dimensional mapping of PPG signal; however, this requires further studies.
ACKNOWLEDGMENT Financial support from European Social fund, project number 2009/0211/1DP/1.1.1.2.0/09/APIA/VIAA/077, is highly appreciated.
REFERENCES a
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Fig. 6 Video frame of human face in reflected light in red (a), green (b) and blue (c) color spaces
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Fig. 7 PPGI maps of human face evaluated from video shoot in reflected light in red (a), green (b) and blue (c) color spaces
Wu T, Blazek V, Schmitt H J (2000) Photoplethysmography imaging: a new noninvasive and noncontact method for mapping of the dermal perfusion changes. Proc. SPIE 4163: 62-70 Wu T (2003) PPGI: New Development in Noninvasive and Contactless Diagnosis of Dermal Perfusion Using Near InfraRed Light. J. GCPD e.V., 7(1): 17-24 Humphreys K, Markham C, Ward T E (2005) A CMOS camera-based system for clinical photoplethysmographic applications. Proc. SPIE, 5823, 88-95 Zheng J, Hu S (2007) The preliminary investigation of imaging photoplethysmographic system. Journal of Physics: Conf. Series 85: 012031 Verkruysse W, Svaasand L O, Nelson J S (2008) Remote plethysmographic imaging using ambient light. Opt. Express, 16(26): 21434– 21445 Erts R, Rubins U, Spigulis J (2009) Monitoring of blood pulsation using non-contact technique. WC 2009, IFMBE Proceedings 25/VII: 754–756 Author: Institute: Street: City: Country: Email:
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Uldis Rubins Institute of Atomic physics and Spectroscopy Raina Bulv.19 Riga Latvia
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