IEICE TRANSACTIONS on Communications
Photoplethysmography Measurement Algorithm for a Smartphone Camera
Summary :
In this study, we propose a method for measuring a photoplethysmograph using a complementary metal-oxide-semiconductor image sensor (CMOS) or smartphone camera for the adaptation of a mobile health (m-health) services. The proposed algorithm consists of six procedures. Before measuring the photoplethysmograph, the human fingertip must make contact with the smartphone camera lens and turn on the camera light. The first procedure converts the red-green-blue (RGB) to a gray image from a camera image, Then, region of interest (ROI) must be detected from the obtained image. The third procedure calculates the baseline level to reduce direct current (DC) offset effect, before extracting the photoplethysmograph from the camera image. The baseline is filtered, and the last step oversamples the resulting baseline filtered data using cubic spline interpolation. The proposed algorithm has been tested on six people using CMOS image sensors of several smartphones, which can effectively acquire a PPG signal in any situation. We believe that the proposed algorithm could easily be adapted into any m-health system that used a CMOS image sensor.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E99-B No.3 pp.586-591
- Publication Date
- 2016/03/01
- Publicized
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2015MIP0001
- Type of Manuscript
- Special Section PAPER (Special Section on Information and Communication Technology for Healthcare and Medical Applications in Conjunction with Main Topics of ISMICT2015)
- Category
Authors
Sangjoon LEE
SUN MOON University
Chul Geun PARK
SUN MOON University
Kuk Won KO
SUN MOON University
Keyword
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Sangjoon LEE, Chul Geun PARK, Kuk Won KO, "Photoplethysmography Measurement Algorithm for a Smartphone Camera" in IEICE TRANSACTIONS on Communications,
vol. E99-B, no. 3, pp. 586-591, March 2016, doi: 10.1587/transcom.2015MIP0001.
Abstract: In this study, we propose a method for measuring a photoplethysmograph using a complementary metal-oxide-semiconductor image sensor (CMOS) or smartphone camera for the adaptation of a mobile health (m-health) services. The proposed algorithm consists of six procedures. Before measuring the photoplethysmograph, the human fingertip must make contact with the smartphone camera lens and turn on the camera light. The first procedure converts the red-green-blue (RGB) to a gray image from a camera image, Then, region of interest (ROI) must be detected from the obtained image. The third procedure calculates the baseline level to reduce direct current (DC) offset effect, before extracting the photoplethysmograph from the camera image. The baseline is filtered, and the last step oversamples the resulting baseline filtered data using cubic spline interpolation. The proposed algorithm has been tested on six people using CMOS image sensors of several smartphones, which can effectively acquire a PPG signal in any situation. We believe that the proposed algorithm could easily be adapted into any m-health system that used a CMOS image sensor.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2015MIP0001/_p
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@ARTICLE{e99-b_3_586,
author={Sangjoon LEE, Chul Geun PARK, Kuk Won KO, },
journal={IEICE TRANSACTIONS on Communications},
title={Photoplethysmography Measurement Algorithm for a Smartphone Camera},
year={2016},
volume={E99-B},
number={3},
pages={586-591},
abstract={In this study, we propose a method for measuring a photoplethysmograph using a complementary metal-oxide-semiconductor image sensor (CMOS) or smartphone camera for the adaptation of a mobile health (m-health) services. The proposed algorithm consists of six procedures. Before measuring the photoplethysmograph, the human fingertip must make contact with the smartphone camera lens and turn on the camera light. The first procedure converts the red-green-blue (RGB) to a gray image from a camera image, Then, region of interest (ROI) must be detected from the obtained image. The third procedure calculates the baseline level to reduce direct current (DC) offset effect, before extracting the photoplethysmograph from the camera image. The baseline is filtered, and the last step oversamples the resulting baseline filtered data using cubic spline interpolation. The proposed algorithm has been tested on six people using CMOS image sensors of several smartphones, which can effectively acquire a PPG signal in any situation. We believe that the proposed algorithm could easily be adapted into any m-health system that used a CMOS image sensor.},
keywords={},
doi={10.1587/transcom.2015MIP0001},
ISSN={1745-1345},
month={March},}
Copy
TY - JOUR
TI - Photoplethysmography Measurement Algorithm for a Smartphone Camera
T2 - IEICE TRANSACTIONS on Communications
SP - 586
EP - 591
AU - Sangjoon LEE
AU - Chul Geun PARK
AU - Kuk Won KO
PY - 2016
DO - 10.1587/transcom.2015MIP0001
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E99-B
IS - 3
JA - IEICE TRANSACTIONS on Communications
Y1 - March 2016
AB - In this study, we propose a method for measuring a photoplethysmograph using a complementary metal-oxide-semiconductor image sensor (CMOS) or smartphone camera for the adaptation of a mobile health (m-health) services. The proposed algorithm consists of six procedures. Before measuring the photoplethysmograph, the human fingertip must make contact with the smartphone camera lens and turn on the camera light. The first procedure converts the red-green-blue (RGB) to a gray image from a camera image, Then, region of interest (ROI) must be detected from the obtained image. The third procedure calculates the baseline level to reduce direct current (DC) offset effect, before extracting the photoplethysmograph from the camera image. The baseline is filtered, and the last step oversamples the resulting baseline filtered data using cubic spline interpolation. The proposed algorithm has been tested on six people using CMOS image sensors of several smartphones, which can effectively acquire a PPG signal in any situation. We believe that the proposed algorithm could easily be adapted into any m-health system that used a CMOS image sensor.
ER -
English
