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Research Papers

Pulse Oximeter for Low SpO2 Level Detection Using Discrete Time Signal Processing Algorithm

[+] Author and Article Information
Sumit Pandey

Center for Reliability Sciences and Technologies,
Chang Gung University,
No. 259, Wen-Hua 1st Road, Guishan District,
Taoyuan City, Taiwan 33302, China;
Department of Electronic Engineering,
Chang Gung University,
No. 259, Wen-Hua 1st Road, Guishan District,
Taoyuan City, Taiwan 33302, China
e-mail: sumit.pandey.tech@outlook.com

Cher Ming Tan

Center for Reliability Sciences and Technologies,
Chang Gung University,
No. 259, Wen-Hua 1st Road, Guishan District,
Taoyuan City, Taiwan 33302, China;
Department of Electronic Engineering,
Chang Gung University,
No. 259, Wen-Hua 1st Road, Guishan District,
Taoyuan City, Taiwan 33302, China;
Institute of Radiation Research,
College of Medicine,
Chang Gung University,
No. 259, Wen-Hua 1st Road, Guishan District,
Taoyuan City, Taiwan 33302, China;
Department of Mechanical Engineering,
Ming Chi University of Technology,
Taishan Dist.,
New Taipei City, Taiwan 24301, China;
Department of Urology,
Chang Gung Memorial Hospital,
No. 5, Fuxing Street, Guishan District,
Taoyuan City, Taiwan 33305, China
e-mail: cmtan@cgu.edu.tw

Hsiao-Wen Chen

Department of Urology,
Chang Gung Memorial Hospital,
No. 5, Fuxing Street, Guishan District,
Taoyuan City, Taiwan 33305, China;
Medical College,
Chang Gung University,
No. 259, Wen-Hua 1st Road, Guishan District,
Taoyuan City, Taiwan 33302, China
e-mail; mhc1211@cgmh.org.tw

Yao En Xie

Center for Reliability Sciences and Technologies,
Chang Gung University,
No. 259, Wen-Hua 1st Road, Guishan District,
Taoyuan City, Taiwan 33302, China;
Department of Electronic,
Chang Gung University,
No. 259, Wen-Hua 1st Road, Guishan District,
Taoyuan City, Taiwan 33302, China
e-mail: h4564000@gmail.com

Jung Hua Tung

Center for Reliability Sciences and Technologies,
Chang Gung University,
No. 259, Wen-Hua 1st Road, Guishan District,
Taoyuan City, Taiwan 33302, China;
Institute of Mechanical and Electrical Engineering,
National Taipei University of Technology,
No. 1, Section 3,
Da'an District,
Taipei City, Taiwan 106, China
e-mail: fred.tung@mail.cgu.edu.tw

Yu-Chuan Kau

Department of Anesthesiology,
Chang Gung Memorial Hospital,
No. 5, Fuxing Street, Guishan District,
Taoyuan City, Taiwan 33305, China
e-mail: yichuan@cgmh.org.tw

Chia-Chih Liao

Department of Anesthesiology,
Chang Gung Memorial Hospital,
No. 5, Fuxing Street, Guishan District,
Taoyuan City, Taiwan 33305, China
e-mail: m7141@cgmh.org.tw

1Corresponding authors.

Manuscript received August 18, 2018; final manuscript received April 16, 2019; published online May 2, 2019. Assoc. Editor: Rafael V. Davalos.

J. Med. Devices 13(2), 021011 (May 02, 2019) (8 pages) Paper No: MED-18-1137; doi: 10.1115/1.4043588 History: Received August 18, 2018; Revised April 16, 2019

Oximeter is an important clinical device used for measuring peripheral capillary oxygen saturation (SpO2) in blood and hence accurate results are needed in order to help physicians predict clinical problems in the initial stage(s) of liver or kidney diagnosis. Different issues associated with the accuracy of SpO2 and heart rate measurement accuracy are studied in this work. With the understanding of these issues, a new SpO2 monitoring system is proposed that comprises of a better detection method, novel discrete time signal processing (DTSP) algorithm, and a custom-made oximeter probe head. The proposed SpO2 measurement system is capable of determining low levels of SpO2 present in human blood and produce the results in a short time that enable real-time monitoring of a patient SpO2. It can also distinguish low level of SpO2 against background noise.

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References

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Figures

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Fig. 1

Research methodology flow chart

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Fig. 2

Hardware architecture of oximeter

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Fig. 3

(a) Oximeter sensor's probe head and (b) Arduino driven circuit for SpO2 measurement

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Fig. 4

Signal Processing Algorithm for calculating SpO2, using raw reflected signal from infrared laser diode (IRRAW) and red laser diode (RRAW)

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Fig. 5

(a) Ideal reflected from arteries [17], (b) reflected IRRAW light signals during experiment without depressing the volunteers' arms, (c) reflected IRRAW light signals during experiment with depressing the volunteers' arms, and (d) filtered signal after applying filter on reflected IRRAW signal

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Fig. 6

(a) FFT of the IRRAW signal and (b) FFT of RRAW signal

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Fig. 7

Mathematical function applied on (a) IRRAW versus time (s) and (b) RRAW versus time (s)

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Fig. 8

(a) IRH (peak in IRRAW curve for every second) and IRL (valley in IRRAW curve for every second) detection. The time interval between two peaks (IRH) is bn. (b) RH (peak in RRAW curve for every second) and RL (valley in RRAW curve for every second) detection.

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Fig. 9

Extinction coefficients εHBO2λR, εHBO2λIR, εHBλR, and εHBλIR versus different light wavelength in human blood [17,20] (Reprinted with permission from Elsevier © 2013)

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Fig. 10

Measurement of SpO2, when blood flow is obstructed by the proximal and distal cuffs

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Fig. 11

Measurement of SpO2 for 10 min from the palm of (a) volunteer-1 and (b) volunteer-2

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Fig. 12

(a) and (b) represent IRRAW and RRAW signals and one can see that they have similar pattern (when blood flow is not obstructed); (c) and (d) represent IRRAW and RRAW signals and again they have similar pattern (when blood flow is obstructed by the proximal and distal cuffs); (e) and (f) IRRAW and RRAW signals have different patterns when there is error during measurement or when there is no object for measurement

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