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Journal of Current Science and Technology

ISSN 2630-0656 (Online)

Design and construction of a non-invasive blood glucose and heart rate meter by photoplethysmography

  • Preya Anupongongarch, College of Biomedical Engineering, Rangsit University, Patumthani, Thailand, Corresponding author; E-mail
  • Thawat Kaewgun, College of Biomedical Engineering, Rangsit University, Patumthani, Thailand
  • Jamie A. O'Reilly, College of Biomedical Engineering, Rangsit University, Patumthani, Thailand
  • Swanjit Suraamornkul, Faculty of Medicine, Vajira Hospital Navamindradhiraj University, Bangkok, Thailand


This article describes the design and construction of a non-invasive blood glucose and heart rate meter that can non-invasively measure blood glucose level and heart rate from the fingertip.  This device operates on the principle of light absorption, known as the Beer-Lambert Law, tracking changes in near-infrared light absorbance of blood glucose with blood volume changes in a photoplethysmogram (PPG) using opto-electronics.  The design incorporates near-infrared 950 nm wavelength and red 630 nm wavelength LED light sources and a photodiode light receiver.  An Arduino NANO 3.0 Mini USB microcontroller was used for signal processing, enabling the meter to compute blood glucose levels in the range of 70 to 130 mg/dL and measure heart rate across the range of 60 to 100 bpm.  To validate the effectiveness of this device, it was used by a sample group of diabetic patients at the Endocrine Unit, Faculty of Medicine, Vajira Hospital.  The results of device evaluation compared with standard clinical measurements were as follows: 1) The non-invasive blood glucose meter accurately measured blood sugar levels in the range of 75 to 150 mg/dL (R2 = 0.99); 2) Across the ranges of 75 to 130 mg/dL and 131 to 289 mg/dL the device had average percentage error of 3.18% and 22.14%, respectively and the overall average percentage error was 10.76%; 3) Heart rate measurements from 60 to 100 bpm showed a mean percentage error of 2.94%, and these were not statistically different from a vital sign monitor (p= 0.222), and 4) Although readings from the meter appeared to be systematically lower than results of standard blood tests, this was not a statistically significant difference (p= 0.135).  Overall, these findings indicate that this non-invasive blood glucose meter may be suitable for non-critical patient monitoring applications where patient comfort and convenience are important considerations.

Keywords: blood glucose level; blood glucose meter; diabetes monitoring; heart rate meter; non-invasive; point of care

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DOI: 10.14456/jcst.2022.9


Allen, J. (2007). Photoplethysmography and its application in clinical physiological measurement. Physiol Meas, 28(3), R1-39. doi:10.1088/0967-3334/28/3/R01

Anupongongarch, P., Kaewgun, T., & O'Reilly, J. A. (2020). Design and Construction of a Non-Invasive Blood Glucose Meter. International Journal of Applied, 13(2), 36-42.

Anupongongarch, P., Kaewgun, T., O'Reilly, J. A., & Khaomek, P. (2019). Development of a Non-Invasive Blood Glucose Sensor. International Journal of Applied, 12(1), 13-19.

Castaneda, D., Esparza, A., Ghamari, M., Soltanpur, C., & Nazeran, H. (2018). A review on wearable photoplethysmography sensors and their potential future applications in health care. International journal of biosensors & bioelectronics, 4(4), 195-202. doi:10.15406/ijbsbe.2018.04.00125

Clarke, W. L., Cox, D., Gonder-Frederick, L. A., Carter, W., & Pohl, S. L. (1987). Evaluating clinical accuracy of systems for self-monitoring of blood glucose. Diabetes Care, 10(5), 622-628. doi:10.2337/diacare.10.5.622

Elgendi, M. (2012). On the analysis of fingertip photoplethysmogram signals. Current cardiology reviews, 8(1), 14-25. doi:10.2174/157340312801215782

Fatah, I. S., Ali, M., & Taha, A. M. (2018). Measure the Heart Rate and Respiration Rate Under Nervous Situation. International Journal of Applied Engineering Research, 13(9). 7070-7075.

Habbu, S., Dale, M., & Ghongade, R. (2019). Estimation of blood glucose by non-invasive method using photoplethysmography. Sādhanā44(6), 1-14. doi:10.1007/s12046-019-1118-9

Jayadevappa, B., & Holi, M. (2016). Photoplethysmography: Design, Development, Analysis and Applications in Clinical and Physiological Measurement - A Review. International Journal of Innovative Research in Science, Engineering and Technology, 5(3). 3519-3531.

Mathew, T. K., & Tadi, P. (2021). Blood Glucose Monitoring. StatPearls. Retrived form

Mondal, H., & Mondal, S. (2020). Clarke Error Grid Analysis on Graph Paper and Microsoft Excel. Journal of diabetes science and technology, 14(2), 499-499. doi:10.1177/1932296819890875

Monte-Moreno, E. (2011). Non-invasive estimate of blood glucose and blood pressure from a photoplethysmograph by means of machine learning techniques. Artificial intelligence in medicine, 53(2), 127-138. doi:10.1016/j.artmed.2011.05.001

Pickering, D. (2013). How to measure the pulse. Community Eye Health, 26(82), 37.

Reimers, A. K., Knapp, G., & Reimers, C. D. (2018). Effects of Exercise on the Resting Heart Rate: A Systematic Review and Meta-Analysis of Interventional Studies. Journal of clinical medicine, 7(12). doi:10.3390/jcm7120503

Tamura, T. (2019). Current progress of photoplethysmography and SPO2 for health monitoring. Biomedical Engineering Letters, 9(1), 21-36. doi:10.1007/s13534-019-00097-w

Tamura, T., Maeda, Y., Sekine, M., & Yoshida, M. (2014). Wearable Photoplethysmographic Sensors-Past and Present. Electronics, 3(2), 282-302.

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