Proposal of Prediction Accuracy Improvement in Non-invasive Blood Glucose Measurement using MHC Method

  • Ryo Takeuchi Kyushu Institute of Technology
  • Kazuhiko Nagao National College of Technology, Yuge Shosen High School
  • Hiroyuki Miyamoto Kyushu Institute of Technology


According to the World Health Organization, 422 million adults worldwide have diabetes. Diabetic patients must regularly measure and manage their blood glucose levels. However, existing blood glucose meters require needles to draw blood, causing pain and infection problems. The measuring instrument to solve this problem would be a non-invasive blood glucose measuring instrument, but none is practically used at present. The authors have been studying non-invasive blood glucose measurement methods to reduce the burden on diabetic patients. As a result of previous research, we developed a simple non-invasive blood glucose meter and a blood glucose control system. Currently, our aim is to improve accuracy of blood glucose level prediction. In this paper we report on the blood glucose level prediction technique realized by using biological information. As a result, heart rate and MHC method are used as input data, and prediction using machine learning can be performed with high accuracy.


World Health Organization, “GLOBAL REPORT ON DIA- BETES”, 2016.

Ministry of Health, Labour and Welfare, “Heisei 28 nen kokuminkenkou・eiyoutyousakeltuka no gaiyou (in Japanese)”, 2017.

M. Haneda, M. Noda, H. Origasa, H. Noto, D. Yabe, Y. Fujita, A. Goto, T. Kondo and E. Araki, “Japanese Clinical Practice Guideline for Diabetes 2016”, Diabetology Inter- national, Vol.9, pp.1-45, 2018. DOI: 10.1007/s13340-018- 0345-3

Taku Takeda, “Keltutou ziko sokutei no gaiyou”, The Journal of the Japanese Society of Internal Medicine, Vol.98, No.4, pp.761-767, 2009.

A. J. Talib, M. Alkahtani, L. Jiang, F. Alghannam, R. Brick, C. L. Gomes, M. O. Scully, A. V. Sokolov and P. R. Hemmer, “Lanthanide ions doped in vanadium oxide for sensitive op- tical glucose detection”, Optical Materials Express, Vol.8, No.11, pp.3277-3287, 2018. DOI: 10.1364/OME.8.003277

G. V. D. Berghe, P. Wouters, et al., “Intensive insulin therapy in critically ill patients”, The New England Journal of Medicine, Vol.345, No.19, pp.1359-1367, 2001. DOI: 10.1056/NEJMoa011300

R. P. Dellinger, J. M. Carlet, H. Masur, et al., “Surviving Sepsis Campaign guidelines for management of severe sepsis and septic shock”, Intensive Care Medicine, Vol.30, No.3, pp.536-555, 2004. DOI: 10.1007/s00134-004-2210-z

A. H. Del’Aulnoit, S. Boudet, M. Ge ́nin, P. -F. Gautier, J. Schiro, D. H. del’Aulnoit and R. Beuscart, “Development of a Smart Mobile Data Module for Fetal Monitoring in E-Healthcare”, Journal of Medical Systems, Vol.42, No.5, pp.83, 2018. DOI: 10.1007/s10916-018-0938-1

A. A. Abdellatif, A. Emam, C. -F. Chiasserini, A. Mo- hamed, A. Jaoua and R. Ward, “Edge-based compression and classification for smart healthcare systems: Concept, implementation and evaluation”, Expert Systems with Applications, Vol.117, No.1, pp.1-14, 2019. DOI: 10.1016/j.eswa.2018.09.019

E. B. Ferlie and S. M. Shortell, “Improving the quality of health care in the United Kingdom and the United States: A framework for change”, Milbank Quarterly, Vol.79, No.2, pp.281-315, 2003. DOI: 10.1111/1468-0009.00206

H. Shen, D. Ma, Y. Zhao, H. Sun, S. Sun, R. Ye, L. Huang, B. Lang and Y. Sun, “MIAPS: A web-based system for remotely accessing and presenting medical images”, Com- puter Methods and Programs in Biomedicine, Vol.113, No.1, pp.266-283, 2014. DOI: 10.1016/j.cmpb.2013.09.008

Saiketugahuyou,hisinsyuukeltutoutisensanozituyoukani tyousen (in Japanese), National Institutes for Quantum and Radiological Science and Technology, https://www.qst., access date: 2020.12.22

Z. Blum, D. Pankratov and S. Shleev, “Powering electronic contact lenses: Current achievements, challenges, and perspectives”, Expert Review of Ophthalmology, Vol.9, No.4, pp.269-273, 2014. DOI: 10.1586/17469899.2014.922873

M. C. Pande and A. K. Joshi, “Non-Invasive Blood Glucose Measurement”, International Journal of Computational Engineering Research, Vol.5, No.4, pp.129-131, 2015.

S. Y. H. Kit, “Non-Invasive Blood Glucose Measurement Using Temperature-based Approach”, Jurnal Teknologi, Vol.64, No.3, 2013.

R. Takeuchi, A. Seo and K. Nagao, “hisinsyuu keltutou sokuteiki no kaihatu oyobi seido tyousa (in Japanese)”, In- formation Processing Society of Japan, Forum on Information Technology 2018, No.CO-004, pp.47, Fukuoka Institute of Technology, 2018.

R.TakeuchiandK.Nagao,“MHCgizyutuwomotiitahisin- syuu keltutousokuteiki no kaihatu (in Japanese)”, Information Processing Society of Japan, The 81st National Convention of IPSJ, No.6ZG-08, pp.665-666, Fukuoka University nanakuma campus, 2019.

K. Esposito, M. Ciotola, D. Carleo, B. Schisano, L. Sardelli, D. D. Tommaso, L. Misso, F. Saccomanno, A. Ceriello and D. Giugliano, “Post-meal glucose peaks at home associate with carotid initima-media thickness in type 2 diabetes”, The Journal of Clinical Endocrinology & Metabolism, Vol.93, No.4, pp.1345-1350, 2008. DOI: 10.1210/jc.2007-2000

T. Takai, A. Matsuda, K. Saito, K. Yamamoto, Y. Sakamoto, T. Kuzuya, S. Yoshida and M. Ota, “Variations in Heart Rate During Deep Breathing as an Early Index of Diabetic Auto- nomic Neuropathy”, Journal of the Japan Diabetes Society, Vol.26, No.1, pp.37-43, 1983.

S. Kurasawa, S. Koyama, H. Ishizawa, K. Fujimoto and S. Chino, “Verification of Non-Invasive Blood Glucose Mea- surement Method Based on Pulse Wave Signal Detected by FBG Sensor System”, Sensors, Vol.17, No.12, 2017. DOI: 10.3390/s17122702

How to Cite
Takeuchi, R., Nagao, K., & Miyamoto, H. (2021). Proposal of Prediction Accuracy Improvement in Non-invasive Blood Glucose Measurement using MHC Method. Journal of the Institute of Industrial Applications Engineers, 9(1), 9.