Non-invasive glucose measurement based on ultrasonic transducer and near IR spectrometer

Yanan Gao; Yukino Yamaoka; Yoshimitsu Nagao; Jiang Liu; Shigeru Shimamoto

doi:10.1007/978-981-13-1059-1_3

Non-invasive glucose measurement based on ultrasonic transducer and near IR spectrometer

Yanan Gao^*, Yukino Yamaoka, Yoshimitsu Nagao, Jiang Liu, Shigeru Shimamoto

^*Corresponding author for this work

Global Center for Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

This paper studies a noninvasive method to measure glucose level based on ultrasonic transducer and near infrared spectrometer. A series pair data of ultrasonic transducer from human finger, palm, wrist and arm are collected six times a day, and 16 spectral data of NIR spectrometer (reflection) from finger are collected by an OGTT experiment. The collected data are calibrated by using partial least squares regression and feed-forward back-propagation artificial neural network to predict the glucose level. In this study, error grid analysis is used to validate the prediction performance. In addition, the accuracy of the calibration models is improved.

Original language	English
Title of host publication	Mobile and Wireless Technology 2018 - International Conference on Mobile and Wireless Technology ICMWT 2018
Publisher	Springer-Verlag
Pages	33-40
Number of pages	8
ISBN (Print)	9789811310584
DOIs	https://doi.org/10.1007/978-981-13-1059-1_3
Publication status	Published - 2019 Jan 1
Event	International Conference on Mobile and Wireless Technology, ICMWT 2018 - Kowloon, Hong Kong Duration: 2018 Jun 25 → 2018 Jun 27

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	513
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Other

Other	International Conference on Mobile and Wireless Technology, ICMWT 2018
Country/Territory	Hong Kong
City	Kowloon
Period	18/6/25 → 18/6/27

Keywords

BP-ANN
Glucose measurement
Near infrared spectrometer
Non-invasive
PLSR
Ultrasonic transducer

ASJC Scopus subject areas

Industrial and Manufacturing Engineering

Access to Document

10.1007/978-981-13-1059-1_3

Cite this

Gao, Y., Yamaoka, Y., Nagao, Y., Liu, J., & Shimamoto, S. (2019). Non-invasive glucose measurement based on ultrasonic transducer and near IR spectrometer. In Mobile and Wireless Technology 2018 - International Conference on Mobile and Wireless Technology ICMWT 2018 (pp. 33-40). (Lecture Notes in Electrical Engineering; Vol. 513). Springer-Verlag. https://doi.org/10.1007/978-981-13-1059-1_3

Non-invasive glucose measurement based on ultrasonic transducer and near IR spectrometer. / Gao, Yanan; Yamaoka, Yukino; Nagao, Yoshimitsu et al.
Mobile and Wireless Technology 2018 - International Conference on Mobile and Wireless Technology ICMWT 2018. Springer-Verlag, 2019. p. 33-40 (Lecture Notes in Electrical Engineering; Vol. 513).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Gao, Y, Yamaoka, Y, Nagao, Y, Liu, J & Shimamoto, S 2019, Non-invasive glucose measurement based on ultrasonic transducer and near IR spectrometer. in Mobile and Wireless Technology 2018 - International Conference on Mobile and Wireless Technology ICMWT 2018. Lecture Notes in Electrical Engineering, vol. 513, Springer-Verlag, pp. 33-40, International Conference on Mobile and Wireless Technology, ICMWT 2018, Kowloon, Hong Kong, 18/6/25. https://doi.org/10.1007/978-981-13-1059-1_3

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title = "Non-invasive glucose measurement based on ultrasonic transducer and near IR spectrometer",

abstract = "This paper studies a noninvasive method to measure glucose level based on ultrasonic transducer and near infrared spectrometer. A series pair data of ultrasonic transducer from human finger, palm, wrist and arm are collected six times a day, and 16 spectral data of NIR spectrometer (reflection) from finger are collected by an OGTT experiment. The collected data are calibrated by using partial least squares regression and feed-forward back-propagation artificial neural network to predict the glucose level. In this study, error grid analysis is used to validate the prediction performance. In addition, the accuracy of the calibration models is improved.",

keywords = "BP-ANN, Glucose measurement, Near infrared spectrometer, Non-invasive, PLSR, Ultrasonic transducer",

author = "Yanan Gao and Yukino Yamaoka and Yoshimitsu Nagao and Jiang Liu and Shigeru Shimamoto",

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doi = "10.1007/978-981-13-1059-1_3",

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AU - Gao, Yanan

AU - Yamaoka, Yukino

AU - Nagao, Yoshimitsu

AU - Liu, Jiang

AU - Shimamoto, Shigeru

PY - 2019/1/1

Y1 - 2019/1/1

N2 - This paper studies a noninvasive method to measure glucose level based on ultrasonic transducer and near infrared spectrometer. A series pair data of ultrasonic transducer from human finger, palm, wrist and arm are collected six times a day, and 16 spectral data of NIR spectrometer (reflection) from finger are collected by an OGTT experiment. The collected data are calibrated by using partial least squares regression and feed-forward back-propagation artificial neural network to predict the glucose level. In this study, error grid analysis is used to validate the prediction performance. In addition, the accuracy of the calibration models is improved.

AB - This paper studies a noninvasive method to measure glucose level based on ultrasonic transducer and near infrared spectrometer. A series pair data of ultrasonic transducer from human finger, palm, wrist and arm are collected six times a day, and 16 spectral data of NIR spectrometer (reflection) from finger are collected by an OGTT experiment. The collected data are calibrated by using partial least squares regression and feed-forward back-propagation artificial neural network to predict the glucose level. In this study, error grid analysis is used to validate the prediction performance. In addition, the accuracy of the calibration models is improved.

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KW - Near infrared spectrometer

KW - Non-invasive

KW - PLSR

KW - Ultrasonic transducer

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BT - Mobile and Wireless Technology 2018 - International Conference on Mobile and Wireless Technology ICMWT 2018

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ER -

Non-invasive glucose measurement based on ultrasonic transducer and near IR spectrometer

Abstract

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Keywords

ASJC Scopus subject areas

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