Papers

Dry Electrode-Based Body Fat Estimation System with Anthropometric Data for Use in a Wearable Device

International Journal
2016~2020
작성자
이진영
작성일
2019-05-01 22:15
조회
1567
Authors : Seung-Chul Shin, Jinkyu Lee, Soyeon Choe, Hyuk In Yang, Jihee Min, Ki-Yong Ahn, Justin Y. Jeon, Hong-Goo Kang

Year : 2019

Publisher / Conference : Sensors

Volume : 19, issue 9

The bioelectrical impedance analysis (BIA) method is widely used to predict percent body fat (PBF). However, it requires four to eight electrodes, and it takes a few minutes to accurately obtain the measurement results. In this study, we propose a faster and more accurate method that utilizes a small dry electrode-based wearable device, which predicts whole-body impedance using only upper-body impedance values. Such a small electrode-based device typically needs a long measurement time due to increased parasitic resistance, and its accuracy varies by measurement posture. To minimize these variations, we designed a sensing system that only utilizes contact with the wrist and index fingers. The measurement time was also reduced to five seconds by an effective parameter calibration network. Finally, we implemented a deep neural network-based algorithm to predict the PBF value by the measurement of the upper-body impedance and lower-body anthropometric data as auxiliary input features. The experiments were performed with 163 amateur athletes who exercised regularly. The performance of the proposed system was compared with those of two commercial systems that were designed to measure body composition using either a whole-body or upper-body impedance value. The results showed that the correlation coefficient ( r2 ) value was improved by about 9%, and the standard error of estimate (SEE) was reduced by 28%.
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7 International Journal Jinkyu Lee, Hong-Goo Kang "A Joint Learning Algorithm for Complex-Valued T-F Masks in Deep Learning-Based Single-Channel Speech Enhancement Systems" in IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol.27, issue 6, pp.1098-1108, 2019
6 International Conference Keulbit Kim, Jinkyu Lee, Jan Skoglund, Hong-Goo Kang "Model Order Selection for Wind Noise Reduction in Non-negative Matrix Factorization" in ITC-CSCC, 2019
5 International Journal Seung-Chul Shin, Jinkyu Lee, Soyeon Choe, Hyuk In Yang, Jihee Min, Ki-Yong Ahn, Justin Y. Jeon, Hong-Goo Kang "Dry Electrode-Based Body Fat Estimation System with Anthropometric Data for Use in a Wearable Device" in Sensors, vol.19, issue 9, 2019
4 International Journal Jinkyu Lee, Jan Skoglund, Turaj Shabestary, Hong-Goo Kang "Phase-Sensitive Joint Learning Algorithms for Deep Learning-Based Speech Enhancement" in IEEE Signal Processing Letters, vol.25, issue 8, pp.1276-1280, 2018
3 International Conference Jinkyu Lee, Keulbit Kim, Turaj Shabestary, Hong-Goo Kang "Deep bi-directional long short-term memory based speech enhancement for wind noise reduction" in HSCMA, 2017
2 International Conference Jinkyu Lee, Hyunson Seo, Hong-Goo Kang "Adaptation of HMM dynamic parameters in reverberant environment" in EUSIPCO, 2013
1 International Conference Jinkyu Lee, Soonho Baek, Hong-Goo Kang "Signal and feature domain enhancement approaches for robust speech recognition" in 8th International Conference on Information, communications and Signal Processing, 2011