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
4004
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%.
전체 371
311 International Conference Yoohwan Kwon*, Hee-Soo Heo*, Bong-Jin Lee, Joon Son Chung "The ins and outs of speaker recognition: lessons from VoxSRC 2020" in ICASSP, 2021
310 International Conference You Jin Kim, Hee Soo Heo, Soo-Whan Chung, Bong-Jin Lee "End-to-end Lip Synchronisation Based on Pattern Classification" in IEEE Spoken Language Technology Workshop (SLT), 2020
309 International Conference Seong Min Kye, Yoohwan Kwon, Joon Son Chung "Cross Attentive Pooling for Speaker Verification" in IEEE Spoken Language Technology Workshop (SLT), 2020
308 International Conference Suhyeon Oh, Hyungseob Lim, Kyungguen Byun, Min-Jae Hwang, Eunwoo Song, Hong-Goo Kang "ExcitGlow: Improving a WaveGlow-based Neural Vocoder with Linear Prediction Analysis" in APSIPA (*awarded Best Paper), 2020
307 International Conference Hyeon-Kyeong Shin, Hyewon Han, Kyungguen Byun, Hong-Goo Kang "Speaker-invariant Psychological Stress Detection Using Attention-based Network" in APSIPA, 2020
306 International Conference Min-Jae Hwang, Frank Soong, Eunwoo Song, Xi Wang, Hyeonjoo Kang, Hong-Goo Kang "LP-WaveNet: Linear Prediction-based WaveNet Speech Synthesis" in APSIPA, 2020
305 International Conference Hyungseob Lim, Suhyeon Oh, Kyungguen Byun, Hong-Goo Kang "A Study on Conditional Features for a Flow-based Neural Vocoder" in Asilomar Conference on Signals, Systems, and Computers, 2020
304 International Conference Soo-Whan Chung, Soyeon Choe, Joon Son Chung, Hong-Goo Kang "FaceFilter: Audio-visual speech separation using still images" in INTERSPEECH (*awarded Best Student Paper), 2020
303 International Conference Soo-Whan Chung, Hong-Goo Kang, Joon Son Chung "Seeing Voices and Hearing Voices: Learning Discriminative Embeddings Using Cross-Modal Self-Supervision" in INTERSPEECH, 2020
302 International Conference Hyewon Han, Soo-Whan Chung, Hong-Goo Kang "MIRNet: Learning multiple identities representations in overlapped speech" in INTERSPEECH, 2020