Gait Phase Detection Based on Muscle Deformation with Static Standing-Based Calibration

Miyake, Tamon; Yamamoto, Shintaro; Hosono, Satoshi; Funabashi, Satoshi; Cheng, Zhengxue; Zhang, Cheng; Tamaki, Emi; Sugano, Shigeki

doi:10.3390/s21041081

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Gait Phase Detection Based on Muscle Deformation with Static Standing-Based Calibration

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Faculty of Science and Engineering, Waseda University, Tokyo 169-8555, Japan

Graduate School of Advanced Science and Engineering, Waseda University, Tokyo 169-8555, Japan

H2L Inc., Tokyo 106-0032, Japan

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Graduate School of Creative Science and Engineering, Waseda University, Tokyo 169-8555, Japan

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Graduate School of Fundamental Science and Engineering, Waseda University, Tokyo 169-8555, Japan

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Department of Mechanical Systems Engineering, Ibaraki University, Ibaraki 316-0033, Japan

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Global Information and Telecommunication Institute, Waseda University, Tokyo 169-8050, Japan

Author to whom correspondence should be addressed.

Academic Editor: Silvia Fantozzi

Sensors 2021, 21(4), 1081; https://doi.org/10.3390/s21041081

Received: 5 December 2020 / Revised: 25 January 2021 / Accepted: 1 February 2021 / Published: 4 February 2021

(This article belongs to the Collection Sensors for Gait, Human Movement Analysis, and Health Monitoring)

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Abstract

Gait phase detection, which detects foot-contact and foot-off states during walking, is important for various applications, such as synchronous robotic assistance and health monitoring. Gait phase detection systems have been proposed with various wearable devices, sensing inertial, electromyography, or force myography information. In this paper, we present a novel gait phase detection system with static standing-based calibration using muscle deformation information. The gait phase detection algorithm can be calibrated within a short time using muscle deformation data by standing in several postures; it is not necessary to collect data while walking for calibration. A logistic regression algorithm is used as the machine learning algorithm, and the probability output is adjusted based on the angular velocity of the sensor. An experiment is performed with 10 subjects, and the detection accuracy of foot-contact and foot-off states is evaluated using video data for each subject. The median accuracy is approximately 90% during walking based on calibration for 60 s, which shows the feasibility of the static standing-based calibration method using muscle deformation information for foot-contact and foot-off state detection. View Full-Text

Keywords: gait phase detection; muscle deformation; static standing-based calibration

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MDPI and ACS Style

Miyake, T.; Yamamoto, S.; Hosono, S.; Funabashi, S.; Cheng, Z.; Zhang, C.; Tamaki, E.; Sugano, S. Gait Phase Detection Based on Muscle Deformation with Static Standing-Based Calibration. Sensors 2021, 21, 1081. https://doi.org/10.3390/s21041081

AMA Style

Miyake T, Yamamoto S, Hosono S, Funabashi S, Cheng Z, Zhang C, Tamaki E, Sugano S. Gait Phase Detection Based on Muscle Deformation with Static Standing-Based Calibration. Sensors. 2021; 21(4):1081. https://doi.org/10.3390/s21041081

Chicago/Turabian Style

Miyake, Tamon, Shintaro Yamamoto, Satoshi Hosono, Satoshi Funabashi, Zhengxue Cheng, Cheng Zhang, Emi Tamaki, and Shigeki Sugano. 2021. "Gait Phase Detection Based on Muscle Deformation with Static Standing-Based Calibration" Sensors 21, no. 4: 1081. https://doi.org/10.3390/s21041081

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