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JACIII Vol.27 No.3 pp. 372-377
doi: 10.20965/jaciii.2023.p0372
(2023)

Research Paper:

A Real-Time Voluntary Motion Extraction Method Based on an Adaptive Filter

Mingyuan Xie*1,*2,*3 ORCID Icon, Jinhua She*4 ORCID Icon, Zhen-Tao Liu*1,*2,*3,† ORCID Icon, and Zhaohui Yang*5

*1School of Automation, China University of Geosciences
No.388 Lumo Road, Hongshan, Wuhan 430074, China

*2Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems
No.388 Lumo Road, Hongshan, Wuhan 430074, China

*3Engineering Research Center of Intelligent Technology for Geo-Exploration, Ministry of Education
No.388 Lumo Road, Hongshan, Wuhan 430074, China

*4School of Engineering, Tokyo University of Technology
1404-1 Katakura, Hachioji, Tokyo 192-0982, Japan

*5Department of Rehabilitation, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
No.1277 Jiefang Road, Jianghan, Wuhan 430022, China

Corresponding author

Received:
December 27, 2022
Accepted:
January 5, 2023
Published:
May 20, 2023
Keywords:
tremor suppression, adaptive filter, voluntary motion
Abstract

Tremors are a symptom of several disorders of the central and peripheral nervous systems, such as Parkinson’s disease (PD). Exoskeletons have been investigated as noninvasive tremor suppression alternatives to medication and surgery. The challenge in musculoskeletal tremor suppression is attenuation of tremor motion without impeding the patient’s voluntary motion. Linear low-pass filters (LPFs) are commonly used for tremor removal. This study presents an alternative method based on an adaptive filter. We compare the effectiveness of the LPFs and adaptive filter on the recorded acceleration signals from an online database.

Filter performances of adaptive filter and linear LPFs

Filter performances of adaptive filter and linear LPFs

Cite this article as:
M. Xie, J. She, Z. Liu, and Z. Yang, “A Real-Time Voluntary Motion Extraction Method Based on an Adaptive Filter,” J. Adv. Comput. Intell. Intell. Inform., Vol.27 No.3, pp. 372-377, 2023.
Data files:
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Last updated on Apr. 05, 2024