A Real-Time Voluntary Motion Extraction Method Based on an Adaptive Filter-Reference-Cited by-同舟云学术

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

Published:2023-05-20 Issue:3 Volume:27 Page:372-377
ISSN:1883-8014
Container-title:Journal of Advanced Computational Intelligence and Intelligent Informatics
language:en
Short-container-title:JACIII

Author:

Xie Mingyuan¹²³^ORCID,She Jinhua⁴^ORCID,Liu Zhen-Tao¹²³^ORCID,Yang Zhaohui⁵

Affiliation:

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

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

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

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

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

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.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Hubei Province

Wuhan Applied Foundational Frontier Project

Higher Education Discipline Innovation Project

Japan Society for the Promotion of Science

Publisher

Fuji Technology Press Ltd.

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction

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