Literature DB >> 22868526

A decentralized modular control framework for robust control of FES-activated walker-assisted paraplegic walking using terminal sliding mode and fuzzy logic control.

Vahab Nekoukar1, Abbas Erfanian.   

Abstract

A major challenge to developing functional electrical stimulation (FES) systems for paraplegic walking and widespread acceptance of these systems is the design of a robust control strategy that provides satisfactory tracking performance. The systems need to be robust against time-varying properties of neuromusculoskeletal dynamics, day-to-day variations, subject-to-subject variations, external disturbances, and must be easily applied without requiring offline identification during different experimental sessions. Another major problem related to walker-assisted FES-activated walking concerns the high metabolic rate and upper body effort that limit the clinical applications of FES systems. In this paper, we present a novel decentralized modular control framework for robust control of walker-assisted FES-activated walking. For each muscle-joint dynamics, an independent module control is designed, and the dynamics of the plant are identified online. This process requires no prior knowledge about the dynamics of the plant to be controlled and no offline learning phase. The module is based on adaptive fuzzy terminal sliding mode control and fuzzy logic control. The module control adjusts both pulse-amplitude and pulsewidth of the stimulation signal in such a way that upper body effort is minimized and the lower extremity walking pattern lies within a defined boundary of the reference trajectory. The proposed control strategy has been evaluated on three paraplegic subjects. The results showed that accurate tracking performance and smooth walking pattern were achieved. This favorable performance was obtained without requiring offline identification, manual adjustments, and predefined ON/OFF timing of the muscles.

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Mesh:

Year:  2012        PMID: 22868526     DOI: 10.1109/TBME.2012.2208963

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  6 in total

1.  Hardware System for Real-Time EMG Signal Acquisition and Separation Processing during Electrical Stimulation.

Authors:  Ya-Hsin Hsueh; Chieh Yin; Yan-Hong Chen
Journal:  J Med Syst       Date:  2015-07-26       Impact factor: 4.460

2.  An Iterative Learning Controller for a Switched Cooperative Allocation Strategy during Sit-to-Stand Tasks with a Hybrid Exoskeleton.

Authors:  Vahidreza Molazadeh; Qiang Zhang; Xuefeng Bao; Nitin Sharma
Journal:  IEEE Trans Control Syst Technol       Date:  2021-07-05       Impact factor: 5.418

3.  A Modified Dynamic Surface Controller for Delayed Neuromuscular Electrical Stimulation.

Authors:  Naji Alibeji; Nicholas Kirsch; Brad E Dicianno; Nitin Sharma
Journal:  IEEE ASME Trans Mechatron       Date:  2017-05-16       Impact factor: 5.303

4.  Characterization of the Force Production Capabilities of Paralyzed Trunk Muscles Activated With Functional Neuromuscular Stimulation in Individuals With Spinal Cord Injury.

Authors:  Aidan R W Friederich; Musa L Audu; Ronald J Triolo
Journal:  IEEE Trans Biomed Eng       Date:  2021-07-16       Impact factor: 4.756

5.  Intensity- and Duration-Adaptive Functional Electrical Stimulation Using Fuzzy Logic Control and a Linear Model for Dropfoot Correction.

Authors:  Guangtao Chen; Zhihang Shen; Yu Zhuang; Xiaoyun Wang; Rong Song
Journal:  Front Neurol       Date:  2018-03-19       Impact factor: 4.003

6.  Human Gait Control Using Functional Electrical Stimulation Based on Controlling the Shank Dynamics.

Authors:  Zohre Rezaee; Hamid Reza Kobravi
Journal:  Basic Clin Neurosci       Date:  2020-01-01
  6 in total

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