Probabilistic Model-Based Learning Control of a Soft Pneumatic Glove for Hand Rehabilitation.

Journal: IEEE transactions on bio-medical engineering
Published Date:

Abstract

OBJECTIVE: Stroke survivors are usually unable to perform activities of daily living (ADL) independently due to loss of hand functions. Soft pneumatic gloves provide a promising assistance approach for stroke survivors to conduct ADL tasks. However, few studies have explored effective control strategies for the 'human-soft robot' integrated system due to challenges in the nonlinearities of soft robots and uncertainties of human intentions. Therefore, this work aims to develop control approaches for the system to improve stroke survivors' hand functions.

Authors

  • Zhi Qiang Tang
  • Ho Lam Heung
    Department of Biomedical Engineering, the Chinese University of Hong Kong, Hong Kong.
  • Xiang Qian Shi
    Department of Biomedical Engineering, the Chinese University of Hong Kong, Hong Kong.
  • Raymond Kai Yu Tong
  • Zheng Li
    Department of Integrated Pulmonology, Fourth Clinical Medical College of Xinjiang Medical University, Urumqi, Xinjiang, China.