Establishing the Central and Peripheral Fatigue Indexes and VR Based Anti-Fatigue Training Paradigm for Individuals with Parkinson Disease (II)

Project: National Science and Technology CouncilNational Science and Technology Council Academic Grants

Project Details


Fatigue is one of the most common symptoms in individuals with Parkinson’s Disease (PD). Past researches indicated that more than half of the individuals with PD suffered from fatigue. The severity of fatigue was correlated to the quality of life in individuals with PD. Finding the contributions of the central and the peripheral factors to fatigue, building reliable fatigue indexes, and developing an effective training program for individuals with PD are very important. Fatigue can be categorized into peripheral or central causes. The central fatigue and voluntary activation failure originate from the decrease of motivation or the reduction of the conduction within corticospinal tracts. Peripheral fatigue includes the neuromuscular transmission failure in alpha motor neuron, neural-muscular junction, muscle membrane, and E-C coupling failure. Quantifying the weighting of central versus peripheral factors contributing to the fatigue in people with PD is important. Conventional clinical fatigue evaluation can not differentiate the causes of fatigue In laboratory test, peripheral fatigue and central fatigue can be differentiated by electrical stimulation induced twitch forces and interpolated twitch technique, respectively. However, the laboratory monitoring fatigue indexes have to be tested during isometric contractions which are not possible for real-time monitoring and/or feedback controlling. Developing non-invasive real-time monitoring fatigue indexes is important. Cycling exercise produces leg rhythmic movements similar to that during ambulation. It has been shown to improve functional performance in individuals with central nervous lesion. Cycling exercise has advantages on easily adjusting training intensity and is suitable for strength and anti-fatigue training. Due to bradykinesia and the frequent episodes of freezing of gait, motor-assisted fast cycling training is potential to be an optimal form of training for individuals with PD. A study reported that the brain activation areas after fast cycling was similar to the areas at on-medication phase, suggesting that fast cycling training induced brain plasticity in individuals with PD. Studies suggested that individuals with PD benefit from visual and/or audio cuing training. Conventional cuing training required space modification and man power. Virtual Reality (VR) can provide visual/audio cuing more economically than conventional clinical setting. VR may also alleviate central fatigue but its effect needs to be verified. In additions, a recent study suggested that modulation of peripheral resistance could change the components of fatigue. The effect on individuals with PD needed to be further studied. The purpose of this project is to develop non-invasive method to monitor central and peripheral fatigue, to establish VR anti-fatigue ergo cycling training paradigm, and to evaluate the anti-fatigue training effect in individuals with PD. This project is a three-year project. In the previous year, we have established the central fatigue testing platform, integrated sensors testing platform, developed fatigue threshold algorism, and finished pilot test on central fatigue of a PD individual. The purposes of the following two years are: 1. Finding the optimal feedback variables for anti-central-fatigue training in individuals with PD. 2. Evaluating the effect of combined VR and feedback resistance /assistance modulation of the anti-fatigue ergo cycling training on various fatigue components in individuals with PD. This project is integrated with three other projects of Dr. Chan (Project 1), Dr. Chen (Project 3), and Dr. Liaw (Project 4). This project will use the algorism developed by Project 1 to build simplified non-invasive fatigue indexes. The parameters developed by this project will feedback to Project 1 for developing integrated SOC. This project will use the VR platform and HR, HRV related exercise intensity monitoring indexes developed by Project 3 to set up the training and testing paradigm The results of this project will be provided to Project 3 for designing the VR cueing system and feedback controlling interface. This project will use the interactive cycling system and active assisted training system developed by Project 4 to perform testing and training. The results of this project will be provided to Project 4 for developing interactive cadence and resistance feedback controlling parameters. The results of this project will advance the real-time fatigue monitoring technique, help in understanding the causes of fatigue, and develop an effective training program for individuals with PD.

Project IDs

Project ID:PB10308-3333
External Project ID:MOST103-2221-E182-036
Effective start/end date01/08/1431/07/15


  • Fatigue
  • electromyography (EMG)
  • central fatigue
  • cycling training


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