Wearable Myo-Kinematic Device and Real-Time Analysis System for Anti-Fatigue Training in Patients with Parkinson’s Disease (II)

Forced exercise is demonstrated useful in functional improvement of motor control and central nervous system in patients with Parkinson’s disease (PD). The forced exercise requires the guide by human or machine. The incorporation of virtual reality (VR) in exercise trainers is shown to have a better performance than without VR. However, training exercise usually induces undesirable central fatigue and peripheral fatigue in PD patients. Therefore, a real-time fatigue monitoring is very important for exercise training. Furthermore, the movement disorders such as tremor, rigidity, and bradykinesia may also result in fatigue during training. The measured physiological data and motor characteristics may contain the mixed information related to fatigues and movement disorders, and should be identified. This integrated project is aimed to develop an anti-fatigue VR-guided ergo cycling trainer (Subprojects 3 & 4) with physiological monitoring (Subproject 1) and motor and fatigue assessment (Subproject 2). The role of this subproject is to develop a myo-kinematic (myo represents muscle mechanic property and myoelectric (kinetic); kinematic represents accelerations and angular velocity of moving extremities) measurement and analysis platform for physiological monitoring and motor assessment during anti-fatigue training. In previous year, a kinetic-kinematic device was developed and applied to fatigue research on healthy subjects during ergo cycling training. The muscle mechanical property during training and the myo-oxygenation before/after fatigue were investigated. Extended from previous results, in the first year, similar methodologies will be applied to patients with PD but the kinetic-kinematic device will be miniaturized for comfortable consideration. The Hilbert-Huang transform will be used to analyze the dynamic myoelectric features during different stepping cycling phases to obtain a more accurate estimation of muscle fatigue. A near infrared ray spectroscopy (NIRS) tissue oxygenation device will also be developed. In the second year, a sleeve-like myo-kinematic device with NIRS tissue oxygenation measurement will be developed with the corporation of Taiwan Textile Research Institute. The real-time myo-kinematic analysis and an embedded system will be developed so that the analyzed data can be sent to the VR ergo cycling trainer where peripheral fatigue and central fatigue, and the relationships with tremor, rigidity and bradykinesia can be estimated from the myo-kinematic characteristics during stepping training.

Project ID:PB10308-3327
External Project ID:MOST103-2221-E182-035