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

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 with physiological monitoring and motor assessment. The role of this subproject is to develop a myo-kinematic (myo represents muscle tone 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 the first year, a sleeve-like kinetic-kinematic device will be developed with the incorporation of Taiwan Textile Research Institute. The kinetic-kinematic of healthy subjects will be investigated during ergo cycling training. The myotone and myo-oxygenation before/after fatigue will also be investigated. In the second year, similar methodologies and system will be applied to patients with PD. The independent component analysis is also used to isolate the myoelectric signals from multiple motor units to obtain a more accurate estimation of muscular coherence for muscle fatigue estimation. In the third year, a sleeve-like myo-kinematic device incorporating with a near-infrared-ray tissue oxygenation measurement will be developed. 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, central fatigue, tremor, rigidity, and bradykinesia can be estimated from myo-kinematic data guided by VR.

Project ID:PB10207-0361
External Project ID:NSC102-2221-E182-021