A Novel Heart Rate Variability Algorithm Incorporated into a Real-Time Bio-Monitoring Assessment and Development of 3D Virtual Reality Settings with the Applications into the Anti-Fatigue Training for Patients with Parkinson's Disease

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

Project Details


It is reported from the previous studies in literature that patients with Parkinson's Disease (PD) usually suffer from non-motor symptoms, including sleep disorders and autonomic dysfunctions. In addition, some researches also indicated that fatigue is a common symptom in patients with PD. Since Heart Rate Variability (HRV) may provide an insight into the underlying Autonomic Nervous System (ANS) control activities, it has been used to assess the ANS function in patients with PD to investigate whether or not the ANS dysfunction is associated with any non-motor or clinical features of PD. On the other hand, fatigue assessment during exercise based on HRV was also investigated by some researchers. Therefore, in order to design an anti-fatigue cycling training system for effectively treating the PD patients, it is essential to clarify the relation between fatigue and other motor or non-motor symptoms of PD. Therefore, this project aims to (1) develop a novel innovative HRV spectral estimation algorithm by combining the use of the Integral Pulse Frequency Modulation (IPFM) model and the Compressed Sensing (CS) framework, (2) validate the feasibility and applicability of the proposed HRV algorithm into the anti-fatigue cycling training system for patients with PD as well as incorporate it into the system, and (3) establish a 3D anti-fatigue Virtual Reality (VR) infrastructure so stationary cycling with VR-based visual/audio cueing and feedback, or tours will enhance executive function and cognitive control.

Project IDs

Project ID:PB10207-0360
External Project ID:NSC102-2221-E182-023
Effective start/end date01/08/1331/07/14


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