Project Details
Abstract
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
External Project ID:NSC102-2221-E182-023
Status | Finished |
---|---|
Effective start/end date | 01/08/13 → 31/07/14 |
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