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Test and Validation of a Smart Exercise Bike for Motor Rehabilitation in Individuals With Parkinson’s Disease
- Source :
- IEEE Transactions on Neural Systems and Rehabilitation Engineering. 24:1254-1264
- Publication Year :
- 2016
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2016.
-
Abstract
- To assess and validate the Smart Exercise Bike designed for Parkinson's Disease (PD) rehabilitation, 47 individuals with PD were randomly assigned to either the static or dynamic cycling group, and completed three sessions of exercise. Heart rate, cadence and power data were captured and recorded for each patient during exercise. Motor function for each subject was assessed with the UPDRS Motor III test before and after the three exercise sessions to evaluate the effect of exercise on functional abilities. Individuals who completed three sessions of dynamic cycling showed an average of 13.8% improvement in the UPDRS, while individuals in the static cycling group worsened by 1.6% in UPDRS. To distinguish the static and dynamic cycling groups by biomechanical and physiological features, the complexity of the recorded signals (cadence, power, and heart rate) was examined using approximate entropy (ApEn), sample entropy (SaEn) and spectral entropy (SpEn) as measures of variability. A multiple linear regression (MLR) model was used to relate these features to changes in motor function as measured by the UPDRS Motor III scale. Pattern variability in cadence was greater in the dynamic group when compared to the static group. In contrast, variability in power was greater for the static group. UPDRS Motor III scores predicted from the pattern variability data were correlated to measured scores in both groups. These results support our previous study which explained how variability analysis results for biomechanical and physiological parameters of exercise can be used to predict improvements in motor function.
- Subjects :
- 0209 industrial biotechnology
medicine.medical_specialty
medicine.medical_treatment
Biomedical Engineering
02 engineering and technology
Approximate entropy
Article
03 medical and health sciences
020901 industrial engineering & automation
0302 clinical medicine
Physical medicine and rehabilitation
Heart rate
Linear regression
Internal Medicine
medicine
Humans
Neurorehabilitation
Movement Disorders
Rehabilitation
General Neuroscience
Neurological Rehabilitation
Parkinson Disease
Equipment Design
Robotics
Exercise Therapy
Equipment Failure Analysis
Sample entropy
Treatment Outcome
Therapy, Computer-Assisted
Exercise Test
Physical therapy
Cadence
Psychology
Cycling
030217 neurology & neurosurgery
Subjects
Details
- ISSN :
- 15580210 and 15344320
- Volume :
- 24
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Neural Systems and Rehabilitation Engineering
- Accession number :
- edsair.doi.dedup.....82333a375d1b66edabaf3f1687e53a2e
- Full Text :
- https://doi.org/10.1109/tnsre.2016.2549030