Analysis of human tremor in patients with Parkinson disease using entropy measures of signal complexity

Tremor in Parkinson's disease (PD) is a fundamental feature used in the determination of disease onset and progression. Traditionally, tremor has been evaluated using frequency domain analysis. However, in many cases, this analysis did not show significant differences comparing healthy elders a...

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Bibliographic Details
Published in:2010 Annual International Conference of the IEEE Engineering in Medicine and Biology 2010-01, p.2786-2789
Main Authors: Gil, L M, Nunes, T P, Silva, F H S, Faria, A C D, Melo, P L
Format: Article
Language:English
Subjects:
Accuracy
Biomedical measurements
Complexity theory
Frequency domain analysis
Parkinson's disease
Time series analysis
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Summary:Tremor in Parkinson's disease (PD) is a fundamental feature used in the determination of disease onset and progression. Traditionally, tremor has been evaluated using frequency domain analysis. However, in many cases, this analysis did not show significant differences comparing healthy elders and individuals with PD. Given its complex nature, recently the interest in nonlinear dynamical analysis for better understanding of tremor has grown. In this paper, we examine the effect of PD on the complexity of the tremor time series of PD patients using the approximate entropy method (ApEn). Tremor was also evaluated in the frequency domain. This study involved 11 healthy and 11 PD patients. The peak frequency was similar in both groups, while the amplitude and power in the peak frequency and the total power were significantly higher in PD patients (p
ISSN:1094-687X
1558-4615
DOI:10.1109/IEMBS.2010.5626365