On the use of information theory for detecting upper limb motor dysfunction: An application to Parkinson’s disease
Parkinson’s disease (PD) is a chronic neurodegenerative disorder characterized by a selective loss of dopaminergic neurons in the substantia nigra, decreased striatal dopamine levels, and consequent extrapyramidal motor dysfunctions. Several potential early diagnostic markers of PD have been proposed. Since they have not been validated in presymptomatic PD, the diagnosis and monitoring of the disease is based on subjective clinical assessment of cognitive and motor symptoms. In this study, we investigated interjoint coordination synergies in the upper limb of healthy and parkinsonian subjects during the performance of unconstrained linear-periodic movements in a horizontal plane using the mutual information (MI). We found that the MI is a sensitive metric in detecting upper limb motor dysfunction, thus suggesting that this method might be applicable to quantitatively evaluating the effects of the antiparkinsonian medication and to monitor the disease progression.
Year of publication: |
2011
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Authors: | Oliveira, M. Elias de ; Menegaldo, L.L. ; Lucarelli, P. ; Andrade, B.L.B. ; Büchler, P. |
Published in: |
Physica A: Statistical Mechanics and its Applications. - Elsevier, ISSN 0378-4371. - Vol. 390.2011, 23, p. 4451-4458
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Publisher: |
Elsevier |
Subject: | Parkinson’s disease | Upper limb | Motor dysfunction | Mutual information |
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