Objective: The purpose of this study was to identify differences in kinematic arm motion after tDCS intervention based on principal component analysis that allows generating layers of subtle motions to capture unnatural repetition of movements in a case of secondary dystonia.

Background: Secondary dystonia may be defined by involuntary, sustained muscle contractions which cause twisting and repetitive movements or abnormal postures. Secondary dystonia is usually due to neurological conditions such as stroke, Parkinson disease, trauma or basal ganglia and the thalamus infarct, which can cause social incapacity and affect quality of life [1].There is now significant evidence for a loss of inhibition in the central nervous system (CNS), including the cortex, brain stem, and spinal cord which can be the essential cause of the functional abnormalities observed in dystonia [2]. Transcranial direct current stimulation (tDCS) is a promising method for neurorehabilitation after neurological disease. It is used to stimulate the brain and to modulate its function. However; the effectiveness of this approach on secondary dystonia has not been established [3]. Recently PCA has become a common method of reducing data dimensionality and to reveal underlying data structures in the field of biomechanics [4].

Method: In this blinded-placebo controlled study, 10 sessions of bihemispheric tDCS was delivered to a patient suffering from secondary dystonia due to stroke. The patient received 10 consecutive daily sessions of bihemispheric tDCS (2mA, 20 min), via two(12 cm2) saline-soaked electrodes. PCA analysis was performed on data of joint angles using wireless sensors during human arm reaching movements.

Results: The patterns of PCA after intervention reveals that tDCS provide the smoothest trajectory in motion  and small number of principal components, which is similar to the minimum jerk patterns.Some studies showed that the minimum jerk policy in joint angles could be an appropriate strategy for describing the smoothness of human motions.

Conclusion: This is the first report to demonstrate a therapeutic trend after tDCS-supported therapy in secondary dystonia. This study set out to identify biomechanical features characterizing movement smoothness after intervention. Further research may provide the base information support the use of tDCS for neuroplasticity changes in secondary dystonia.

References: [1] S. Fahn, S. Bressman, and C. Marsden, “Classification of dystonia,” Advances in neurology, vol. 78, p. 1, 1998.J. Clerk Maxwell, A Treatise on Electricity and Magnetism, 3rd ed., vol. 2. Oxford: Clarendon, 1892, pp.68–73. [2 ]M. Hallett, “Neurophysiology of dystonia: the role of inhibition,” Neurobiology of disease, vol. 42, no. 2, pp. 177-184, 2011. [3] S. Furuya, M. A. Nitsche, W. Paulus, and E. Altenmüller, “Surmounting retraining limits in Musicians’ dystonia by transcranial stimulation,” Annals of neurology, vol. 75, no. 5, pp. 700-707, 2014. [4] A. T. Wrigley, W. J. Albert, K. J. Deluzio, and J. M. Stevenson, “Principal component analysis of lifting waveforms,” Clinical Biomechanics, vol. 21, no. 6, pp. 567-578, 2006.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/after-effects-of-transcranial-direct-current-stimulation-tdcs-on-hand-biomechanics-in-a-patient-with-secondary-dystonia/