An Informed Multitask Diffusion Adaptation Approach to Study Tremor in Parkinson's Disease

Abstract

In this paper, a network-based approach for studying the relation between the tremor intensity and the brain connectivity of Parkinson's patients is introduced. We propose an adaptive multitask diffusion strategy to estimate the underlying model between the gait information and the electroencephalography signals. Furthermore, the method incorporates an S-transform-based connectivity measure that performs well even on a single-trial basis. The estimated connectivity values are then combined with the combination weights of the multitask diffusion strategy to model the relation between tremor and the brain signals. The outcome is an enhanced brain connectivity measure representing its time-space relation to the tremor. The results show how the differences between the connectivity values of patients with mild and severe hand tremor are most distinguishable when using the proposed method.