Towards prediction of Parkinson s disease tremor for a demand-driven deep brain stimulator.

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Parkinson?s disease is a neurological disorder that affects the production of dopa, a substance which is used in the synthesis of the neurotransmitter dopamine (DA). DA is found in regions of the nervous system mainly involved in the regulation of movement; hence the lack of DA has severe repercussions to the control of movement, such as the inducement of limb tremor, bradykinesia and general stiffness of movement. Currently deep brain stimulation (DBS) has replaced the administration of L-dopa as a method of alleviating these symptoms; DBS involves the implantation of an electrical stimulator in the brain which provides a continuous electric pulse preventing the onset of tremor. Despite the benefits of DBS, the continuous stimulation requires that an operation is performed every approximately 18 months in order to replace the stimulator batteries. This is costly both in terms of time and money, and is also stressful for the patient himself with adverse effects on the quality of life. One way of extensively increasing the time between the battery replacement operations is to use complex signal processing techniques in order to predict the onset of tremor and only provide an electrical pulse when necessary. The benefits of this type of ?intelligent? stimulator design are enormous. Initial investigations towards this technology have been performed, with highly promising results that warrant further research, the foundations of which can be laid with the aid of this grant. The proposed research involves the transfer of knowledge between the engineering and medical communities such that strong interdisciplinary collaboration can be established and which takes the DBS technology to the next level.