The second most common neurodegenerative disease is Parkinson’s disease (PD). PD is a chronic and progressive ailment in which the brain is unable to control body movement. Typical symptoms of PD include resting tremor, bradykinesia, and postural instability. Although medications have been helpful in treating PD symptoms, currently, there is no cure for PD and the effectiveness of medications decrease over time in parallel with unmitigated disease progression. Nevertheless, new advances in Deep Brain Stimulation (DBS) have helped to provide relief from some PD symptoms in patients who are particularly resistant to pharmacologic intervention. For DBS in a surgical procedure, through a small opening in the skull, an electrode is implanted into the brain’s basal ganglia. After the surgery an expert calibrates the unit to optimize the efficiency. This includes setting the frequency, voltage and the duty cycle of the oscillator inside the neurotransmitter.

Early diagnosis and accurate disease stage monitoring with or without interventions are areas of high priority in this field. In order for physicians to accurately monitor disease progression with respect to prescription or DBS efficacy a sensitive, accurate assessment of disease is needed. Current practice relies heavily upon subjective patient examination to monitor disease progression. The accuracy of disease monitoring is, therefore, subject to patient to patient and clinic to clinic variability.

In this project, we will develop a powerful quantitative prototype designed to provide physicians with continuous real-time monitoring of movement dysfunction symptoms thus improving accuracy for disease staging or efficacy of pharmacologic or DBS interventions. This will be achieved through strategic placement of body sensors to differentiate the subtle repetitive nature of limb resting tremors or limited, bradykinetic truncal movements associated with PD versus normal motor control.

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