A novel accelerometer-based method for the real-time assessment of Parkinson's tremor

Parkinson's disease is the second most common neurodegenerative disease. Tremor is an early symptom for about 70% of patients with Parkinson's disease. Accelerometers have been widely used for the detecting of the tremor signals. There were also several signal processing methods have been proposed to assess and quantify the tremor behavior of the Parkinson's disease, such as the power spectral density and wavelet analysis, etc.. In this paper, we present a novel method, suitable for the real-time implementation of assessing Parkinson's tremor, based on a low-cost accelerometer sensing system.