A Comparison Of The Different Algorithms For Essential Tremor And Parkinson’s Disease Tremor Differentiation Based On Hand Tremor

Essential tremor (ET) and Parkinson’s disease tremor (PD) are the two most common types of tremor. Misdiagnosis of among these two groups of tremors often occurs when using clinical observations, due to overlapping of symptoms between ET and PD at the early stage of disease. To assist specialist in making decisions when diagnosing the tremor, a tremor monitoring and differential diagnosis system is implemented using a wireless inertia measurement unit, to collect hand tremor data from patients and perform classifications of tremor. Four different types of tremor classification algorithms, namely the Tremor Stability Index (TSI), Mean Harmonic Peak Power (MHPP), Relative Energy (RE) and Empirical Mode Decomposition – Singular Value Decomposition (EMD-SVD) analysis had been tested with 153 postural tremor recordings and 154 rest tremor recordings collected from ET and PD patients. A tremor detection algorithm based on tremor intensity, dominant frequency and length of tremor had been used to select recordings significance tremor of ET and PD for analysis. 43 postural recordings (ET, n= 8 and PD, n=35) and 43 rest tremor recordings (ET, n=4 and PD, n=39) had been selected. The distribution of features extracted from each algorithm was tested with Mann Whitney U test, and the sensitivity, specificity and accuracy for each algorithms in correctly classify ET patients were analysed using receiver operating curves (ROC). The results had shown that are distinct differences between the distributions of MHPP (p=0.001) and RE (p=0.019) among ET and PD. The ROC results had showed that the MHPP had the highest accuracy in classify ET and PD (85.7%), with sensitivity and specificity of 88.6% and 87.5% respectively