Detecting position dependent tremor with the Empirical mode decomposition

摘要

BackgroundPrimary bowing tremor (PBT) occurs in violinists in the right bowing-arm and is a highly nonlinear and non-stationary signal. However, Fourier-transform based methods (FFT) make the a priori assumption of linearity and stationarity. We present an interesting case of a violinist with PBT and apply a novel method for nonlinear and non-stationary signals for tremor analysis: the empirical mode decomposition (EMD). We compare the results of FFT and EMD analyses. MethodsTremor was measured and quantified in a 50-year-old professional violinist with an accelerometer. Data were analyzed using the EMD, the Hilbert transform, the Hilbert spectrum and the marginal Hilbert spectrum. Findings are compared to the FFT-spectrum and FFT-spectrogram. ResultsWe could show that the EMD yields intrinsic mode functions, which represent the tremor and IMFs, which are associated with voluntary movement. The instantaneous frequency and amplitude are obtained. In contrast the low time frequency resolution and the artifacts of voluntary movements are seen in the FFT results. ConclusionsPBT may present itself as a highly non-stationary and nonlinear phenomenon, which can be accurately analyzed with the EMD, since it gives the instantaneous amplitude and frequency and can identify voluntary from involuntary (tremor) movement.