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  • Title: Detection of tremor bursts by a running second order moment function and analysis using interburst histograms.
    Author: Journée HL, Postma AA, Sun M, Staal MJ.
    Journal: Med Eng Phys; 2008 Jan; 30(1):75-83. PubMed ID: 17280862.
    Abstract:
    INTRODUCTION: Conventional linear signal processing techniques are not always suitable for the detection of tremor bursts in clinical practice due to inevitable noise from electromyographic (EMG) bursts. This study introduces (1) a non-linear analysis technique based on a running second order moment function (SOMF) and (2) auto- and cross-interburst interval histograms (IBIH) showing distributions of interburst interval EMG bursts of pathological tremors illustrating an application of the SOMF. MATERIALS AND METHODS: EMG recordings from extensors and flexors of two patients with Parkinson's disease with a rest tremor and from a healthy subject during sustained muscular contraction were preliminary analyzed in a pilot study. The SOMF was obtained by repeated second order moment calculations within a window of fixed width W (time scale parameter) plotted as a function of time. Minimum SOMF values indicate local "moments of inertia" of each EMG burst. Bursts were detected and located when minimum SOMF values were below level L (decision parameter). Optimal settings of parameters W and L were calculated empirically for pathological tremor EMGs. Auto- and cross-IBIHs were obtained from minimum SOMF values of detected bursts. RESULTS: Tremor frequency and phase relation between EMG bursts from auto- and cross-IBIHs agreed with those derived from spectral analysis. Burst detection by SOMF has a high sensitivity and selectivity even with noisy background. CONCLUSION: The SOMF is appropriate for detection of individual EMG bursts of pathological tremors. The technique is sensitive to non-stationary changes of tremor bursts regardless of their amplitude. IBIHs provide a measure of tremor frequency and phase difference between EMG bursts.
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