Discrimination of Parkinsonian tremor from essential tremor by implementation of a wavelet-based soft-decision technique on EMG and accelerometer signals

Abstract A wavelet-decomposition with soft-decision algorithm is used to estimate an approximate power-spectral density (PSD) of both accelerometer and surface EMG signals for the purpose of discrimination of Parkinson tremor from essential tremor. A soft-decision wavelet-based PSD estimation is used with 256 bands for a signal sampled at 800 Hz. The sum of the entropy of the PSD in band 6 (7.8125–9.375 Hz) and band 11 (15.625–17.1875 Hz) is used as a classification factor. The data has been recorded for diagnostic purposes in the Department of Neurology of the University of Kiel, Germany. Two sets of data are used. The training set, which consists of 21 essential-tremor (ET) subjects and 19 Parkinson-disease (PD) subjects, is used to obtain the threshold value of the classification factor differentiating between the two subjects. The test data set, which consists of 20 ET and 20 PD subjects, is used to test the technique and evaluate its performance. A “voting” between three results obtained from accelerometer signal and two EMG signals is applied to obtain the final discrimination. A total accuracy of discrimination of 85% is obtained.

[1]  Alireza Minagar,et al.  Movement disorders. , 2009, The Medical clinics of North America.

[2]  G. Deuschl,et al.  Cortical involvement in the generation of essential tremor. , 2007, Journal of neurophysiology.

[3]  M. Brin,et al.  Consensus Statement of the Movement Disorder Society on Tremor , 2008, Movement disorders : official journal of the Movement Disorder Society.

[4]  Abdulnasir Hossen,et al.  A soft decision algorithm for obstructive sleep apnea patient classification based on fast estimation of wavelet entropy of RRI data. , 2005, Technology and health care : official journal of the European Society for Engineering and Medicine.

[5]  G. Deuschl,et al.  Clinical neurophysiology of tremor. , 1996, Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society.

[6]  G. Deuschl,et al.  Tremor classification and tremor time series analysis. , 1995, Chaos.

[7]  H. Freund,et al.  The cerebral oscillatory network of parkinsonian resting tremor. , 2003, Brain : a journal of neurology.

[8]  Abdulnasir Hossen,et al.  Subband decomposition soft-decision algorithm for heart rate variability analysis in patients with obstructive sleep apnea and normal controls , 2005, Signal Process..

[9]  G. Deuschl,et al.  Cortical correlates of the basic and first harmonic frequency of Parkinsonian tremor , 2009, Clinical Neurophysiology.

[10]  Jan Booij,et al.  Parkinson's disease is overdiagnosed clinically at baseline in diagnostically uncertain cases: A 3‐year European multicenter study with repeat [123I]FP‐CIT SPECT , 2009, Movement disorders : official journal of the Movement Disorder Society.

[11]  Abdulnasir Hossen,et al.  A wavelet-based soft decision technique for screening of patients with congestive heart failure , 2007, Biomed. Signal Process. Control..

[12]  Oren Cohen,et al.  Rest tremor in patients with essential tremor: prevalence, clinical correlates, and electrophysiologic characteristics. , 2003, Archives of neurology.

[13]  J. Jankovic,et al.  Criteria for the diagnosis of essential tremor. , 2000, Neurology.

[14]  R. Djaldetti,et al.  [123I]-FP-CIT SPECT and olfaction test in patients with combined postural and rest tremor , 2008, Journal of Neural Transmission.

[15]  Angelo Antonini,et al.  Cost‐effectiveness of 123I‐FP‐CIT SPECT in the differential diagnosis of essential tremor and Parkinson's disease in Italy , 2008, Movement disorders : official journal of the Movement Disorder Society.

[16]  J. Timmer,et al.  Tremor-correlated cortical activity in essential tremor , 2001, The Lancet.

[17]  J. Schulz,et al.  Long-term EMG recordings differentiate between parkinsonian and essential tremor , 2008, Journal of Neurology.

[18]  J Dichgans,et al.  Reliability, specificity and sensitivity of long-term tremor recordings. , 1995, Electroencephalography and clinical neurophysiology.

[19]  Rodger J. Elble,et al.  Essential tremor frequency decreases with time , 2000, Neurology.

[20]  G. Deuschl,et al.  Tremor analysis in two normal cohorts , 2004, Clinical Neurophysiology.

[21]  Jeffrey M. Hausdorff,et al.  Detecting scaling in the period dynamics of multimodal signals: application to Parkinsonian tremor. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[22]  A. Hossen.  Power spectral density estimation via wavelet decomposition , 2004 .

[23]  Rangaraj M. Rangayyan,et al.  Biomedical Signal Analysis: A Case-Study Approach , 2001 .