Long-term EMG recordings differentiate between parkinsonian and essential tremor

Abstract

The differential diagnosis of tremor is mainly based on clinical criteria.Nevertheless, these criteria are in some cases not sufficient to differentiate between different tremor forms. Long-term EMG has proven to be a valid and reliable method for the quantification of pathological tremors. The aim of the study was to develop a long-term EMG-based automated analysis procedure that separates parkinsonian tremor from essential tremor. Using longterm EMG tremor was recorded in 45 consecutive patients, 26 with Parkinson's disease (PD) and 19 with essential tremor (ET). Eight tremor parameters were generated automatically. By stepwise backward regression a subset of these criteria was extracted to achieve an automated classification of the tremor by a mathematical model. The obtained model was then tested on a new group of 13 patients in early stages of the disease. Significant differences between groups were found for tremor occurrence, tremor asymmetry, mean tremor frequency and standard deviation of phase of antagonistic muscles. Due to data overlap a classification of the two tremor forms was not possible based on a single tremor parameter. Using logistic regression, a linear formula based on the three parameters tremor occurrence, mean tremor frequency and standard deviation of phase was established and predicted the correct diagnosis in 93% of patients. The validation of the model on the new group of patients in early stages of the tremor disease yielded a correct diagnosis in 100% of cases. We conclude that long-term EMG recording allows a rater-independent classification of parkinsonian versus essential tremor.

Neurological Tremor: Sensors, Signal Processing and Emerging Applications

“…Recent works indicate that these recordings allow a rater-independent classification of parkinsonian versus essential tremor [23]. Arrays of SEMG are being adopted by many laboratories.…”

Discrimination of Parkinsonian Tremor from Essential Tremor Using the Nonlinear Analysis of Wrist Muscle EMG Signals

“…IM provides an alternative approach for an accurate discrimination of the tremor forms. A few numbers of new analytical procedures have been proposed and developed using IM, such as a soft-decision wavelet-based PSD estimation technique [6] and Long-term EMG recordings [5]. A method of long-term EMG recording was proved to be suitable for the classification of PD and ET [7].…”

“…Essential tremor (ET) and the tremor in Parkinson's disease (PD) are the two most common pathological tremor forms encountered in clinical neurology [2]. ET is usually present during posture and action, whereas the most common tremor form in Parkinson's disease is resting tremor [5]. When all the typical features are present, these two tremor forms can be easily distinguished on a clinical method.…”

“…A method of long-term EMG recording was proved to be suitable for the classification of PD and ET [7]. But this is more time consuming and cumbersome to patients and doctors as it entails more than one visit and longer recording times also outside the laboratory [5].…”

A holistic approach to assess the feasability of telehealth for Parkinson's disease management

“…Spieker et al (1998) developed a method of ambulatory long-term EMG monitoring for quantification of tremor using a Fast Fourier Transformation (FFT) concluding that EMG is useful for differentiation between Essential Tremor (ET) and PD with a high sensitivity and a high reliability and for tremor quantification [363]. Also, Breit et al (2008) developed a long-term EMG-based automated analysis procedure that separates parkinsonian tremor from essential tremor using logistic regression, a linear formula based on the three parameters predicted the correct diagnosis in 93% of patients [364]. Cole et al (2010) tested the feasibility of using a Dynamic Neural Network (DNN) solution for detecting time-varying occurrences of tremor and dyskinesia at 1 second using surface electromyographic (sEMG) sensors and tri-axial accelerometers worn by PD patients.…”