EMG signal morphology in essential tremor and Parkinson's disease

• Published in: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Vol. 2013; pp. 5765 - 5768
• Main Authors: Ruonala, V., Meigal, A., Rissanen, S. M., Airaksinen, O., Kankaanpaa, M., Karjalainen, P. A.
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 01.01.2013
• Subjects: Action Potentials; Diagnosis, Differential; Discriminant Analysis; Educational institutions; Electromyography; Essential Tremor - diagnosis; Hand - physiology; Histograms; Humans; Morphology; Parkinson Disease - diagnosis; Parkinson's disease; Principal Component Analysis; Severity of Illness Index; Signal Processing, Computer-Assisted; Vectors
• ISSN: 1094-687X; 1557-170X; 1558-4615
• DOI: 10.1109/EMBC.2013.6610861

The aim of this work was to differentiate patients with essential tremor from patients with Parkinson's disease. The electromyographic signal from the biceps brachii muscle was measured during isometric tension from 17 patients with essential tremor, 35 patients with Parkinson's disease, and 40 healthy controls. The EMG signals were high pass filtered and divided to smaller segments from which histograms were calculated using 200 histogram bins. EMG signal histogram shape was analysed with a feature dimension reduction method, the principal component analysis, and the shape parameters were used to differentiate between different patient groups. The height of the histogram and the side difference between left and right hand were the best discriminators between essential tremor and Parkinson's disease groups. With this method, it was possible to discriminate 13/17 patients with essential tremor from 26/35 patients with Parkinson's disease and 14/17 patients with essential tremor from 29/40 healthy controls.