A clinically applicable approach for detecting spontaneous action potential spikes in amyotrophic lateral sclerosis with a linear electrode array.

Abstract

Examination of spontaneous muscle activity is an important part of the routine electromyogram (EMG) in assessing neuromuscular diseases. The EMG is specifically valuable as a diagnostic test in supporting the diagnosis of amyotrophic lateral sclerosis. High-density surface EMG is a relatively new technique that has until now been used in research but has the potential for clinical application. This study presents a simple high-density surface EMG method for automatic detection of spontaneous action potentials from surface electrode array recordings of patients with amyotrophic lateral sclerosis. To reduce computational complexity while maintaining useful information from the electrode array recording, the multichannel high-density surface EMG was transferred to single-dimensional data by calculating the maximum difference across all channels of the electrode array. A spike detection threshold was then set in the single-dimensional domain to identify the firing times of each spontaneous action potential spike, whereas a spike extraction threshold was used to define the onset and offset of the spontaneous spikes. These data were used to extract the spontaneous spike waveforms from the electrode array EMG. A database of detected spontaneous spikes was thus obtained, including their waveforms, on all channels along with their corresponding firing times. This newly developed method makes use of the information from different channels of the electrode array EMG recording. It also has the primary feature of being simple and fast in implementation, with convenient parameter adjustment and user-computer interaction. Hence, it has good possibilities for clinical application.

• Authors: Faezeh Jahanmiri-Nezhad, Xiaoyan Li, Paul E Barkhaus, William Z Rymer, Ping Zhou
• Journal: Journal of clinical neurophysiology : official publication of the American Electroencephalographic Society (J Clin Neurophysiol) Vol. 31 Issue 1 Pg. 35-40 (Feb 2014) ISSN: 1537-1603 [Electronic] United States
• PMID: 24492444 (Publication Type: Journal Article, Research Support, N.I.H., Extramural, Research Support, U.S. Gov't, Non-P.H.S.)

Topics

• Action Potentials (physiology)
• Algorithms
• Amyotrophic Lateral Sclerosis (physiopathology)
• Electrodes
• Electromyography (methods)
• Humans
• Muscle, Skeletal (physiopathology)
• Signal Processing, Computer-Assisted