Journal of Neuroscience Methods xxx (2005) xxx–xxx EMGLAB: An interactive EMG decomposition program Kevin C. McGill a,* , Zoia C. Lateva a , Hamid R. Marateb b a Rehabilitation R&D Center, VA Palo Alto Health Care System, 3801 Miranda Ave, Palo Alto, CA 94304, USA b Electronics and Computer Research Center, Isfahan University, Isfahan, Iran Received 15 December 2004; received in revised form 22 April 2005; accepted 22 April 2005 Abstract This paper describes an interactive computer program for decomposing EMG signals into their component motor-unit potential (MUP) trains and for averaging MUP waveforms. The program is able to handle single- or multi-channel signals recorded by needle or fine-wire electrodes during low and moderate levels of muscular contraction. It includes advanced algorithms for template matching, resolving superimpositions, and waveform averaging, as well as a convenient user interface for manually editing and verifying the results. The program also provides the ability to inspect the discharges of individual motor units more closely by subtracting out interfering activity from other MUP trains. Decomposition accuracy was assessed by cross-checking pairs of signals recorded by nearby electrodes during the same contraction. The results show that 100% accuracy can be achieved for MUPs with peak-to-peak amplitudes greater than 2.5 times the rms signal amplitude. Examples are presented to show how decomposition can be used to investigate motor-unit recruitment and discharge behavior, to study motor-unit architecture, and to detect action potential blocking in doubly innervated muscle fibers. © 2005 Elsevier B.V. All rights reserved. Keywords: EMG; Decomposition; Motor-unit potential; Spike train; Muscle architecture; Double innervation; Common drive 1. Introduction The electromyographic (EMG) signal recorded by a nee- dle or fine-wire electrode is made up of trains of motor- unit potentials (MUPs), and thus provides a potentially rich source of information about motoneuron discharge behav- ior and motor-unit (MU) organization (Basmajian and De Luca, 1985). To obtain this information, it is necessary to sort out the activity of multiple simultaneously active MUs, a process known as decomposition. Before the advent of computers, simple EMG signals were sometimes decom- posed manually by identifying distinctively shaped MUPs on traces photographed at high-sweep speed (Desmedt, 1983). Computer methods have now been developed to mechanize various aspects of this process (Lefever and De Luca, 1982; Abbreviations: EMG, electromyogram; IDI, inter-discharge interval; IFR, instantaneous firing rate; MN, motoneuron; MU, motor unit; MUP, motor-unit potential; MVC, maximum voluntary contraction * Corresponding author. Tel.: +1 650 493 5000x64477; fax: +1 650 493 4919. E-mail address: mcgill@rrdmail.stanford.edu (K.C. McGill). McGill et al., 1985; Haas and Meyer, 1989; De Luca, 1993; Stashuk, 2001; Zennaro et al., 2003). However, some degree of human oversight is still necessary to decompose moder- ately complex EMG signals completely and with consistent reliability. The goal of full decomposition is to detect all the MUs that are active in a signal and to identify every one of their discharges. In reality, most EMG signals contain a continuum of activity, ranging from large MUPs that can be clearly dis- tinguished to small ones that blend into and help constitute the background noise. Thus, the number of MUP trains that can be fully identified depends to some extent on the amount of effort one is willing to expend. Most EMG signals also contain frequent superimpositions. These occur when two or more MUs discharge at nearly the same time and their MUPs overlap. Full decomposition requires the ability to resolve such superimpositions. Full decomposition is important in the study of MU dis- charge behavior. While it is possible to obtain complete discharge patterns for one or two MUs using single-unit recording techniques (Bigland and Lippold, 1954; Datta and Stephens, 1990), and to estimate certain global discharge 0165-0270/$ – see front matter © 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.jneumeth.2005.05.015 NSM-3970; No. of Pages 13