title: Automatic localisation of innervation zones: a simulation study of the external anal sphincter.
abstract: Traumas of the innervation zone (IZ) of the external anal sphincter (EAS), e.g. during delivery, can promote the development of faecal incontinence. Recently developed probes allow high-resolution detection of EMG signals from the EAS. The analysis of pelvic floor muscles by surface EMG (in particular, the estimation of the location of the IZ) has potential applications in the diagnosis and investigation of the mechanisms of incontinence. An automatic method (based on matched filter approach) for the estimation of the IZ distribution of EAS from surface EMG is discussed and tested using an analytical model of generation of EMG signals from sphincter muscles. Simulations are performed varying length of the fibres, thickness of the mucosa, position of the motor units, and force level. Different distributions of IZs are simulated. The performance of the proposed method in the estimation of the IZ distribution is affected by surface MUAP amplitude (as the estimation made by visual inspection), by mucosa thickness (performance decreases when fibre length is higher) and by different MU distributions. However, in general the method is able to identify the position of two IZ locations and can measure asymmetry of the IZ distribution. This strengthens the potential applications of high density surface EMG in the prevention and investigation of incontinence.
authors.affiliation: Laboratorio di Ingegneria del Sistema Neuromuscolare, Dipartimento di Elettronica, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy. luca.mesin@polito.it
authors.forename: Luca
authors.initials: L
authors.lastname: Mesin
authors.forename: Marco
authors.initials: M
authors.lastname: Gazzoni
authors.forename: Roberto
authors.initials: R
authors.lastname: Merletti
mesh_terms: D000465:Algorithms; D001003:Anal Canal / Q000294:innervation* / Q000502:physiology*; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D004576:Electromyography / Q000379:methods*; D006801:Humans; D008959:Models, Neurological; D009119:Muscle Contraction / Q000502:physiology*; D018482:Muscle, Skeletal / Q000502:physiology*