title: A simulation study for a surface EMG sensor that detects distinguishable motor unit action potentials.
abstract: An advanced volume conductor model was used to simulate the surface-detected motor unit action potentials (MUAPs) due to current sources located at different depths within the muscle tissue of the biceps brachii. Seven different spatial filters were investigated by linear summation of the monopolarly detected surface MUAPs on a square array of nine electrodes. The criterion of the relative energy-of-difference (EOD) between the MUAPs was used to rank spatial filters for their ability to distinguish two motor units located at different depths. Using the same criterion pair wise combinations of spatial filters were ranked for their ability to generate different MUAP shape representations of the same motor unit. In both analyses, the bi-transversal double-differential (BiTDD) configurations and pair wise combinations involving a BiTDD configuration consistently ranked highest. Varying electrode spacing did not change the results in a relevant way. Based on the EOD calculations, a four-channel detection system using all available electrodes of the array is proposed. The implications of using only six electrodes, effectively reducing contact area of the sensor in half, are discussed.
authors.affiliation: Department of Control & Instrumentation Engineering, Kangwon National University, KyoDong Samcheok KangwonDo 245-711, Republic of Korea. jlee@kangwon.ac.kr <jlee@kangwon.ac.kr>
authors.forename: Jin
authors.initials: J
authors.lastname: Lee
authors.forename: Alexander
authors.initials: A
authors.lastname: Adam
authors.forename: Carlo J
authors.initials: CJ
authors.lastname: De Luca
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D000818:Animals; D003198:Computer Simulation; D004566:Electrodes; D004576:Electromyography / Q000379:methods*; D008954:Models, Biological; D009046:Motor Neurons / Q000502:physiology*; D018482:Muscle, Skeletal / Q000166:cytology / Q000502:physiology; D013997:Time Factors