title: Fuzzy MUAP recognition in HSR-EMG detection basing on morphological features.
abstract: The idea of 'besides the MU properties and depending on the recording techniques, MUAPs can have unique pattern' was adopted. The aim of this work was to recognise whether a Laplacian-detected MUAP is isolated or overlapped basing on novel morphological features using fuzzy classifier. Training data set was constructed to elaborate and test the 'if-then' fuzzy rules using signals provided by three muscles: the abductor pollicis brevis (APB), the first dorsal interosseous (FDI) and the biceps brachii (BB) muscles of 11 healthy subjects. The proposed fuzzy classier recognized automatically the isolated MUAPs with a performance of 95.03% which was improved to 97.8% by adjusting the certainty grades of rules using genetic algorithms (GA). Synthetic signals were used as reference to further evaluate the performance of the elaborated classifier. The recognition of the isolated MUAPs depends largely on noise level and is acceptable down to the signal to noise ratio of 20 dB with a detection probability of 0.96. The recognition of overlapped MUAPs depends slightly on the noise level with a detection probability of about 0.8. The corresponding misrecognition is caused principally by the synchronisation and the small overlapping degree.
authors.affiliation: Université de Sétif 1, Faculty of Technology, Department of Electronics, LIS Laboratory, 19000 Sétif, Algeria; Department of Rehabilitation and Prevention Engineering, Institute of Applied Medical Engineering, RWTH-Aachen University, 52074 Aachen, Germany. Electronic address: kamel.mebarkia@rwth-aachen.de.
authors.forename: Kamel
authors.initials: K
authors.lastname: Mebarkia
authors.affiliation: Université de Sétif 1, Faculty of Technology, Department of Electronics, LIS Laboratory, 19000 Sétif, Algeria.
authors.forename: Raїs El'hadi
authors.initials: RE
authors.lastname: Bekka
authors.affiliation: Université de Sétif 1, Faculty of Technology, Department of Electrotechnics, L.A.S Laboratory, 19000 Sétif, Algeria.
authors.forename: Aicha
authors.initials: A
authors.lastname: Reffad
authors.affiliation: Department of Rehabilitation and Prevention Engineering, Institute of Applied Medical Engineering, RWTH-Aachen University, 52074 Aachen, Germany.
authors.forename: Catherine
authors.initials: C
authors.lastname: Disselhorst-Klug
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000328:Adult; D000465:Algorithms; D004576:Electromyography / Q000379:methods*; D005260:Female; D017143:Fuzzy Logic; D006225:Hand; D006801:Humans; D008297:Male; D018482:Muscle, Skeletal / Q000502:physiology*; D011336:Probability; D012815:Signal Processing, Computer-Assisted; D055815:Young Adult
keywords: Fuzzy classification; Fuzzy ‘if-then’ rules; High spatial resolution EMG; Laplacian filter; Motor unit action potential; Optimization; Parameterization; Pattern recognition