Τίτλος:
Methodology of surface electromyography in gait analysis: review of the literature
Γλώσσες Τεκμηρίου:
Αγγλικά
Περίληψη:
Gait analysis is a significant diagnostic procedure for the clinicians who manage musculoskeletal disorders. Surface electromyography (sEMG) combined with kinematic and kinetic data is a useful tool for decision making of the appropriate method needed to treat such patients. sEMG has been used for decades to evaluate neuromuscular responses during a range of activities and develop rehabilitation protocols. The sEMG methodology followed by researchers assessed the issues of noise control, wave frequency, cross talk, low signal reception, muscle co-contraction, electrode placement protocol and procedure as well as EMG signal timing, intensity and normalisation so as to collect accurate, adequate and meaningful data. Further research should be done to provide more information related to the muscle activity recorded by sEMG and the force produced by the corresponding muscle during gait analysis. © 2019, © 2019 Informa UK Limited, trading as Taylor & Francis Group.
Συγγραφείς:
Papagiannis, G.I.
Triantafyllou, A.I.
Roumpelakis, I.M.
Zampeli, F.
Garyfallia Eleni, P.
Koulouvaris, P.
Papadopoulos, E.C.
Papagelopoulos, P.J.
Babis, G.C.
Περιοδικό:
Journal of Medical Engineering and Technology
Εκδότης:
Taylor and Francis Ltd.
Λέξεις-κλειδιά:
Decision making; Diagnosis; Muscle, Diagnostic procedure; Electrode placement; Gait biomechanics; Muscle activities; Muscle co-contraction; Musculoskeletal disorders; Rehabilitation protocols; Surface electromyography, Gait analysis, academic achievement; analysis of variance; artificial neural network; clinical decision making; electromyography; gait; hamstring muscle; human; kinematics; locomotion; maximum voluntary contraction; motor unit potential; muscle contraction; muscle strength; noise reduction; principal component analysis; priority journal; quadriceps femoris muscle; Review; systematic review; task performance; waveform; electrode; electromyography; gait; physiology; procedures; signal processing; skeletal muscle, Electrodes; Electromyography; Gait Analysis; Humans; Muscle, Skeletal; Signal Processing, Computer-Assisted
DOI:
10.1080/03091902.2019.1609610
