title: [Using AR model to analyze injured nerve with needle EMG signal].
abstract: The two main factors to affect the style of the recruitment are temporal recruitment and spatial recruitment. This study sought a new way to analyze the recruitment with the modern spectrum method. The abnormal spatial recruitment and temporal recruitment of varied injury degrees of intramuscular neuron were compared through the AR model. At last, AR coefficients were extracted and passed through BP artificial neuron network to classify different NEMG signals and good result was gained.
authors.affiliation: Department of Biomedical Engineering, Shanghai Jiaotong University, Shanghai 200030, China.
authors.forename: Chuan
authors.initials: C
authors.lastname: Qin
authors.forename: Zhizhong
authors.initials: Z
authors.lastname: Wang
authors.forename: Gang
authors.initials: G
authors.lastname: Wang
authors.forename: Bo
authors.initials: B
authors.lastname: Ma
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D004576:Electromyography / Q000295:instrumentation / Q000379:methods; D004594:Electrophysiology; D006801:Humans; D008959:Models, Neurological; D008962:Models, Theoretical; D009119:Muscle Contraction / Q000502:physiology; D018482:Muscle, Skeletal / Q000294:innervation / Q000502:physiology*; D009339:Needles; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated; D059348:Peripheral Nerve Injuries; D012815:Signal Processing, Computer-Assisted / Q000295:instrumentation