Spike sorting paradigm for classification of multi-channel recorded fasciculation potentials.
Background: Fasciculation potentials (FPs) are important in supporting the electrodiagnosis of Amyotrophic Lateral Sclerosis (ALS). If classified by shape, FPs can also be very informative for laboratory-based neurophysiological investigations of the motor units.Methods: This study describes a Matla...
| Publicado en: | Computers in Biology & Medicine Vol. 55; pp. 26 - 36 |
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| Autores principales: | , , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
2014
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=109767464&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 109767464 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00104825 JC2 jtl: Computers in Biology & Medicine issn: 00104825 maglogo: N pubinfo: dt: 2014 vid: 55 pid: 82545 pub: Elsevier B.V. place: Philadelphia, Pennsylvania artinfo: ui: 109767464 NLM25450215 2012821883 10.1016/j.compbiomed.2014.09.013 NLM25450215 PMC4254689 109767464 ppf: 26 ppct: 10 formats: tig: atl: Spike sorting paradigm for classification of multi-channel recorded fasciculation potentials. aug: au: Jahanmiri-Nezhad, Faezeh Barkhaus, Paul E Rymer, William Zev Zhou, Ping sug: subj: Action Potentials Physiology Electromyography Methods Neuromuscular Manifestations Physiopathology Signal Processing, Computer Assisted Aged Amyotrophic Lateral Sclerosis Physiopathology Cluster Analysis Female Human Male Middle Age Muscle, Skeletal Physiopathology Factor Analysis Aged: 65+ years Middle Aged: 45-64 years Female Male ab: Background: Fasciculation potentials (FPs) are important in supporting the electrodiagnosis of Amyotrophic Lateral Sclerosis (ALS). If classified by shape, FPs can also be very informative for laboratory-based neurophysiological investigations of the motor units.Methods: This study describes a Matlab program for classification of FPs recorded by multi-channel surface electromyogram (EMG) electrodes. The program applies Principal Component Analysis on a set of features recorded from all channels. Then, it registers unsupervised and supervised classification algorithms to sort the FP samples. Qualitative and quantitative evaluation of the results is provided for the operator to assess the outcome. The algorithm facilitates manual interactive modification of the results. Classification accuracy can be improved progressively until the user is satisfied. The program makes no assumptions regarding the occurrence times of the action potentials, in keeping with the rather sporadic and irregular nature of FP firings.Results: Ten sets of experimental data recorded from subjects with ALS using a 20-channel surface electrode array were tested. A total of 11891 FPs were detected and classified into a total of 235 prototype template waveforms. Evaluation and correction of classification outcome of such a dataset with over 6000 FPs can be achieved within 1-2 days. Facilitated interactive evaluation and modification could expedite the process of gaining accurate final results.Conclusion: The developed Matlab program is an efficient toolbox for classification of FPs. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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