Name
Title | ||
|---|---|---|
Application of higher order statistics to surface electromyogram signal classification. |
Abstract | ||
|---|---|---|
The electromyographic (EMG) signal provides information about the performance of muscles and nerves. At any instant, the shape of the muscle signal, motor unit action potential (MUAP), is constant unless there is movement of the position of the electrode or biochemical changes in the muscle due to changes in contraction level. The rate of neuron pulses, whose exact times of occurrence are random i... |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/TBME.2005.847525 | IEEE Transactions on Biomedical Engineering |
Keywords | Field | DocType |
Higher order statistics,Electromyography,Muscles,Neurons,Signal processing,Shape,Reconstruction algorithms,Electrodes,Transfer functions,Cepstrum | Signal processing,Negentropy,Feature vector,Pattern recognition,Computer science,Higher-order statistics,Stationary process,Feature extraction,Probability distribution,Artificial intelligence,Probability density function | Journal |
Volume | Issue | ISSN |
52 | 7 | 0018-9294 |
Citations | PageRank | References |
5 | 0.69 | 10 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kianoush Nazarpour | 1 | 75 | 19.08 |
| Ahmad R. Sharafat | 2 | 121 | 11.32 |
| S. Mohammad | 3 | 5 | 0.69 |
| P. Firoozabadi | 4 | 5 | 0.69 |