Kyung-jin YOU, Ki-won RHEE, Hyun-chool SHIN
Dept. of Information & Telecommunication, Soongsil University, Se oul 156-743, Korea
Abstract-This paper provides a method to infer finger flexing motions using a 4-channel surface Electromyogram (sEMG). Surface EMGs are harml ess to the human body and easily done. However, they do not reflect the activity of specific nerves or muscles, unlike invasive EMGs. On the other hand, the non -invasive type is difficult to use for discriminating various motions while usi ng only a small number of electrodes. Surface EMG data in this study were obtain ed from four electrodes placed around the forearm. The motions were the flexion of each 5 single fingers (thumb, index finger, middle finger, ring finger, and l ittle fingers). One subject was trained with these motions and another left was untrained. The maximum likelihood estimation method was used to infer the finger motion. Experimental results have showed that this method could be useful for r ecognizing finger motions. The average accuracy was as high as 95%.
Key words-surface EMG; finger flexion; pattern classifi cation; neural signal processing
Manuscript Number: 1674-8042(2011)02-0140-04
dio: 10.3969/j.issn.1674-8042.2011.02.10
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