| dc.creator |
KILIÇ, Ergin |
|
| dc.creator |
Dogan, Erdi |
|
| dc.date |
2015-12-31T22:00:00Z |
|
| dc.date.accessioned |
2020-10-06T09:35:36Z |
|
| dc.date.available |
2020-10-06T09:35:36Z |
|
| dc.identifier |
26aceb21-c55b-4a69-8ab3-d58a617eb4a3 |
|
| dc.identifier |
10.1109/siu.2016.7495689 |
|
| dc.identifier |
https://avesis.sdu.edu.tr/publication/details/26aceb21-c55b-4a69-8ab3-d58a617eb4a3/oai |
|
| dc.identifier.uri |
http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/55742 |
|
| dc.description |
Electromyography (EMG) signals have been used for the control of prosthetics, orthotics and rehabilitation devices as a result of developments in hardware and software technology. A number of signal processing is required because of very low amplitude and noisy structure of the EMG signal. Feature extraction is the most important attribute of the EMG signal processing and there are many different methods proposed in the literature. In this study, a hardware and software platform is created to perform real-time feature extraction from EMG signals and an application was carried out for an EMG signal which was collected from a forearm. Thus, the structural behaviors of different feature extraction methods are shown on a real-time application. |
|
| dc.language |
tur |
|
| dc.rights |
info:eu-repo/semantics/closedAccess |
|
| dc.title |
Real-Time Feature Extraction from EMG Signals |
|
| dc.type |
info:eu-repo/semantics/conferenceObject |
|