Adaptive Linear Energy Detector based on onset and offset electromyography activity detection
| Autor: | Abdelaziz Ouldali, Karim Abed-Meraim, Hichem Bengacemi, Ammar Mesloub |
|---|---|
| Přispěvatelé: | Laboratoire d'Etude des Phénomènes de Transfert Appliqués aux Bâtiments (LEPTAB), Université de La Rochelle (ULR), Abed-Meraim, Karim |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Engineering Voice activity detection Offset (computer science) medicine.diagnostic_test business.industry [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing Detector Pattern recognition Electromyography Energy analysis 03 medical and health sciences 030104 developmental biology [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing Probability of error Activity detection Electronic engineering medicine Artificial intelligence business ComputingMilieux_MISCELLANEOUS |
| Zdroj: | 2017 6th International Conference on Systems and Control (ICSC) 2017 6th International Conference on Systems and Control (ICSC), May 2017, Batna, Algeria. pp.409-413 |
| Popis: | This paper describes a new approach for detecting onset/offset electromyography activity. The proposed approach is based on energy analysis which has been widely used in Voice Activity Detection (VAD). A performance analysis has been carried out in order to get the appropriate frame length of EMG signal to adapt within our proposed method. Synthetic and Real EMG signals are used to illustrate us the performance of our proposed method. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|