Comparison of ELM and ANN on EMG Signals Obtained for Control of Robotic-Hand
Küçük Resim Yok
Tarih
2018
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
IEEE
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
The intelligent robotics industry is evolving and humanoid robots can be made, as well as being able to perform the physical functions of people. Robotic hands are vital for many people at this point. In this study, it was aimed to classify the Electromyography (EMG) signals received from the human arm in the correct direction and then to perform robotic hand application. This is very important in understanding and classifying the geometric structure of the object held in robotic hand applications. The classification time and accuracy ratio between ANN and ELM used for this classification were investigated. For this, 11 features were extracted and classifications were tried by using Extreme Learning Machine (ELM) and Artificial Neural Networks (ANN). The obtained successful classification results were compared with each other and applied to a robotic-hand.
Açıklama
10th International Conference on Electronics, Computers and Artificial Intelligence (ECAI) -- JUN 28-30, 2018 -- Iasi, ROMANIA
Anahtar Kelimeler
component, robotic -hand, Artificial Neural Networks (ANN), Extreme Learning Machine (ELM), EMG signals
Kaynak
PROCEEDINGS OF THE 2018 10TH INTERNATIONAL CONFERENCE ON ELECTRONICS, COMPUTERS AND ARTIFICIAL INTELLIGENCE (ECAI)
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
