A STATISTICAL FEATURE EXTRACTION IN WAVELET DOMAIN FOR MOVEMENT CLASSIFICATION: A CASE STUDY FOR EYES OPEN, EYES CLOSED, AND OPEN/CLOSED FIST TASKS

Şükriye KARA; Semih ERGİN

Makale detayları

A STATISTICAL FEATURE EXTRACTION IN WAVELET DOMAIN FOR MOVEMENT CLASSIFICATION: A CASE STUDY FOR EYES OPEN, EYES CLOSED, AND OPEN/CLOSED FIST TASKS

Yazarlar:

Şükriye KARA | Semih ERGİN

Yayıncı:

Kirklareli University

Ana Başlıklar:

Uygulamalı fizik

Dergi:

Ejovoc (Electronic Journal of Vocational Colleges) 2018 Vol.8 Issue 2, pp.158-162

Belge Tipi:

Makale

Yayın Tarihi:

11/2018

Belge Dili:

İngilizce

Document ID (Org No.):

2000692983

eISSN:

2146-7684

pISSN:

2146-7684

Özet:

 



Analysis of brain signals constitute an importance,
especially for paralyzed people or people suffer from motor disabilities. For
this aim, some studies have been evaluated to measure signals from the scalp to
provide non-muscle control arguments. Brain-Computer Interface Systems turns
these signals into device signals that are controllable at the level of
thought. In this paper, we classify diverse tasks according to EEG
(electroencephalogram) signals. Then pre-processing, feature extraction and
classification steps are hold. For classification, we use FLDA, Linear SVM,
Quadratic SVM, PCA, and k-NN methods. The best result is obtained by using
k-NN.




.

 



Analysis of brain signals constitute an importance,
especially for paralyzed people or people suffer from motor disabilities. For
this aim, some studies have been evaluated to measure signals from the scalp to
provide non-muscle control arguments. Brain-Computer Interface Systems turns
these signals into device signals that are controllable at the level of
thought. In this paper, we classify diverse tasks according to EEG
(electroencephalogram) signals. Then pre-processing, feature extraction and
classification steps are hold. For classification, we use FLDA, Linear SVM,
Quadratic SVM, PCA, and k-NN methods. The best result is obtained by using
k-NN.




.

Makale detayları

A STATISTICAL FEATURE EXTRACTION IN WAVELET DOMAIN FOR MOVEMENT CLASSIFICATION: A CASE STUDY FOR EYES OPEN, EYES CLOSED, AND OPEN/CLOSED FIST TASKS

Yazarlar: Şükriye KARA | Semih ERGİN

Yayıncı: Kirklareli University

Ana Başlıklar: Uygulamalı fizik

Dergi: Ejovoc (Electronic Journal of Vocational Colleges) 2018 Vol.8 Issue 2, pp.158-162

Belge Tipi: Makale

Yayın Tarihi: 11/2018

Belge Dili: İngilizce

Document ID (Org No.): 2000692983

eISSN: 2146-7684

pISSN: 2146-7684

Sayı

Yazarlar:

Şükriye KARA | Semih ERGİN

Yayıncı:

Kirklareli University

Ana Başlıklar:

Uygulamalı fizik

Dergi:

Ejovoc (Electronic Journal of Vocational Colleges) 2018 Vol.8 Issue 2, pp.158-162

Belge Tipi:

Makale

Yayın Tarihi:

11/2018

Belge Dili:

İngilizce

Document ID (Org No.):

2000692983

eISSN:

2146-7684

pISSN:

2146-7684