Approach based on wavelet packet transform and 1D-RMLBP for drowsiness detection using EEG
Künye
Alçin, O. F. (December 01, 2020). Approach based on wavelet packet transform and 1D‐RMLBP for drowsiness detection using EEG. Electronics Letters, 56, 25, 1378-1381.Özet
Early drowsiness detection may be crucial for the vehicle alertness system. Towards this, wearable technology, camera-based biophysical signals like electroencephalogram (EEG) approaches are utilised. In this Letter, the EEG-based approach is proposed to detect drowsiness. The proposed method consists of random sampling-based artificial signal augmentation, wavelet packet transform decomposition, logarithmic energy entropy, and one-dimensional region mean local binary pattern (1d-RMLBP) based feature extraction and classifier. k-Nearest neighbour and support vector machine classifiers are employed to detect the drowsiness. The MIT/BIH polysomnographic dataset has been used to test the proposed model. The proposed method has superior performance than the other methods using the same data set. The experimental results demonstrate that the proposed model could efficiently detect drowsiness from polysomnographic EEG signals.
Kaynak
Electronics LettersCilt
56Sayı
25Koleksiyonlar
İlgili Öğeler
Başlık, yazar, küratör ve konuya göre gösterilen ilgili öğeler.
-
New human identification method using Tietze graph-based feature generation
Tuncer, Türker; Aydemir, Emrah; Doğan, Şengül; Kobat, Mehmet Ali; Kaya, Muhammed Çağrı; Metin, Serkan (Springer, 2021)Electrocardiogram (ECG) signals have been widely used for disease diagnosis. Besides, the ECG signals can be used for human identification. In this work, a Tietze pattern and neighborhood component analysis (NCA)-based ... -
Biyoakustik ses verileri üzerinde çeşitli sınıflandırıcı algoritmalarının temel bileşen analizi kullanılarak performans karşılaştırması
Onal, Merve Kesim; Avcı, Engin; Türkoğlu, İbrahim (IEEE (Institute of Electrical and Electronics Engineers), 2019)Doğal ortamlarda alınan seslerin tanınması laboratuvar ortamında alınan veya yapay olarak oluşturulan seslerin tanınmasından daha zordur. Özellikle benzer canlıların çıkardıkları sesler tanınmayı zorlaştıran bir etkendir. ... -
A Novel Analog Modulation Classification: Discrete Wavelet Transform-Extreme Learning Machine (DWT-ELM)
Üstündağ, Mehmet (Bitlis Eren Üniversitesi, 2021)The aim of this study is to propose a method using discrete wavelet transform and extreme learning machine (DWT-ELM) in classification of communication signals. Six types of analog modulated signals as “AM”, “DSB”, “USB”, ...