Search
Now showing items 1-10 of 12
Two-stepped majority voting for efficient EEG-based emotion classification
(Springer, 2020)
In this paper, a novel approach that is based on two-stepped majority voting is proposed for efficient EEG-based emotion classification. Emotion recognition is important for human-machine interactions. Facial features- and ...
Approach based on wavelet packet transform and 1D-RMLBP for drowsiness detection using EEG
(Wiley-Blackwell, 2020)
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 ...
Electrocardiogram beat classification using deep convolutional neural network techniques
(Institute of Physics Publishing, 2020)
The electrocardiogram (ECG) is a useful method which enables the monitoring of various cardiac conditions, such as arrhythmia and heart rate variability (HRV). ECG beats help to determine various heart failures such as ...
Classification of physical actions from surface EMG signals using the wavelet packet transform and local binary patterns
(Institute of Physics Publishing, 2020)
Physical action recognition is a hot topic in human-machine interactions. It has potential uses in helping disabled people and in various robotic applications. Electromyography (EMG) signals measure the electrical activity ...
Deep rhythm and long short term memory-based drowsiness detection
(Elsevier, 2021)
In this paper, a deep-rhythm-based approach is proposed for the efficient detection of drowsiness based on EEG recordings. In the proposed approach, EEG images are used instead of signals where the time and frequency ...
Fraktal Eğimden Arındırılmış Dalgalılık Analizi ve Pencereli Kare Ortalamanın Karekökü Tabanlı EMG Sınıflandırma
(Fırat Üniversitesi, 2020)
Elektromiyografik (EMG) kas aktivitesini ölçmek için kullanılan faydalı bir tekniktir. EMG sinyalleri çoğunlukla protez,
fiziksel rehabilitasyon, Nöromusküler bozuklukların teşhisi ve beyin-bilgisayar arayüzü gibi medikal ...
EMG Sinyalleri Kullanılarak GoogLeNet ve Çok Seviyeli DPD ile El Tutma Hareketlerinin Sınıflandırılması
(Fırat University, 2022)
Elektromiyografi (EMG) elektriksel aktiviteyi ölçmek için kullanılan bir yöntemdir. Bu yöntem günümüzde hastalık tespitinde kullanılmasıyla yaygınlaşmış olsa da robotik, protez kontrolü, video oyunları gibi popüler alanlarda ...
Accurate detection of autism using Douglas-Peucker algorithm, sparse coding based feature mapping and convolutional neural network techniques with EEG signals
(Elsevier B.V. All, 2022)
Autism Spectrum Disorders (ASD) is a collection of complicated neurological disorders that first show in early childhood. Electroencephalogram (EEG) signals are widely used to record the electrical activities of the brain. ...
Radiomics and deep learning approach to the differential diagnosis of parotid gland tumors
(Wolters Kluwer Health, 2022)
All studies aimed at the differential diagnosis of benign vs. malignant PGTs or the identification of the
commonest PGT subtypes were identified, and five studies were found that focused on deep learning-based differential ...
A New Framework for Automatic Detection of Patients With Mild Cognitive Impairment Using Resting-State EEG Signals
(IEEE (Institute of Electrical and Electronics Engineers), 2020)
Mild cognitive impairment (MCI) can be an indicator representing the early stage of Alzheimier's disease (AD). AD, which is the most common form of dementia, is a major public health problem worldwide. Efficient detection ...
