Investigation of the Effects of Statistically Significant Features on the Classification of EEG-Based Motor Imagery Tasks

Murside Degirmenci

Motor imagery (MI) task classification is highly prevalent in Electroencephalography (EEG)-based Brain-Computer Interface (BCI) research area. Extremity movement task classification and finger movement classification studies are presented in this thesis. In extremity movement classification, binary-class (right hand and left hand) and multi-class (right hand, left hand, right hand, and left hand) classifications are performed using 4 different feature extraction approaches and statistically significance-based feature selection (the independent t-test, one-way ANOVA test). Firstly, time- ...Daha fazlası

Doktora Tezi 2024 Yalçın İşler İzmir Katip Çelebi Üniversitesi Fen Bilimleri Enstitüsü 6 Görüntülenme

Erişime Açık

Development of a Tele-Physiotherapy Device to Remedy Elbow Joint with Mobile App Support

Arda SARPAY

The aim of this thesis was to develop a wearable tele-physiotherapy device that addresses the remote elbow joint rehabilitation. The developed device consists of a wearable exoskeleton equipped with servo motor, joint angle sensor, EMG sensor, battery and Wi-Fi module. By connecting with the Android mobile application, it enables real-time monitoring of EMG data and programming of personalized exercise programs. The device offers convenience and comfort to patients by eliminating the need for face-to-face physiotherapy sessions and aims to reduce treatment costs and treatment time. The develo ...Daha fazlası

Yüksek Lisans 2024 Yalçın İşler İzmir Katip Çelebi Üniversitesi Fen Bilimleri Enstitüsü 5 Görüntülenme