Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12573/395
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Article Citation - Scopus: 15Design and Multichannel Electromyography System-Based Neural Network Control of a Low-Cost Myoelectric Prosthesis Hand(Copernicus GmbH, 2021-02-04) Siddiq Ahmed, Saygin; Almusawi, Ahmed R.J.; Yilmaz, Bulent; Doǧru, NuranThis study introduces a new control method for electromyography (EMG) in a prosthetic hand application with a practical design of the whole system. The hand is controlled by a motor (which regulates a significant part of the hand movement) and a microcontroller board, which is responsible for receiving and analyzing signals acquired by a Myoware muscle device. The Myoware device accepts muscle signals and sends them to the controller. The controller interprets the received signals based on the designed artificial neural network. In this design, the muscle signals are read and saved in a MATLAB system file. After neural network program processing by MATLAB, they are then applied online to the prosthetic hand. The obtained signal, i.e., electromyogram, is programmed to control the motion of the prosthetic hand with similar behavior to a real human hand. The designed system is tested on seven individuals at Gaziantep University. Due to the sufficient signal of the Mayo armband compared to Myoware sensors, Mayo armband muscle is applied in the proposed system. The discussed results have been shown to be satisfactory in the final proposed system. This system was a feasible, useful, and cost-effective solution for the handless or amputated individuals. They have used the system in their day-to-day activities that allowed them to move freely, easily, and comfortably. © 2021 Elsevier B.V., All rights reserved.Conference Object Citation - Scopus: 2Beyin Dalgalari ve Baş Hareketiyle Gerçek Zamanli Robotik Araba Kontrolü(Institute of Electrical and Electronics Engineers Inc., 2018-11) Oztürk, Nedime; Yilmaz, Bulent; Onver, Ahmet YasinEmotiv Epoc Headset is a portable and low-cost device. In this study, Emotiv Epoc headset was used in order to obtain real-time gyro and EEG signals. The aim of this study was to control a robotic car in real-time by using head movement and opening and closing of the eyes. The maximum and minimum amplitude of the gyro signal, and the ratios of the beta waves of O1 and O2 channel to alpha waves of the same channels were used as threshold values. These threshold values were used to determine the direction of the robotic car. Because of its low-cost and easy implementation, Arduino Uno was used to manage the robotic car. This study has shown that brain waves and head movements can control a device in real time. This system has the potential to be used in neurofeedback and brain-computer interface applications. © 2019 Elsevier B.V., All rights reserved.