El hareketleri için bir veri toplama sistemi tasarımı

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2019

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Department of Electrical & Electronics Engineering
Department of Electrical and Electronics Engineering (EE) offers solid graduate education and research program. Our Department is known for its student-centered and practice-oriented education. We are devoted to provide an exceptional educational experience to our students and prepare them for the highest personal and professional accomplishments. The advanced teaching and research laboratories are designed to educate the future workforce and meet the challenges of current technologies. The faculty's research activities are high voltage, electrical machinery, power systems, signal and image processing and photonics. Our students have exciting opportunities to participate in our department's research projects as well as in various activities sponsored by TUBİTAK, and other professional societies. European Remote Radio Laboratory project, which provides internet-access to our laboratories, has been accomplished under the leadership of our department with contributions from several European institutions.

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Bu çalışmada, bir akıllı eldiven tasarımının yapılması, eldiven üzerindeki farklı ataletsel sensörler ve EMG sensörden veri toplanması, bu verilerin ön işlemeye tabi tutulması ve bu farklı sensör verilerinin kaynaştırılması yoluyla bir insan-makine etkileşimi uygulamasının geliştirilmesi amaçlanmaktadır. Böylelikle görüntü işleme temelli yaklaşımların kusurlu olduğu noktalarda çözümler sunulması hedeflenmektedir. Akıllı eldivende, manyetometre ve jiroskop tarafından üretilecek olan dördey bazlı oryantasyon verileri ile ivmeölçer tarafından üretilecek olan ivme verilerinin ve EMG Sensor tarafından üretilen analog verilerin, toplanması ve daha sonradan farklı uygulamalarca kullanılmasına hazırlık konusunda bir çalışma yapılmıştır.
In this study, we aim at designing a smart glove, which consists of different inertial sensors and an EMG sensor and developing a human-machine interaction application by pre-processing and fusing these different sensory data. We also aim at providing solutions in cases where image processing-based approaches are inefficient. In the proposed smart glove, the quartenion-based orientation data to be produced by the magnetometer and gyroscope together, the acceleration data to be generated by the accelerometer, and the analog data generated by the EMG sensor are collected and then prepared for use by different applications.

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Elektrik ve Elektronik Mühendisliği, Akıllı sistemler, Biyosensörler, EMG, Electrical and Electronics Engineering, Intelligent systems, Eldiven, Biosensors, Hareket sensörleri, Glove, Motion sensors, Temel bileşenler, Principal components

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62