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Abstract
A human brain emits five brainwaves. Those are gamma, beta, alpha, theta, and delta waves. Beta and alpha wave are emitted based of consciousness and concentration level. A software for brain signals’ acquisition is built in this research. It also classifies the acquired data into five motion directions of which are forward, right, left, backward, and stop. Neurosky Mindwave sensor and LabVIEW are used in this project. The data from sensor readings are processed by LabVIEW by using filter function and FFT. Before classifying the data, the program will do training to save the data to Microsoft Excel. When it is about to classify the data, the saved data are called and the mean data are compared to the real-time brainwave readings. The closest data to the training data is used as reference to decide the movements that is being thought by the user. From the running test, we found 100% match for ‘forward’ motion, 83,3% match for ‘right’ motion, 93% match for’ backward motion’, 100% match for ‘left’ motion and 90% match for ‘stop’ motion with training to test subject. 100% match for ‘forward’ motion, 37% match for ‘right’ motion, 100% match for ‘backward’ motion, 100% match for ‘left’ motion and 100% match for ‘stop’ motion without training to test subject.
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How to Cite
Madona, P., Hidayat, M., & Susianti, E. (2018). Akuisisi Dan Klasifikasi Sinyal EEG Untuk Lima Arah Pergerakan Berbasis Labview. Jurnal ELEMENTER (Elektro Dan Mesin Terapan), 4(2), 37–44. https://doi.org/10.35143/elementer.v4i2.2406