Muchlis, Ichwanul (2018) Implementasi Pengenalan Pergerakan Bola Mata Menggunakan Elektroda Dengan Exponential Filter. Sarjana thesis, Universitas Brawijaya.
Abstract
Pada dasarnya seorang manusia adalah makhluk sosial yang saling membutuhkan satu sama lain. Tentunya setiap manusia pasti berharap hidup normal dengan tubuh yang sehat. Seseorang yang kehilangan fisik atau cacat tubuh pasti akan menjadi sebuah tantangan bagi mereka untuk bisa menjalani kehidupan sosial bersama masyarakat lainnya. Beberapa pasien penyandang disabilitas khususnya tunadaksa membutuhkan sebuah alat agar mereka dapat berinteraksi secara normal dengan bantuan alat rehabilitasi. Perancangan alat rehabilitasi memanfaatkan dari salah satu sistem cerdas bio-sinyal yaitu sinyal electrooculography teknik pengukuran untuk merekam aktivitas elektrik dari gerakan mata. Implementasi hardware menggunakan sensor lima elektroda ditempel pada sekitar mata, penguat instrumentasi OP07 dengan penguatan 416 disertai high pass filter orde 2 frekuensi cutoff 0.1Hz dan low pass filter orde 2 frekuensi cutoff 16Hz serta sumber daya tegangan dari rangkaian 9V. Menggunakan metode baseline dengan kombinasi perhitungan nilai bobot exponential filter dan threshold. Terdapat proses perancangan dan implementasi perangkat keras dalam printed circuit board. Perangkat lunak pertama dengan pencarian nilai baseline kedua channel, proses perhitungan nilai bobot 0.3 exponential filter agar noise bisa teratasi dengan tepat dan mengeluarkan hasil yang lebih akurat, penentuan katagori kelima gerakan mata yaitu depan, kanan, kiri, atas, dan bawah dengan nilai threshold. Hasil dari pengujian menyatakan bahwa pengujian pertama masing-masing gerakan mata dilakukan pada 3 subyek mencapai rata-rata tingkat akurasi 98,66%, kedua 5 gerakan mata berurutan dilakukan pada 3 subyek mencapai rata-rata tingkat akurasi 96% dan ketiga pengujian delay mencapai rata-rata tingkat akurasi 93,33%.
English Abstract
Basically a human being is a social creature that needs each other. Surely every human must expect a normal life with a healthy body. A person who loses a physical or a physical disability will definitely be a challenge for them to be able to live social life with other people. Some patients with disabilities, especially those with disabilities, need a tool to enable them to interact normally with the help of rehabilitation tools. The design of rehabilitation tools utilizes from one of the intelligent bio-signal systems ie electrooculographic signal measurement techniques to record the electrical activity of eye movements. The hardware implementation uses five electrode sensors affixed around the eyes, an instrumentation amplifier OP07 with 416 amplification accompanied by high pass filter order 2 cutoff frequency 0.1Hz and low pass filter 2nd order 16Hz cutoff frequency and voltage source of the 9V circuit. Using the baseline method with a combination of calculating the exponential filter and threshold weight values. There is a process of designing and implementing hardware in a printed circuit board. The first software with the search for baseline values of both channels, the process of calculating the weight value of 0.3 exponential filter for the noise can be resolved correctly and issued more accurate results, the determination of the five categories of eye movement ie front, right, left, top, and bottom with threshold value. The results of the test indicate that the first test of each eye movement is performed on 3 subjects reaching an average accuracy rate of 98.66%, the second of 5 consecutive eye movements performed on 3 subjects reaching an average accuracy rate of 96% and the third delay testing reaching flat the accuracy rate of 93.33%.
| Item Type: | Thesis (Sarjana) |
|---|---|
| Identification Number: | SKR/FTIK/2018/211/051801304 |
| Uncontrolled Keywords: | Electrooculography, Baseline, Exponential filter, Gerakan mata, Elektroda |
| Subjects: | 000 Computer science, information and general works > 006 Special computer methods > 006.4 Computer pattern recognition > 006.42 Optical pattern recognition |
| Divisions: | Fakultas Ilmu Komputer > Teknik Informatika |
| Depositing User: | Yusuf Dwi N. |
| Date Deposited: | 23 May 2018 06:38 |
| Last Modified: | 27 Oct 2021 04:01 |
| URI: | http://repository.ub.ac.id/id/eprint/10927 |
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