Desain Algoritma Autonomous Deep Learning (ADL) untuk Sistem Kontrol Tangan Prostetis pada Disabilitas
DOI:
https://doi.org/10.26905/jasiek.v7i2.14184Keywords:
Disabilitas, EEG, Klasifikasi, Kontrol, ADLAbstract
Penyandang Disabilitas (ODD) memiliki risiko kemiskinan yang tinggi di Indonesia dan dianggap tidak produktif. Menurut data Badan Pusat Statistik (BPS), pada tahun 2019-2020, jumlah penyandang disabilitas di Indonesia mencapai lebih dari 28 juta orang. Tangan palsu telah menjadi solusi untuk membantu individu penyandang disabilitas meningkatkan kualitas hidupnya. Pemrosesan sinyal EEG untuk kontrol prostetik masih tergolong baru, dan diperlukan penelitian lebih lanjut untuk mengoptimalkan kinerja algoritma. diusulkan menggunakan desain algoritma Autonomous Deep Learning (ADL). Struktur jaringan dapat dibangun dari awal tanpa adanya pengaturan manual, mengingat kompleksitas jaringan saraf yang sering mengalami overfitting, model tidak efektif dalam klasifikasi. Hasil percobaan dari 6 subjek dengan rata-rata 96% dengan error 10% pada subjek mandiriReferences
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