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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) International Journal of Advances in Intelligent Informatics EMITTER International Journal of Engineering Technology Jurnal Informatika Upgris JURNAL MEDIA INFORMATIKA BUDIDARMA JTERA (Jurnal Teknologi Rekayasa) Cyberspace: Jurnal Pendidikan Teknologi Informasi InComTech: Jurnal Telekomunikasi dan Komputer Jurnal Eksplora Informatika Technomedia Journal Jurnal Tekno Insentif Jurnal Telematika Jurnal Sistem Cerdas Jurnal Teknologi Terapan Jurnal SITECH : Sistem Informasi dan Teknologi Mobile and Forensics Competitive Jurnal Teknik Industri Terintegrasi (JUTIN) Journal of Applied Data Sciences Journal of Dinda : Data Science, Information Technology, and Data Analytics Merpati JEECS (Journal of Electrical Engineering and Computer Sciences) Competitive
Syafrial Fachri Pane, Syafrial Fachri
Politeknik Pos Indonesia
Humanities Automotive Engineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Library & Information Science Mechanical Engineering Neuroscience Transportation Other

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MILA: Low-cost BCI framework for acquiring EEG data with IoT Rolly Maulana Awangga; Syafrial Fachri Pane; Dzikri Ahmad Ghifari; Tri Angga Dio Simamora; Mochamad Yusuf Asyhari
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14884

Abstract

The brain is a vital organ in the human body that acts as the center of the human nervous system. Brain-computer interface (BCI) uses electroencephalography (EEG) signals as information on brain activity. Hospitals usually use EEG as a diagnosis of brain disease. Combining EEG as part of IoT (Internet of Things) with high mobility is challenging research. This research tries to make a low-cost BCI framework for motorcycle riders. Analysis of brain activity from EEG data when motorcycle riders turn left or turn right. Therefore, the method of further installation must produce the right features to obtain precise and accurate brainwave characteristics from EEG signals. This research uses the concept of IoT with software engineering to recording human brain waves so that it becomes a practical device for the wearer. The purpose of this study is to create a low-cost BCI framework for obtaining EEG data.
Co-Authors Adiwijaya Alfadian Owen Alfian Akbar Gozali Alit Fajar Kurniawan Amri Yanuar Asyhari, Mochamad Yusuf Bayu Rahmad Azhari Cahya Kurniawan Chandra Kirana Poetra Cokro Edi Prawiro Dinda Majesty Dzikri Ahmad Ghifari Ekra Sanggala Esi Vidia Rahcmadani Faisal Abdullah Fajri, Ravi Rahmatul Fathonah, Rd. Nuraini Siti Fatonah, Nuraini Siti Ferdinan, Dani Gilang Romadhanu Tartila Habibi, Roni Haq, Dzikri Izzatul Harani, Nisa Hanum Helmi Setyawan, Muhammad Yusril I Made Yadi Dharma Iping Supriana Suwardi Irvanizam, Irvanizam Jenly Ramdan Khaera Tunnisa, Khaera Kurniawan, Alit Fajar Kurniawan, Cahya Mahmud Dwi Sulistiyo Maulyanda, Maulyanda Muhammad Firman Kahfi Muhammad Ruslan Maulani Muhammad Yusril Helmi Setyawan Nazhifah, Sri Azizah Poetra, Chandra Kirana Prianto, Cahyo Ramadhan, Bachtiar Rd. Nuraini Siti Fatonah Reksiyano, Rendy Dwi Restiyana Dwi Astuti Rionald, Valen Rolly Maulana Awan Rolly Maulana Awangga, Rolly Maulana Seta Permana Setiawan Assegaf Siregar, M. Amran Hakim Talan, Maylinda Christy Yosefina Tri Angga Dio Simamora Vegita, Yola Wijayanti, Diana Asri Zain, Rofi Nafiis