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Electroencephalography on Controlling Assistive Device: A Systematic Literature Review Salisa 'Asyarina Ramadhani; Muhammad Ilhamdi Rusydi; Andrivo Rusydi; Minoru Sasaki; Luxfy Roya Azmi
Andalas Journal of Electrical and Electronic Engineering Technology Vol. 4 No. 2 (2024): November 2024
Publisher : Electrical Engineering Dept, Engineering Faculty, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/ajeeet.v4i2.42

Abstract

The present article delves into the practical applications of electroencephalography (EEG) in assistive devices. The article thoroughly summarizes the current state of the art, research trends, methods, and implementation. The focus is primarily on how EEG can operate various assistive devices effectively, incorporating artificial intelligence, machine learning, and several computing methods. The authors emphasize the importance of conducting more research and development in the field and offer valuable insights into its prospective directions. A complete search of the Scopus database from 2017 to 2022, including journals and proceedings such as IEEE Xplore, MDPI, Springer, Frontiers, and ScienceDirect, was conducted to ensure the findings are as comprehensive as possible. Conferring to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, 4397 metadata were transformed into 45. Based on the data synthesis, the following study execution must prioritize determining whether the observed signals are attributable to EEG artifacts or actual EEG signals. The derivation of input signals for controlling helpful devices can be enhanced by utilizing familiar activities, such as facial muscle movements, and employing various machine-learning techniques to ensure high levels of accuracy.
The Influence of Milling on the Structural and Morphological Properties of Waste-Based Active Carbon from Rubber Seeds Using High Energy Milling (HEM) Method Arsyad, Fitri Suryani; Aprilianda; Aulia; Akmal Johan; Ihsan Alfikro; Amiruddin Supu; Ahmad, Nur; Andrivo Rusydi
Science and Technology Indonesia Vol. 11 No. 2 (2026): April
Publisher : Research Center of Inorganic Materials and Coordination Complexes, FMIPA Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26554/sti.2026.11.2.621-631

Abstract

The high-energy milling (HEM) synthesis method has produced activated carbon powder from rubber ore shell waste. The activated carbon was prepared using a chemical method with activation temperatures varying between 400, 500, and 600°C. Temperature optimization resulted in activated carbon with a maximum carbon content at 600°C. The activated carbon was then milled for various times: 0, 30, 60, and 90 minutes. The crystallinity and surface morphology of the samples were then confirmed using an X-ray diffractometer (XRD) and scanning electron microscope (SEM) characterization. Based on the XRD graph, the percentage of structural regularity, or degree of crystallinity, of the activated carbon tended to decrease from 18.17% without milling treatment to 17.52% at 30 minutes of milling, 17.45% at 60 minutes of milling, and 17.35% at 90 minutes of milling. SEM images also show a decrease in the average pore diameter from approximately 0.45 µm to 0.20 µm with a more homogeneous intraparticle morphology structure when the milling time is increased from 30 minutes to 90 minutes. This study demonstrates the potential of rubber seed shell waste for processing into activated carbon. The HEM method can significantly reduce the grain size of activated carbon and increase its surface area and reactivity, making it more effective in applications as an adsorbent and filter.