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Publication Type : Conference Paper
Thematic Areas : Learning-Technologies, Medical Sciences, Biotech
Publisher : In Proceedings of the International Conference on Neural Computation Theory and Applications (NCTA-2014), Rome, Italy .
Source : In Proceedings of the International Conference on Neural Computation Theory and Applications (NCTA-2014), Rome, Italy (2014)
Campus : Amritapuri
School : Centre for Cybersecurity Systems and Networks, School of Biotechnology
Center : Computational Neuroscience and Neurophysiology, Amrita Mind Brain Center, Biotechnology, Cyber Security
Department : Computational Neuroscience Laboratory, cyber Security, biotechnology
Year : 2014
Abstract : There have been significant advancements in brain computer interface (BCI) techniques using EEG-like methods. EEG can serve as non-invasive BMI technique, to control devices like wheelchairs, cursors and robotic arm. In this paper, we discuss the use of EEG recordings to control low-cost robotic arms by extracting motor task patterns and indicate where such control algorithms may show promise towards the humanitarian challenge. Studies have shown robotic arm movement solutions using kinematics and machine learning methods. With iterative processes for trajectory making, EEG signals have been known to be used to control robotic arms. The paper also showcases a case-study developed towards this challenge in order to test such algorithmic approaches. Non-traditional approaches using neuro-inspired processing techniques without implicit kinematics have also shown potential applications. Use of EEG to resolve temporal information may, indeed, help understand movement coordination in robotic arm.
Cite this Research Publication : Dr. Shyam Diwakar, Sandeep Bodda, Chaitanya Nutakki, Asha Vijayan, Dr. Krishnashree Achuthan, and Dr. Bipin G. Nair, “Neural Control using EEG as a BCI Technique for Low Cost Prosthetic Arms”, in Proceedings of the 6th International Conference on Neural Computation Theory and Applications (NCTA 2014), Rome, Oct 22-24, 2014.