Brain-Machine Interfaces: Uses and Developments

Carla Bryan, Ivan Rios (Editors)

Series: Computer Science, Technology and Applications
BISAC: COM014000

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Volume 10

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Volume 2

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Special issue: Resilience in breaking the cycle of children’s environmental health disparities
Edited by I Leslie Rubin, Robert J Geller, Abby Mutic, Benjamin A Gitterman, Nathan Mutic, Wayne Garfinkel, Claire D Coles, Kurt Martinuzzi, and Joav Merrick

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Brain-Machine Interfaces: Uses and Developments reports on advances in the development of a speech prosthetic, building on previous data as well as the results of detecting phonemes, words and phrases during overt and covert speech. The following study aims to quantify and qualify the electroencephalographic (EEG) patterns of commonly used control tasks in BCI systems under different task states. The analysed control tasks were: left hand MI, right hand MI, and a relaxed but focused mental state. The original feasibility study within this manuscript aimed to evaluate the scope of applications for a novel neurorehabilitation intervention. Important observations from that initial study and considers possible applications of TLNS Technology in the future are examined. The closing opinion piece seeks to outline why the development of an electrode that does not encourage growth into the electrode tip is ill-advised, with the core reasons being rejection and “less is more”.

Preface

Chapter 1. Advances in the Development of a Speech Prosthesis
(P.R Kennedy, PhD, A.J. Cervantes, MD, C. Gambrell, and P. Ehirim, MD, Neural Signals Inc, Duluth, GA, USA, and others)

Chapter 2. EEG Pattern Differences in Motor Imagery Based Control Tasks Used for Brain-Computer Interfacing: From Training Sessions to Online Control
(Luz Maria Alonso-Valerdi and Francisco Sepulveda, Escuela de Ingeniería y Ciencias, Tecnológico de Monterrey, Monterrey, Nuevo León, México, and others)

Chapter 3. Direct and Indirect Benefits of Translingual Neurostimulation Technology for Neurorehabilitation of Chronic Stroke Symptoms
(Dafna Paltin, Yuri P. Danilov, PhD, and Mitchell E. Tyler, Department of Kinesiology, University of Wisconsin—Madison, WI, USA)

Chapter 4. Essential Trick for Long-Term Recording from the Human Brain
(Phil Kennedy, MD, PhD, Neural Signals Inc.,Duluth, USA, and others)

Index

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