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Commanding An Avatar Through Mind: An Approach Towards a Paradigm Shift in Adaptive Brain-Computer Interface for Robotic or Wheel-Chair Based Navigation - Softcover
Inhaltsangabe
Among several, one of the main goals of Brain-Computer Interface (BCI) system is to improve the quality of life of paralyzed persons. While significant effort has been made to recognize user intention, the necessity of predicting user intention in the context of BCI for navigation to design a dynamic interface, has not been addressed yet. State-of-the-art BCI system has low bandwidth because of which the user is subjected to much cognitive or interaction load. However a BCI system designed with dynamic customization feature to adapt as per individual user, would indeed reduce the interaction load and provide embodiment feeling to the user. Therefore this book describes an intelligent BCI based on reinforcement learning approach to learn the user behavior and predict the intentions in the context of a robotic navigation. Even with an adaptive BCI, the system is error-prone due to misclassification of the user's intention. This book also focuses on Support Vector Machines (SVM) classifier for detecting error-related potentials and shows comparable classification performance of SVM to that of state-of-the-art classifiers such as Gaussian classifier and Bayesian filter methods.
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Reseña del editor
Among several, one of the main goals of Brain-Computer Interface (BCI) system is to improve the quality of life of paralyzed persons. While significant effort has been made to recognize user intention, the necessity of predicting user intention in the context of BCI for navigation to design a dynamic interface, has not been addressed yet. State-of-the-art BCI system has low bandwidth because of which the user is subjected to much cognitive or interaction load. However a BCI system designed with dynamic customization feature to adapt as per individual user, would indeed reduce the interaction load and provide embodiment feeling to the user. Therefore this book describes an intelligent BCI based on reinforcement learning approach to learn the user behavior and predict the intentions in the context of a robotic navigation. Even with an adaptive BCI, the system is error-prone due to misclassification of the user's intention. This book also focuses on Support Vector Machines (SVM) classifier for detecting error-related potentials and shows comparable classification performance of SVM to that of state-of-the-art classifiers such as Gaussian classifier and Bayesian filter methods.
Biografía del autor
Dullal Ghosh holds a bachelor's degree in Mechanical Engineering from NIT-Allahabad, India. He has completed master's program in Mechatronics from KTH, Sweden and master thesis work related to Brain-Computer Interface at TU Munich, Germany as an Erasmus exchange scholar in the year 2012. Currently he works as a Design Engineer at General Electric.
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Commanding An Avatar Through Mind
Verlag:
LAP LAMBERT Academic Publishing Nov 2013, 2013
ISBN 10: 3659454729
ISBN 13: 9783659454721
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Taschenbuch
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Taschenbuch. Zustand: Neu. Neuware -Among several, one of the main goals of Brain-Computer Interface (BCI) system is to improve the quality of life of paralyzed persons. While significant effort has been made to recognize user intention, the necessity of predicting user intention in the context of BCI for navigation to design a dynamic interface, has not been addressed yet. State-of-the-art BCI system has low bandwidth because of which the user is subjected to much cognitive or interaction load. However a BCI system designed with dynamic customization feature to adapt as per individual user, would indeed reduce the interaction load and provide embodiment feeling to the user. Therefore this book describes an intelligent BCI based on reinforcement learning approach to learn the user behavior and predict the intentions in the context of a robotic navigation. Even with an adaptive BCI, the system is error-prone due to misclassification of the user's intention. This book also focuses on Support Vector Machines (SVM) classifier for detecting error-related potentials and shows comparable classification performance of SVM to that of state-of-the-art classifiers such as Gaussian classifier and Bayesian filter methods.Books on Demand GmbH, Überseering 33, 22297 Hamburg 68 pp. Englisch. Artikel-Nr. 9783659454721
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