%0 Journal Article
%T Controlling Assistive Machines in Paralysis Using Brain Waves and Other Biosignals
%A Paulo Rog¨Śrio de Almeida Ribeiro
%A Fabricio Lima Brasil
%A Matthias Witkowski
%A Farid Shiman
%A Christian Cipriani
%A Nicola Vitiello
%A Maria Chiara Carrozza
%A Surjo Raphael Soekadar
%J Advances in Human-Computer Interaction
%D 2013
%I Hindawi Publishing Corporation
%R 10.1155/2013/369425
%X The extent to which humans can interact with machines significantly enhanced through inclusion of speech, gestures, and eye movements. However, these communication channels depend on a functional motor system. As many people suffer from severe damage of the motor system resulting in paralysis and inability to communicate, the development of brain-machine interfaces (BMI) that translate electric or metabolic brain activity into control signals of external devices promises to overcome this dependence. People with complete paralysis can learn to use their brain waves to control prosthetic devices or exoskeletons. However, information transfer rates of currently available noninvasive BMI systems are still very limited and do not allow versatile control and interaction with assistive machines. Thus, using brain waves in combination with other biosignals might significantly enhance the ability of people with a compromised motor system to interact with assistive machines. Here, we give an overview of the current state of assistive, noninvasive BMI research and propose to integrate brain waves and other biosignals for improved control and applicability of assistive machines in paralysis. Beside introducing an example of such a system, potential future developments are being discussed. 1. Introduction The way humans interact with computers has changed substantially in the last decades. While, for many years, the input from the human to the machine was mainly managed through keystrokes, then later through hand movements using a computer mouse, other potential input sources have been opened up allowing more intuitive and effortless control, for example, based on speech [1], gestures [2], or eye movements [3], all depending on a functional motor system. As cardiovascular diseases increase and people live longer, an increasing number of people suffer from conditions that affect their capacity to communicate or limit their mobility [4], for example, due to stroke, neurodegenerative disorders, or hereditary myopathies. Motor disability can also result from traumatic injuries, affecting the central or peripheral nervous system or can be related to amputations of the upper or lower extremities. While these handicapped people would benefit the most from assistive machines, their capacity to interact with computers or machines is often severely impeded. Among the most important causes of neurological disabilities resulting in permanent damage and reduction of motor functions or the ability to communicate are stroke, multiple sclerosis (MS), spinal cord injury (SCI),
%U http://www.hindawi.com/journals/ahci/2013/369425/