Controlling assistive machines in paralysis using brain waves and other biosignals

Paulo Rogério De Almeida Ribeiro, Fabricio Lima Brasil, Matthias Witkowski, Farid Shiman, Christian Cipriani, Nicola Vitiello, Maria Chiara Carrozza, Surjo Raphael Soekadar

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Article number369425
JournalAdvances in Human-Computer Interaction
Publication statusPublished - 2013

ASJC Scopus subject areas

  • Human-Computer Interaction


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