Abstract
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 language | English |
|---|---|
| Article number | 369425 |
| Journal | Advances in Human-Computer Interaction |
| Volume | 2013 |
| DOIs | |
| Publication status | Published - 2013 |
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ASJC Scopus subject areas
- Human-Computer Interaction
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Controlling assistive machines in paralysis using brain waves and other biosignals. / De Almeida Ribeiro, Paulo Rogério; Lima Brasil, Fabricio; Witkowski, Matthias; Shiman, Farid; Cipriani, Christian; Vitiello, Nicola; Carrozza, Maria Chiara; Soekadar, Surjo Raphael.
In: Advances in Human-Computer Interaction, Vol. 2013, 369425, 2013.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Controlling assistive machines in paralysis using brain waves and other biosignals
AU - De Almeida Ribeiro, Paulo Rogério
AU - Lima Brasil, Fabricio
AU - Witkowski, Matthias
AU - Shiman, Farid
AU - Cipriani, Christian
AU - Vitiello, Nicola
AU - Carrozza, Maria Chiara
AU - Soekadar, Surjo Raphael
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
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U2 - 10.1155/2013/369425
DO - 10.1155/2013/369425
M3 - Article
VL - 2013
JO - Advances in Human-Computer Interaction
JF - Advances in Human-Computer Interaction
SN - 1687-5893
M1 - 369425
ER -