Analysis of Algorithms for Detection of Pedaling Intention in Brain-Machine Interfaces
The use of brain-machine interfaces in people who has suffered a cerebrovascular accident could help the rehabilitation process through the cognitive involvement of the patient. These interfaces translate the brain waves into commands to control the movement of an assistant mechanical device. Howeve...
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| Published in: | Revista iberoamericana de automática e informática industrial Vol. 16; no. 2; pp. 222 - 231 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | Spanish |
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Universitat Politècnica de València
01.03.2019
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| ISSN: | 1697-7912, 1697-7920 |
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| Abstract | The use of brain-machine interfaces in people who has suffered a cerebrovascular accident could help the rehabilitation process through the cognitive involvement of the patient. These interfaces translate the brain waves into commands to control the movement of an assistant mechanical device. However, the control of these devices should be more stable and achieve a higher accuracy. This work studies if algorithms, such as Stockwell or Hilbert-Huang transform, can improve the control of these devices, and if a personalization by subject or electrode configuration is desirable. Besides, through the analysis of five volunteers is determined that the motor intention can not be detected only by data acquired previously to the movement using desynchronized/synchronized related events. Therefore, it is needed to extend the time processing to the two seconds after the movement starting. |
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| AbstractList | The use of brain-machine interfaces in people who has suffered a cerebrovascular accident could help the rehabilitation process through the cognitive involvement of the patient. These interfaces translate the brain waves into commands to control the movement of an assistant mechanical device. However, the control of these devices should be more stable and achieve a higher accuracy. This work studies if algorithms, such as Stockwell or Hilbert-Huang transform, can improve the control of these devices, and if a personalization by subject or electrode configuration is desirable. Besides, through the analysis of five volunteers is determined that the motor intention can not be detected only by data acquired previously to the movement using desynchronized/synchronized related events. Therefore, it is needed to extend the time processing to the two seconds after the movement starting. |
| Author | M. Ortiz M. Rodríguez-Ugarte E. Iáñez J.M. Azorín |
| Author_xml | – sequence: 1 fullname: M. Ortiz organization: Universidad Miguel Hernández – sequence: 2 fullname: M. Rodríguez-Ugarte organization: Universidad Miguel Hernández – sequence: 3 fullname: E. Iáñez organization: Universidad Miguel Hernández – sequence: 4 fullname: J.M. Azorín organization: Universidad Miguel Hernández de Elche |
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| SubjectTerms | (De)sincronización relacionada a eventos Análisis y tratamiento de señales Intención motora Interfaces Cerebro-Máquina Máquinas de soporte vectorial Offline Rehabilitación Transformada de Fourier Transformada de Hilbert-Huang Transformada de Stoc |
| Title | Analysis of Algorithms for Detection of Pedaling Intention in Brain-Machine Interfaces |
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