Implementación de una interfaz cerebro-computador (BCI) que permita controlar el movimiento de elevación y avance durante el vuelo de un cuadricóptero (dron)
In this project, a brain-computer interface (BCI) is implemented allowing flight control of a simulated drone through the use of steady state visual evoked potentials (SSVEP) that were generated by a light dashboard that could be adjusted to blink at different frequencies. Through a sweep of frequen...
| Autor Principal: | Castro Gutiérrez, Andrés Felipe |
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| Otros Autores: | Ortega Hernández, Juan Felipe |
| Formato: | info:eu-repo/semantics/bachelorThesis |
| Idioma: | spa |
| Publicado: |
Universidad de San Buenaventura - Cali
2018
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| Materias: | |
| Acceso en línea: |
http://hdl.handle.net/10819/6255 |
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| Sumario: |
In this project, a brain-computer interface (BCI) is implemented allowing flight control of a simulated drone through the use of steady state visual evoked potentials (SSVEP) that were generated by a light dashboard that could be adjusted to blink at different frequencies. Through a sweep of frequencies made between 20 and 40 Hz, five different frequencies can be identified: 22, 25, 26, 27 and 34 Hz, which were assigned to the same number of movements: ascent, descent, advance, rewind and rotate clockwise, respectively. The project makes use of a Matlab script that is responsible for the reception and processing of the EEG data, identifying the stimulus selected by the user, calculating which of the five frequencies has the highest energy during a control period of two seconds. The interface was validated by applying five pattern tests to six users, each test had the duration of one minute, the efficiency found was between 72.18% and 95.33%. |
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