Abstract
Brain-computer interfaces (BCIs) based on brain magnetic fields is a novel trend in the field of rehabilitation robotic that could be leveraged for helping the patients who have lost voluntary muscle control to communicate. This study present an experiment of controlling a virtual drone in three-dimensional space using brain magnetic fields induced by left or right hand motor imagery. We applied optically-pumped magnetometers (OPMs) to capture brain magnetic fields, Subjects sat in the magnetically shield room (MSR) comfortably and performed the motor imagery (MI) task corresponded to the cue provided via an brain magnetic fields based BCI system whilst saving the data attached with variable classlabels. Then, we processed the data in time and frequency domain in order to extract the signal feature in form of an event-related desynchronization (ERD) or event-related synchronization (ERS). Furthermore, machine learning was employed to be the identification tool for motor imagery brain magnetic fields and further, controlled a virtual drone flight according to commands.
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Notes
- 1.
The bridge between QZFM sensor and host computer is UART to USB serial port line.
- 2.
The height of MSR is 1.6 m.
- 3.
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Tan, G., Gai, J., Guo, R., Zhang, G., Lin, Q., Hu, Z. (2023). Virtual Drone Control Using Brain-Computer Interface Based on Motor Imagery Brain Magnetic Fields. In: Ying, X. (eds) Human Brain and Artificial Intelligence. HBAI 2022. Communications in Computer and Information Science, vol 1692. Springer, Singapore. https://doi.org/10.1007/978-981-19-8222-4_14
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DOI: https://doi.org/10.1007/978-981-19-8222-4_14
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