Abstract | ||
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Several kinds of brain–computer interface (BCI) systems have been proposed to compensate for the lack of medical technology for assisting patients who lose the ability to use motor functions to communicate with the outside world. However, most of the proposed systems are limited by their nonportability, impracticality, and inconvenience because of the adoption of wired or invasive electroencephalography acquisition devices. Another common limitation is the shortage of functions provided because of the difficulty of integrating multiple functions into one BCI system. In this paper, we propose a wireless, noninvasive and multifunctional assistive system which integrates steady state visually evoked potential-based BCI and a robotic arm to assist patients to feed themselves. Patients are able to control the robotic arm via the BCI to serve themselves food. Three other functions: 1) video entertainment; 2) video calling; and 3) active interaction are also integrated. This is achieved by designing a functional menu and integrating multiple subsystems. A refinement decision-making mechanism is incorporated to ensure the accuracy and applicability of the system. Fifteen participants were recruited to validate the usability and performance of the system. The averaged accuracy and information transfer rate achieved is 90.91% and 24.94 bit per min, respectively. The feedback from the participants demonstrates that this assistive system is able to significantly improve the quality of daily life. |
Year | DOI | Venue |
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2019 | 10.1109/TCDS.2018.2820153 | IEEE Transactions on Cognitive and Developmental Systems |
Keywords | DocType | Volume |
Signal to noise ratio,Wireless communication,Harmonic analysis,Feature extraction,Electroencephalography,Robots,Correlation | Journal | 11 |
Issue | ISSN | Citations |
3 | 2379-8920 | 3 |
PageRank | References | Authors |
0.36 | 0 | 7 |
Name | Order | Citations | PageRank |
---|---|---|---|
Chin-Teng Lin | 1 | 3840 | 392.55 |
Ching-Yu Chiu | 2 | 3 | 0.36 |
Avinash Kumar Singh | 3 | 31 | 13.77 |
Jung-Tai King | 4 | 52 | 9.83 |
Li-Wei Ko | 5 | 519 | 58.70 |
Yun-Chen Lu | 6 | 3 | 0.36 |
Yu-Kai Wang | 7 | 74 | 16.92 |