Papers
2
Total Citations
14
H-Index
2
About
Amine Bendahmane is a researcher at the intersection of robotics and brain-computer interfaces (BCIs), whose work pushes the boundaries of autonomous systems and neural signal processing. In robotics, Bendahmane has tackled the critical challenge of energy-constrained exploration, developing a modified Butterfly Optimization Algorithm that enables robots to efficiently map unknown environments while managing limited power resources—a contribution that has garnered 9 citations since 2022. This work addresses a fundamental bottleneck in field robotics, where autonomous operation duration is often limited by battery life. In the domain of BCIs, Bendahmane has made notable contributions to hybrid systems that combine multiple neural paradigms. His 2024 study on the effects of stimulation presentation order in sequential ERP/SSVEP hybrid BCIs (5 citations) explores how to optimize the timing of different neural responses to improve system performance. This research is particularly significant because concurrent hybrid BCIs that combine endogenous and exogenous paradigms face limitations in command set size, and Bendahmane’s work offers insights into overcoming these constraints. By investigating how the sequence of visual and cognitive stimuli affects brain signal detection, he is helping to design more responsive and versatile BCI systems that could eventually enable faster, more natural communication for users with motor impairments.
Research Focus
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Top Papers
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