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About

Suprijanto Suprijanto is a researcher whose work sits at the compelling intersection of brain-computer interfaces (BCI), robotics, and autonomous systems, with a particular focus on developing assistive technologies for individuals with physical disabilities. His most influential contribution, "A Collaborative Control of Brain Computer Interface and Robotic Wheelchair" (2015), has garnered 21 citations and introduced an innovative scheme integrating non-invasive BCI with robotic wheelchair systems using steady-state visual evoked potential (SSVEP) methodology to interpret EEG signals — a meaningful step toward restoring independence for mobility-impaired patients. This work was further extended through his heuristic SSVEP-based BCI system, reinforcing his commitment to practical, patient-centered applications. Beyond neural interfaces, Suprijanto has made notable contributions to mobile robotics, developing a modified particle filter approach for more computationally efficient robot localization (10 citations) and a Lyapunov-based wall-following control algorithm that eliminates the need for orientation sensors (7 citations). Across these varied yet interconnected domains, his research consistently emphasizes elegant, resource-conscious solutions to real-world engineering challenges, making his body of work particularly valuable for students and engineers pursuing human-robot interaction and autonomous navigation research.