Nathaniel Chandra Harjanto
Papers
1
Total Citations
3
H-Index
1
About
Nathaniel Chandra Harjanto’s research sits at the intersection of neural engineering and assistive robotics, with a focus on developing brain-computer interface (BCI) systems that translate human intention directly into machine action. His most cited work, a 2015 study on a “Heuristic Steady State Visual Evoked Potential based Brain Computer Interface system for robotic wheelchair application,” pioneered a practical, non-invasive BCI framework that allows individuals with severe motor disabilities to control a robotic wheelchair using steady-state visual evoked potentials (SSVEP). By integrating heuristic algorithms to improve signal classification and real-time responsiveness, Harjanto’s system bypasses the need for peripheral muscle activity, offering a direct neural pathway to mobility. Although his citation count remains modest—with the flagship paper accruing 3 citations—his contribution is notable for its translational ambition: it directly addresses a pressing clinical need for autonomy in patients with paralysis or neuromuscular disorders. Harjanto’s work exemplifies how BCI technology can move from laboratory prototypes toward tangible, life-enhancing applications, laying groundwork for future innovations in assistive robotics and human-machine symbiosis.
Research Focus
Key Achievements
Top Papers
- 1