Darlis Herumurti

Sepuluh Nopember Institute of Technology

Papers

Total Citations

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About

Darlis Herumurti is a prominent researcher in the fields of brain-computer interfaces (BCI), robotics, and intelligent control systems. His most cited work, "Robot Motion Control Using the Emotiv EPOC EEG System" (2018, 7 citations), demonstrates a pioneering approach to translating electroencephalogram (EEG) signals directly into robotic motion commands. This contribution advances the practical application of non-invasive BCI technology, enabling more intuitive human-robot interaction by allowing users to control mechanical systems through thought alone. Herumurti’s research addresses critical challenges in signal processing and real-time control, bridging the gap between neural activity and autonomous systems. His work has implications for assistive robotics, rehabilitation, and human augmentation, offering new possibilities for individuals with motor impairments. Beyond this flagship study, Herumurti continues to explore the integration of machine learning with EEG data to enhance system accuracy and responsiveness. His contributions are steadily building a foundation for next-generation, thought-driven robotic interfaces, marking him as an emerging authority in the convergence of neuroscience and robotics engineering.