Seung‐Mo Hong

Papers

Total Citations

H-Index

About

Seung-Mo Hong is a researcher whose work sits at the intersection of robotics, biomedical engineering, and signal processing. His primary research focus is on the real-time prediction and compensation of physiological tremor—the involuntary, rhythmic oscillations that degrade precision in microsurgical and robotic applications. Hong’s most cited paper, "Multi-step prediction of physiological tremor for robotics applications" (2013, 8 citations), tackles a critical bottleneck in surgical robotics: the unavoidable phase delay of 16–20 ms introduced by hardware filters and sensor pre-filtering. By developing a multi-step prediction algorithm, Hong demonstrated how to anticipate tremor motion ahead of time, effectively neutralizing this delay and enabling smoother, more accurate robotic tool control. This contribution is especially vital for telesurgery and robot-assisted procedures where even millisecond lags can compromise safety and outcomes. While his citation count is modest, the work’s direct relevance to improving real-time performance in medical robotics marks it as a foundational step toward more responsive and reliable surgical systems. Hong’s research continues to inform the design of low-latency, tremor-cancelling controllers, bridging the gap between theoretical signal prediction and practical robotic deployment.