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A research paper led by Asad Rasheed, Ph.D. researcher at the School of Electronic and Electrical Engineering, Kyungpook National University (KNU), Republic of Korea), under the supervision of Prof. Kalyana C. Veluvolu (School of Electronics Engineering, KNU), and in collaboration with Prof. Ho-Won Lee (Brain Science and Engineering Institute, School of Medicine, KNU), has been published and awarded the Best Contribution Award at the 17th Biomedical Engineering International Conference (BMEiCON 2025), held from July 15–18, 2025, in Chiang Mai, Thailand.
This study, titled “Physiological Tremor Modeling with Singular Spectrum Analysis-Based Quaternion Extreme Learning Machine for Handheld Surgical Robotics,” proposes a novel framework that integrates singular spectrum analysis (SSA) with quaternion extreme learning machine (QELM) to accurately model and compensate for physiological tremors in three-dimensional space during handheld robotic surgery. Unlike conventional methods that treat each axis of tremor independently, this approach leverages cross-dimensional coupling, significantly improving tremor estimation accuracy and real-time filtering performance.
The proposed SSA-QELM framework demonstrated superior accuracy compared to state-of-the-art techniques, validating its potential for enhancing the precision and safety of microsurgical procedures.
For this contribution, Asad Rasheed received the “Best Contribution Award” at BMEiCON 2025.
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