Mark Asselin

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About

Mark Asselin is a biomedical engineer whose research focuses on the intersection of surgical robotics, optical sensing, and automated tissue characterization. His work aims to enhance intraoperative decision-making by developing intelligent systems that can detect and classify tissue types in real time. In his most-cited paper, "Sensor-Based Automated Detection of Electrosurgical Cautery States" (2022, 6 citations), Asselin introduced a novel method to automatically detect energy events from electrosurgical tools by integrating navigation system data. This approach enables the precise localization of tissue cauterization events, paving the way for sensor-classified tissue mapping during surgery. His earlier work, "Robotic tissue scanning with biophotonic probe" (2020, 2 citations), explored the use of Raman spectroscopy—a molecular analysis technique—for real-time, automated tissue classification. By combining robotic scanning with biophotonic probes, Asselin demonstrated a path toward minimally invasive, high-accuracy tissue identification without human intervention. Though early in his career, Asselin’s contributions are significant for advancing autonomous surgical systems and improving surgical precision. His research holds promise for reducing errors in electrosurgery and enabling more reliable, data-driven intraoperative tissue analysis.