Surgical Safety Technologies (SST), the global leader in AI-powered clinical intelligence, today announced the integration of kinematic data into its OR Black Box® - the market's only comprehensive solution for improving perioperative quality, safety, and efficiency. This new capability introduces advanced motion tracking to laparoscopic procedures, offering next-generation insight into surgical technique and performance.
The integration of AI-powered computer vision kinematic data into the OR Black Box marks a significant leap in surgical intelligence - one rooted in decades of research and a deep understanding of where healthcare must evolve. Motion metrics have long been recognized as strong indicators of surgical proficiency, but their use has been limited to controlled simulations, academic settings, or proprietary robotic systems. For the first time, our proprietary AI technology generates comprehensive laparoscopic kinematic data - capturing movement smoothness, path length, velocity profiles, and instrument economy - regardless of device manufacturer or camera system. This camera-agnostic surgical intelligence solution brings advanced motion analysis to all laparoscopic cases in real-world operating rooms, not just those performed with specific equipment.
"By integrating motion analytics into the OR Black Box, we're redefining how surgical proficiency is assessed, taught, and improved," said Teodor Grantcharov, MD, Founder of SST. "We're providing a new dimension of analysis for surgeons and health systems, powered by transparency and the most trustworthy, objective data possible. This will illuminate opportunities for surgical performance improvement in ways that would otherwise not be achievable."
SST's kinematic capability further extends the analytical depth of the OR Black Box - enabling the most complete, objective evaluation of surgical skill. Users will be able to visualize and compare motion profiles to identify technical inefficiencies, assess procedural competency, and even track surgical proficiency over time. This advancement opens unprecedented research opportunities for the academic community, providing access to standardized kinematic datasets previously unavailable or locked within proprietary systems - a critical foundation for developing next-generation AI models that can objectively assess technical performance across surgical specialties. Such forward-thinking innovation reflects not only technological leadership, but also strategic foresight into the kind of data-driven intelligence solutions health systems need to drive lasting improvements in surgical care delivery.
"This technology represents a transformative opportunity for surgical education and research worldwide," said Filippo Filicori, MD, System Chief of Surgical Innovation at Northwell Health and Chair of the SAGES AI Committee. "Access to standardized kinematic data will empower academic institutions globally to build objective assessment frameworks and collaborative research initiatives that were previously unattainable. Beyond individual training programs, this creates the foundation for a universal language of surgical movement that researchers can leverage to develop evidence-based educational models, establish international benchmarks for technical proficiency, and ultimately accelerate the democratization of surgical expertise across borders."
