In a move to revolutionize clinical training, the research team at Tri-Service General Hospital (TSGH) has developed a "Smart Sensing Simulation Arm." By integrating Embodied Cognitive Learning theory with high-precision sensors, the team has transformed traditional static medical models into an interactive, AI-driven system designed to eliminate "blind testing" in phlebotomy practice.

Technical Superiority and Real-time Feedback:

• Nerve Detection Module: Unlike standard trainers, this system features a tri-axial accelerometer and copper mesh induction to detect if a needle has strayed into high-risk nerve zones.
• Dual-Mode Learning: The AI provides real-time guidance on needle angles and immediate error analysis via voice prompts, significantly boosting student confidence.
• Proven Clinical Efficacy: In a study of 99 medical interns, the system showed statistically significant improvements (p < 0.05) in accuracy and emergency response. Notably, "low-achieving" students showed the greatest progress, highlighting the system's remedial potential.

Project leader and medical technologist Shan-Shan Hsieh noted that the system, which secured a Taiwan utility patent in March 2024, is ready for institutional rollout. Initial deployment is planned for NDMC, TMU, and NYCU, with future goals to launch a subscription-based remote platform targeting high-demand markets like Singapore and Thailand.

Resource: 《新創動態》抽血實習不再盲測！三總打造「智慧感應手臂」 AI精準監控零誤差