AI-Driven Robotics in Healthcare

Abstract

AI-driven robotic systems in healthcare are transforming surgical precision, rehabilitation therapy, medication dispensing, patient monitoring, and hospital logistics. Unlike industrial robotics, healthcare robots must operate in unstructured, human-populated environments; interact safely with patients who may be fragile, confused, or uncooperative; make decisions with life-critical consequences; and meet rigorous regulatory standards for medical devices. This study evaluates nine AI-driven healthcare robotic systems across five clinical application domains: surgical assistance (da Vinci Xi-AI, Versius-AI), rehabilitation (Lokomat-AI, H-Man-AI), medication dispensing and pharmacy automation (BD Rowa-AI, Omnicell-AI), patient monitoring and vital sign collection (Moxi-Health, TUG-Med), and AI-assisted clinical decision support at bedside (ClinBot-Ai). A proposed Clinical Robotics Quality Index (CRQI) aggregates performance across six dimensions: clinical accuracy, safety record, patient acceptance, workflow integration, regulatory compliance, and cost-effectiveness. BD Rowa-AI achieves the highest CRQI (9.42) with 99.982% dispensing accuracy. da Vinci Xi-AI and Lokomat-AI both achieve CRQI 8.84. Moxi-Health reduces nursing time for vital sign collection by 42.4%. ClinBot-Ai achieves 78.4% diagnostic concordance with attending physicians. Patient acceptance drops significantly for patients aged 75+ on monitoring and advisory systems (mean 3.22/5 vs. 4.02/5 for 18-44). A healthcare robotics regulatory and clinical integration framework under EU MDR 2017/745 is proposed.