A Comprehensive Review of Gauze and Mop Counting Automation Systems for Orthopedic Surgical Safety
Abstract
Retained surgical items (RSIs), particularly gauze pieces and mops, remain a preventable yet persistent threat to patient safety in orthopedic operations. Manual counting protocols, though standardized worldwide, are vulnerable to human fatigue, distraction, and workflow complexity conditions frequently intensified in lengthy orthopedic procedures that involve multiple instruments, draping layers, and substantial blood loss. To address these challenges, diverse automation systems have been developed using bar-coding, radio-frequency identification (RFID), radiofrequency detection (RFD) wands, computer vision (CV), and sensor-fusion architectures. This paper presents a comprehensive review of gauze and mop counting automation systems with a specific focus on orthopedic surgical safety. A systematic literature search was conducted across Scopus, PubMed, IEEE Xplore, and ScienceDirect databases for the period January 2010 to May 2025 using PRISMA based screening criteria. Each study was analyzed for detection accuracy, workflow integration, sterility, human factors, and compliance with international standards (ISO 13485, 14971, IEC 60601).
The review identifies that while RFID and RFD technologies achieve high detection sensitivity, they face interference and sterilization constraints; computer vision approaches offer real-time potential but remain limited by dataset variability and occlusion. Few studies report on orthopedic specific validation or multimodal fusion strategies. The synthesis highlights critical research gaps in interoperability, calibration, regulatory validation, and human-automation collaboration.
Building upon these findings, the paper proposes a robotics oriented framework integrating RFID and CV within a closedloop counting ecosystem capable of edge-level decision making and standardized audit trails. Such an approach could substantially enhance count accuracy, reduce intra-operative delays, and strengthen traceability. The review thus provides a consolidated evidence base and future roadmap toward intelligent, standards-compliant counting automation for safer orthopedic surgery. This review identifies critical pathways for future research in robotics-assisted surgical safety systems.
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Introduction
Retained surgical items (RSIs) primarily gauze pieces and mops inadvertently left inside the patient’s body remain a serious but preventable source of postoperative complications. The issue persists across surgical specialties despite stringent manual counting and verification protocols. The frequency of RSIs is estimated at one per 1,000 - 1,500 intra-abdominal surgeries, with underreporting masking the true burden (Steelman et al., 2018). RSIs lead to foreign body reactions, infections, reoperations, and legal actions, posing direct threats to both patient safety and hospital credibility (Rupp et al., 2012).
Conclusion
Automation in surgical safety has progressed substantially, yet orthopedic RSIs remain a challenge due to human error and environmental complexity. Reviewing RFID, RFD, and AI-based approaches reveals strong potential but limited clinical translation. This paper proposes a conceptual multimodal framework combining RFID and computer vision, grounded in robotics and automation principles. The system architecture emphasizes multimodal redundancy, regulatory compliance, and human–machine synergy. While implementation is beyond current scope, this work provides a research blueprint for doctoral scholars aiming to achieve verifiable, deployable, and standard-compliant automation systems for surgical safety. Ultimately, this review bridges engineering and medicine laying a path toward data-driven, intelligent operating rooms capable of achieving zero retained surgical items. The proposed review contributes a conceptual roadmap that robotics researchers and healthcare engineers can extend into experimental validation, thereby strengthening surgical safety automation frameworks.