Human errors, e.g. surgeon’s misoperation, have been recognised as a critical cause to the large amount of medical accidents in hospital. Recently, the concept of Medical Cyber-Physical Systems (MCPS) has been proposed to enable automatic medical device coordination for patient protection. However, MCPS have limited capabilities to detect human errors because of only integrating medical devices, and thus, often result in late device coordination when patients are found to have already developed significant adverse physiological reactions. In this paper, we propose to build context-aware MCPS to avoid such risky situations. We leverage various non-medical devices to capture implicit contextual information when human users are interacting with MCPS. By using these contexts, we significantly raise the system’s awareness to human errors, and thus, allow it to take proper actions as early as possible to avoid the potential accidents. A major challenge in designing such systems, however, is how to deal with context uncertainty without sacrificing patient safety. Contexts are uncertain in nature, but false context detection can trigger unnecessary actions harmful to patient. To address this issue, we develop a novel scheme called ‘context-assessment-action’, where medical knowledge is utilised to assess all context-triggered actions and prohibit the risky ones. To our knowledge, our approach is the first to enable context-awareness for safety-critical systems. Finally, we apply this approach and conduct a case study on patient-controlled analgesia. Experimental results demonstrate the effectiveness of our approach and the great promise of context-aware MCPS for patient safety improvement.
- Medical Cyber-Physical Systems
- patient safety
ASJC Scopus subject areas
- Computational Mechanics
- Computer Vision and Pattern Recognition
- Computer Graphics and Computer-Aided Design