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Nursing Clinical Information System01:27

Nursing Clinical Information System

Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
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Modular multiple sensors information management for computer-integrated surgery.

Alberto Vaccarella1, Andinet Enquobahrie, Giancarlo Ferrigno

  • 1NearLab, Dipartimento di Bioingegneria, Politecnico di Milano, Milano, Italy. alberto.vaccarella@mail.polimi.it

The International Journal of Medical Robotics + Computer Assisted Surgery : MRCAS
|March 13, 2012
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Summary
This summary is machine-generated.

A new centralized software architecture effectively synchronizes data from multiple sensors in computer-integrated surgery (CIS). This system minimizes synchronization errors, ensuring reliable spatial and temporal data for enhanced surgical procedures.

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Area of Science:

  • Medical Technology
  • Computer Science
  • Surgical Innovation

Background:

  • Modern operating rooms (ORs) are evolving with computer-integrated surgery (CIS) systems to improve surgical outcomes, safety, and standardization.
  • CIS utilizes various sensors, including position-sensing devices, force sensors, and intra-operative imaging.
  • Integrating data from multiple sensors presents challenges in synchronization and spatial consistency.

Purpose of the Study:

  • To propose and evaluate a centralized, multi-sensor management software architecture for distributed CIS systems.
  • To address issues of spatial and temporal consistency for sensor data within CIS.
  • To assess the feasibility and latency of a centralized data acquisition module for surgical navigation.

Main Methods:

  • Developed a centralized data server module using a client-server architecture.
  • Utilized open-source libraries: Image-Guided Surgery Toolkit (IGSTK) and OpenCV.
  • Benchmarked the system using the ROBOCAST project and tested latency with optical/electromagnetic tracking and ultrasound (US) imaging.

Main Results:

  • The centralized approach effectively minimizes synchronization errors between different data sources.
  • Client-server communication latency was measured at a median of 2 ms for tracking systems.
  • Latency for ultrasound (US) images was a median of 40 ms.

Conclusions:

  • The proposed centralized architecture is suitable for neurosurgery applications.
  • The introduced latency is acceptable, not impacting tracking system performance.
  • Ultrasound image frame rate is limited to 25 fps, providing adequate visual feedback for surgeons.