An Internet of Things operating room platform for neurosurgery

Area of Science:

• Neurosurgery
• Health Informatics
• Sensor Technology

Background:

• Operating rooms (OR) are data-rich environments with strict data security policies.
• Existing data security measures limit the use of valuable OR data for analysis and feedback.
• There is a need for secure, scalable solutions to capture and analyze OR data in real time.

Purpose of the Study:

• To develop and validate a unique sensor-driven, secure, cloud-based data framework for real-time acquisition, streaming, and analytics of OR data.
• To establish an Internet of Things-Operating Room (IoT-OR) platform for surgeon feedback and performance reporting.
• To enable precise, accurate, and fast analytics of surgical data in neurosurgical centers.

Main Methods:

• Deployment of the SmartForceps System, a novel sensorized surgical device, for real-time quantification of tool-tissue force.
• Integration of live-streamed surgical microscope video with time-stamping for correlation with tool-tissue interaction.
• Development of a secure, cloud-hosted IoT platform with custom artificial intelligence (AI) for automated data analysis and continuous model enrichment.

Main Results:

• Successful real-time operation of a cloud-driven, end-to-end secure platform across 3 neurosurgical units in over 250 procedures.
• Establishment of a unique IoT-OR platform linked to smart surgical devices and featuring an intelligent software interface.
• Demonstrated scalability and security of the platform for incorporating additional data sources and global centers.

Conclusions:

• The study validates the utility of sensors, AI, and cloud interconnectivity for real-time surgical monitoring, analytics, and feedback.
• The system creates a secure, data-rich pipeline from closed-door OR data, offering a path toward surgical standardization.
• This digital footprint of surgery enables quantification and analysis at the critical tool-tissue interface.