Surgical Hub Algorithm Updates for Intraoperative 3D Recognition
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Solution Overview
Problem
Existing surgical imaging systems are limited in their ability to recognize and convey three-dimensional structural information and dimensions intraoperatively, often failing to communicate concealed structures and physical contours effectively.
Innovation Solution
A surgical hub and instrument system that establishes a communication pathway with a cloud computing system, aggregating data from multiple surgical devices, updating control algorithms based on this data, and receiving additional updates to enhance recognition and communication capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If cloud-based data aggregation and algorithm updates are implemented, then the ability to recognize and convey three-dimensional structural information is improved, but device complexity and communication requirements increase
Solution Approach 1:
A surgical hub is introduced as an intermediary device between surgical instruments and the cloud computing system. The hub aggregates data from multiple surgical devices, processes information, and communicates with the cloud, thereby reducing the complexity burden on individual instruments while enabling enhanced three-dimensional recognition capabilities through cloud-based algorithms.
Solution Approach 2:
The system is divided into modular components: surgical instruments, a central surgical hub, and a cloud computing system. This segmentation allows each component to perform specific functions independently, with the hub handling local data aggregation and the cloud handling complex algorithm processing, thus managing overall system complexity while improving measurement precision.
2Manufacturing precision
If continuous communication with cloud computing system is maintained, then algorithm accuracy is improved, but loss of time and communication energy increase
Solution Approach 1:
The surgical hub pre-processes and aggregates data from multiple surgical devices before transmitting to the cloud. This preliminary action reduces the amount of data that needs to be communicated continuously, allowing the system to maintain algorithm accuracy through periodic updates while minimizing communication time and energy consumption.
Solution Approach 2:
The system implements a feedback mechanism where the cloud computing system provides updated algorithms to the surgical hub, which then applies these algorithms to improve the accuracy of surgical instrument control. This feedback loop enables continuous improvement of control accuracy without requiring constant communication, as updates are transmitted periodically when necessary.
Data Source
AI summary
Examples here describe a surgical system that may include a cloud computing system, a surgical hub, and a surgical instrument. The cloud computing system may be configured to aggregate data from multiple surgical devices. The surgical hub may determine whether communication is available with the cloud computing system, may receive the aggregate data from the multiple surgical devices via the receiver, may update one or more surgical hub control algorithms based on the aggregated data received, and may continue to communicate with the cloud computing system to receive additional updates, wherein the additional updates relate to updated aggregate data determined by the cloud computing system. The surgical instrument may determine whether communication is available with the cloud computing system and with the surgical hub and may receive the aggregate data relating to the multiple surgical devices from the cloud computing system or the surgical hub via the receiver.