Surgical Automation Controller Dynamic Level Adjustment
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Solution Overview
Problem
Surgical procedures often face challenges in efficiently automating tasks due to the slow adoption of new technologies in medical facilities, leading to suboptimal use of advanced surgical instruments and systems, and there is a need for adaptive autonomy levels and failure mitigation strategies in surgical devices.
Innovation Solution
A surgical device that can dynamically adjust its automation levels based on real-time data, including user, environmental, and historical data, and switch between different autonomous functions to mitigate failures, while also adapting its control algorithms and interconnecting with various surgical systems for optimized performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If surgical tasks are automated using advanced surgical instruments and systems, then productivity and surgical outcomes are improved, but device complexity and difficulty of implementation increase
Solution Approach 1:
The surgical automation system is divided into multiple autonomous functions with distinct automation levels (e.g., Level 1: guidance, Level 2: task execution, Level 3: decision-making). Each function can be independently activated or deactivated based on surgical needs, allowing the system to provide automation only where required while maintaining simplicity in other areas.
Solution Approach 2:
The system dynamically adjusts the level of automation based on real-time surgical context, performance monitoring, and trigger events. The controller can switch between different autonomous functions and automation levels during a procedure, enabling the system to adapt to changing surgical conditions while optimizing the balance between automation benefits and complexity management.
2Adaptability or versatility
If multiple autonomous functions with different automation levels are implemented, then adaptability to surgical conditions is improved, but device complexity increases
Solution Approach 1:
The autonomous functions are segmented into distinct levels (first autonomous function, second autonomous function, etc.) with different degrees of automation. Each function has a specific trigger event and performance monitoring mechanism, allowing the system to manage complexity through modular organization while maintaining high adaptability.
Solution Approach 2:
The system continuously monitors performance of autonomous functions using real-time surgical data and compares it against trigger event thresholds. This feedback mechanism enables automatic adjustment of automation levels and switching between functions based on actual surgical performance, reducing the need for complex manual control while maintaining adaptability.
3Reliability
If real-time monitoring and performance comparison are implemented, then reliability and safety are improved, but use of energy and computational resources increase
Solution Approach 1:
The system monitors performance of autonomous functions by comparing real-time surgical data against pre-established trigger event thresholds and ideal surgical data. This feedback approach enables reliable detection of performance degradation and automatic response to trigger events while using computational resources efficiently by only analyzing data when deviations from expected performance occur.
Data Source
AI summary
Examples described herein may include a surgical computing system that determines an autonomous operation parameter and generates a control signal for an autonomous operation based on the autonomous operation parameter. The surgical computing system may obtain surgical data and determine the autonomous operation parameter based on the surgical data. The surgical computing system may obtain surgical data and determine the autonomous operation parameter based on the surgical data. The surgical computing system may send the control signal for the autonomous operation, for example, to one or more smart surgical devices.