Adaptive Robot-Assisted Procedure Planning System
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Solution Overview
Problem
Current planning tools for robot-assisted medical procedures are generic and non-adaptive, failing to account for specific surgeon, patient, or environmental parameters, and do not effectively evaluate procedures for improving efficiency and patient outcomes.
Innovation Solution
A system that generates and evaluates procedure plans for robot-assisted medical systems based on various inputs, including procedure type, surgeon information, facility details, staff information, patient data, and prior procedure analysis, using a processor and memory with computer-readable instructions to create adaptive plans and performance metrics, allowing for continuous improvement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If generic planning tools are used for robot-assisted medical procedures, then the system is simple and easy to implement, but the procedure plan cannot be adapted to specific surgeon, patient, or environmental parameters
Solution Approach 1:
The planning system is divided into multiple independent modules: procedure type identification module, surgeon information module, patient information module, facility information module, staff information module, and prior procedure analysis module. Each module handles specific parameters independently, allowing the system to adapt to various inputs without becoming overly complex as a whole.
Solution Approach 2:
The procedure plan is generated dynamically based on real-time inputs from multiple sources including surgeon preferences, patient-specific anatomy and medical history, facility constraints, and staff availability. The system continuously adapts the procedure plan as new information becomes available during the pre-operative planning phase.
2Adaptability or versatility
If static planning tools are used, then the system is simple to operate, but the system cannot respond to new information that may improve patient outcomes
Solution Approach 1:
The system incorporates feedback mechanisms where prior procedure data is analyzed and used to improve future procedure plans. Performance metrics from previously executed procedures are fed back into the planning system to refine and optimize subsequent plans, creating a continuous improvement loop that responds to new information while maintaining operational simplicity.
Solution Approach 2:
The system performs preliminary analysis of prior procedure data and generates baseline procedure plans before the actual procedure begins. This advance preparation allows the system to be ready to respond to new information that arises during the procedure while having already established a solid foundational plan.
3Productivity
If procedure plans do not incorporate prior procedure data, then the system is faster to implement, but opportunities for improving efficiency and patient outcomes are lost
Solution Approach 1:
Prior procedure data is analyzed in advance during the pre-operative planning phase, so that when the actual procedure begins, the system already has optimized procedure plans ready. This preliminary analysis prevents time loss during the procedure itself while still capturing the productivity benefits of learning from past experiences.
Solution Approach 2:
The system creates standardized templates and patterns from prior successful procedures that can be quickly copied and adapted to new cases. Instead of analyzing every detail of prior procedures each time, the system identifies reusable patterns and best practices that can be efficiently applied to generate optimized procedure plans.
Data Source
AI summary
A system may comprise a processor and a memory having computer readable instructions stored thereon. The computer readable instructions, when executed by the processor, may cause the system to generate a procedure plan for performing a procedure with a robot-assisted manipulator. The procedure plan may be based on a first plurality of procedure inputs. The system may also generate a performance metric from the implementation of the procedure, evaluate the implemented procedure based on the performance metric to generate procedure evaluation information, and store the procedure evaluation information. The system may also generate a second procedure plan based on the stored procedure evaluation information and a second plurality of procedure inputs.