Robotic Procedure Metrics Using Theater Sensor Workflow Analytics

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Solution Overview

Problem

Existing systems struggle to efficiently process and analyze disparate forms of surgical theater data acquired during nonoperative periods to facilitate reviewer analysis and feedback generation based on team member inefficiencies.

Innovation Solution

A system and method for processing theater-wide sensor data during nonoperative periods to facilitate automated analysis and feedback generation, including object detection, segmentation, and workflow analytics, to improve surgical team efficiency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual review and analysis of surgical theater data is used, then reviewer analysis can be performed, but it is inefficient and time-consuming to process disparate forms of data

Engineering Contradiction:

Improvedata processing efficiencyVSAvoidtime for reviewer analysis

Core Design Contradiction:

ProductivityVSLoss of time

Solution Approach 1:

The system enables automated self-service processing of surgical theater data through machine learning models that automatically detect objects, segment scenes, and generate workflow analytics without requiring manual reviewer intervention for each data point, thereby dramatically improving processing efficiency

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces manual mechanical review processes with automated computational systems including object detection algorithms, image segmentation models, and natural language processing systems that can process disparate data forms simultaneously and generate insights much faster than human reviewers

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Measurement precision

If comprehensive theater-wide sensor data is collected during nonoperative periods, then granular assessment of team performance is enabled, but data processing complexity increases

Engineering Contradiction:

Improveteam performance assessment granularityVSAvoiddata processing system complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The system segments the complex theater-wide data into distinct components including object detection results, scene segmentation layers, and workflow activity classifications, allowing each component to be processed independently by specialized algorithms before being integrated into comprehensive performance metrics

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces intermediary processing layers including trained machine learning models and data normalization systems that act as mediators between raw sensor data and final performance metrics, simplifying the complexity by transforming disparate data forms into standardized intermediate representations

Inventive Principle:

Principle #24Intermediary (Mediator)

3Productivity

If automated analysis systems are implemented, then feedback generation is accelerated, but system complexity and implementation difficulty increase

Engineering Contradiction:

Improvefeedback generation speedVSAvoidautomated system complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The system implements universal multi-functional processing pipelines where the same core machine learning infrastructure handles multiple tasks including object detection, image segmentation, text analysis, and metric generation, reducing overall system complexity compared to having separate specialized systems for each function

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent incorporates feedback mechanisms where system outputs are automatically evaluated and used to refine processing parameters, enabling the system to adapt and improve performance over time without increasing structural complexity, as the feedback loops utilize existing processing components

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS20260024644A1Prediction of metrics of medical procedures and medical environments using robotic system data

Publication Date: 2026.01.22 INTUITIVE SURGICAL OPERATIONS INC

AI summary

The arrangements disclosed herein relate to determining, via at least one machine learning model, a metric value using first robotic system data. The first robotic system data is generated by a first robotic system used to perform a first medical procedure in a first medical environment. The at least one machine learning model is based at least in part on second robotic system data and efficiency-related data comprising one or more second metric values for second medical procedures in second medical environments. The second robotic system data is generated by second robotic systems used to perform the second medical procedures in the second medical environments. The one or more second metric values is determined based at least in part on the second robotic system data and medical environment data generated by sensors deployed within the plurality of second medical environments. The metric value is provided for display on a User Interface (UI).