Robotic Surgery AI Training With Integrated Cybersecurity

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Solution Overview

Problem

Existing robotic surgical systems lack integrated data management, training capabilities for AI models, and cybersecurity measures, which are crucial for enhancing precision, safety, and efficiency in surgical procedures.

Innovation Solution

A robotic surgical system with a central or distributed data repository, a training module for unsupervised/transfer/federated learning, and a cybersecurity module for secure data transmission and access, including encryption, multi-factor authentication, and real-time threat detection.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If robotic surgical systems aggregate and store surgical data in a central or distributed data repository, then AI model training and system improvement are enhanced, but data security risks and cyber threats increase

Engineering Contradiction:

ImproveAI model training capabilityVSAvoidcybersecurity threats

Core Design Contradiction:

Adaptability or versatilityVSObject-affected harmful factors

Solution Approach 1:

A cybersecurity module is introduced as an intermediary between the data repository and external systems. This module implements encryption, multi-factor authentication, and real-time threat detection to protect surgical data while enabling AI training capabilities.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Reliability

If multiple security measures including encryption and multi-factor authentication are implemented, then data security is improved, but system complexity and implementation difficulty increase

Engineering Contradiction:

Improvedata securityVSAvoidsecurity system complexity

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

Multiple security measures (encryption, multi-factor authentication, real-time threat detection) are merged into a single integrated cybersecurity module. This consolidation provides comprehensive security while managing complexity through unified architecture.

Inventive Principle:

Principle #5Merging (Combining)

3Reliability

If real-time threat detection and cybersecurity measures are implemented, then system safety is improved, but processing time and computational resources increase

Engineering Contradiction:

Improvesystem safetyVSAvoidprocessing time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

Real-time threat detection operates continuously in the background without interrupting surgical procedures. The cybersecurity module monitors and responds to threats continuously, ensuring safety while minimizing impact on operational timing.

Inventive Principle:

Principle #20Continuity of useful action

Data Source

PatentUS20250359950A1Integrated ai-powered adaptive robotic surgery system

Publication Date: 2025.11.27 BRUBAKER WILLIAM

AI summary

A robotic surgical system network includes a plurality of robotic surgical systems. Each system includes robotic arms, sensors, a surgeon console, and a control system with an integrated AI module. A network interface is associated with robotic surgical system and provides secure data communication. A central or distributed data repository securely stores surgical data aggregated from the robotic surgical systems. The surgical data includes at least one of procedural data, sensor readings, imaging data, AI decision logs, surgical outcomes, or user interaction data. A training module utilizes aggregated surgical data to train or update AI models for the robotic surgical systems using unsupervised learning, transfer learning, or federated learning techniques. A cybersecurity module implements security measures for data transmission and system access, the measures comprising at least one of encryption, multi-factor authentication, or real-time threat detection.