Audiovisual-Medical Data Synchronization Using Equipment Sound Classification

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Solution Overview

Problem

Existing methods for synchronizing medical data and audiovisual data during procedures rely on human speech, which distracts medical personnel and is inefficient.

Innovation Solution

A computer-implemented method using machine learning algorithms to classify sounds from audio data as equipment-related, enabling passive synchronization of audiovisual and medical data by matching sound patterns and display features, and generating a composite video.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If human speech is used for synchronization, then synchronization can be achieved, but medical personnel are distracted

Engineering Contradiction:

Improvesynchronization accuracyVSAvoiddistraction to medical personnel

Core Design Contradiction:

ReliabilityVSObject-affected harmful factors

Solution Approach 1:

The patent extracts the synchronization function from human speech and transfers it to automated sound classification of equipment noises. The machine learning system separates the synchronization task from human interaction, allowing personnel to focus on medical procedures while the system autonomously synchronizes audiovisual and medical data through equipment sound analysis

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent replaces the mechanical/human speech-based synchronization system with an automated acoustic analysis system. Instead of relying on human vocal commands, the system uses machine learning algorithms to classify and interpret equipment sounds, substituting human speech recognition with automated sound pattern recognition

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Reliability

If traditional synchronization methods are used, then data can be synchronized, but the process is inefficient

Engineering Contradiction:

Improvesynchronization accuracyVSAvoidsynchronization efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The patent implements preliminary action by pre-training machine learning models with equipment sound data before actual medical procedures. The system prepares classification models in advance that can immediately recognize and synchronize equipment sounds during procedures, eliminating the need for real-time manual configuration and improving synchronization efficiency

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system performs self-service synchronization by autonomously classifying equipment sounds and aligning audiovisual and medical data without requiring manual intervention. The machine learning model automatically identifies synchronization points and adjusts timing, allowing the system to synchronize data independently and efficiently

Inventive Principle:

Principle #25Self-service

Data Source

PatentUS20250316295A1Synchronizing audiovisual data and medical data

Publication Date: 2025.10.09 KONINKLIJKE PHILIPS NV

AI summary

The present invention relates to a computer-implemented method of synchronizing audiovisual data and medical data, the method comprising: receiving the audio-visual data (40) recorded by a first device (20), the audio-visual data including an audio channel and a video channel simultaneously capturing a medical procedure performed in a medical environment, receiving the medical data (30) recorded by a second device, the medical data capturing physiological parameters of a patient during the medical procedure; classifying, using one or more machine learning algorithms, one or more sounds from the audio channel of the audio-visual data as being produced by equipment in the medical environment; and synchronizing the audio-visual data with the medical data based on a time of occurrence of the one or more sounds.