Multi-Channel Encoder for Synchronizing Medical Data Streams
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Solution Overview
Problem
Existing systems for data collection in operating rooms lack comprehensive data coverage, synchronization of audio/video feeds with digital data streams, and rigorous data analysis, leading to inadequate identification of adverse events and failure to validate quality improvement benefits.
Innovation Solution
A system that collects and processes real-time medical or surgical data streams using a multi-channel encoder with a network server for synchronization, generating a session container file, and employing a perception engine for pattern extraction and predictive modeling with machine learning techniques to analyze technical and non-technical aspects of surgical procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If comprehensive data collection from multiple sources is implemented, then data coverage and analysis capability are improved, but device complexity and synchronization difficulty increase
Solution Approach 1:
The system segments data collection into multiple independent channels (video feeds, audio feeds, digital data streams) that can be collected, synchronized, and processed separately. Each channel operates independently but contributes to the comprehensive data set, allowing complex multi-source data collection without overwhelming system complexity.
Solution Approach 2:
The encoder acts as an intermediary device that receives data from multiple sources, synchronizes them to a common timeline, and outputs a unified session container file. This intermediary approach manages the complexity of coordinating multiple data streams by centralizing synchronization logic in a single component.
2Loss of information
If multiple video-audio feeds are recorded simultaneously, then comprehensive event documentation is improved, but synchronization accuracy deteriorates
Solution Approach 1:
The system uses periodic timestamp markers embedded in each data stream at regular intervals to maintain synchronization. This periodic timing reference allows the encoder to accurately align video, audio, and digital data streams even when recorded simultaneously from multiple independent sources.
Solution Approach 2:
The system replaces mechanical synchronization methods with digital timestamp-based synchronization. Instead of relying on physical connection or mechanical coupling between devices, each feed is independently timestamped and then synchronized through digital processing, achieving both comprehensive coverage and high precision.
3Measurement precision
If rigorous data analysis methods are applied, then adverse event identification is improved, but data processing time and computational resources increase
Solution Approach 1:
The system performs preliminary organization of data during the recording phase by synchronizing all feeds to a common timeline and creating a structured session container file. This preliminary organization eliminates the need for complex post-processing alignment operations, reducing analysis time while maintaining high identification accuracy.
Solution Approach 2:
The encoder automatically timestamps and organizes data streams without requiring manual intervention or complex external processing. This self-service approach to data organization enables rigorous analysis methods to be applied efficiently, as the data is already prepared in an analysis-ready format.
Data Source
AI summary
A multi-channel recorder/encoder for collecting, integrating, synchronizing and recording medical or surgical data received as independent live or real-time data streams from one or more hardware units. The medical or surgical data relating to a live or real-time medical procedure. Example hardware units include a control interface, cameras, sensors, audio devices, and patient monitoring hardware. Further example systems may include a cloud based platform incorporating the encoder.