Endoscopy Video Capture Device Automatic Recording Control
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Solution Overview
Problem
Medical video recording devices require significant user interaction to start and stop recording, limiting their usage in high-intensity healthcare environments where resources are scarce.
Innovation Solution
A system and method that automatically record video output signals from endoscopy devices by analyzing video image data to identify start and stop indicators, reducing the need for user interaction through a video capture device with a processor, local storage, and network access, ensuring secure and HIPAA-compliant storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If automatic recording is implemented, then user interaction is reduced and recording likelihood increases, but device complexity increases due to added processing requirements
Solution Approach 1:
The video capture device automatically performs recording decisions by analyzing video data itself, without requiring user intervention. The processor examines video frames, detects indicators of medical procedures, and autonomously determines when to start and stop recording, making the system self-sufficient and eliminating the need for manual operation.
Solution Approach 2:
The system continuously analyzes video data in real-time before recording is needed, preparing to capture footage proactively. By monitoring video streams and detecting procedure indicators ahead of time, the system is ready to record immediately when conditions are met, without waiting for user commands.
2Reliability
If continuous recording is performed, then no procedure is missed, but storage requirements and data management burden increase significantly
Solution Approach 1:
The system extracts only the essential recording segments from the continuous video stream by identifying and isolating portions containing medical procedures. Rather than storing all video data, the processor detects specific indicators and extracts only the relevant segments for storage, dramatically reducing data volume while maintaining recording completeness.
Solution Approach 2:
The system performs partial recording by capturing only the necessary portions of video data that contain medical procedures. Instead of recording continuously or excessively, the system applies selective recording based on detected indicators, achieving sufficient coverage of medical events while minimizing unnecessary data accumulation.
3Measurement precision
If manual recording control is used, then recording precision is high, but productivity decreases due to time consumption
Solution Approach 1:
The system uses real-time feedback from video analysis to automatically adjust recording decisions. The processor continuously monitors video data, compares it against known indicators of medical procedures, and immediately responds by starting or stopping recording based on detected conditions, achieving both precision and efficiency through automated feedback loops.
Solution Approach 2:
The system replaces manual mechanical control (user pressing buttons) with automated electronic processing. The processor electronically analyzes video data and automatically controls recording operations, substituting human action with machine intelligence to achieve both accurate timing and high productivity simultaneously.
Data Source
AI summary
A method and device for automatically recording a video output signal from an endoscopy device. Video image data is received at a video capture device, and transmitted with associated metadata to a server. Prior to transmission, the video capture device analyzes the video image data to identify a recording start indicator as a function of predetermined threshold conditions. Once the indicator is identified, the device sends recording start timestamp to a backend server. The server indexes and stores the recorded video data as a function of the associated metadata in a database, and also records the recording the recording start timestamp data in the database. The device is further able to identify a recording stop indicator, and prepare recording stop timestamp data for transmission to the server.