Surgical Video Segment Identification via User Activity Analysis
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Solution Overview
Problem
The challenge lies in efficiently consuming and managing large volumes of surgical videos, as they are typically long and contain repetitive, uninteresting segments, making it impractical for surgeons to watch entire videos for training and analysis.
Innovation Solution
A video analysis and management system that identifies useful segments by monitoring user activities, such as playback operations, to determine popularity scores and generate metadata for efficient video consumption, allowing for the creation of adapted videos that focus on relevant content based on user preferences and time constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If surgeons watch entire surgical videos for training and analysis, then comprehensive understanding of surgical procedures is improved, but time consumption and network resource usage increase significantly
Solution Approach 1:
The system extracts and identifies useful segments from complete surgical videos based on user activities and popularity scores. Instead of requiring surgeons to watch entire hour-long videos, the system extracts only the relevant portions (e.g., critical surgical steps, unusual events) that provide comprehensive understanding while minimizing time consumption.
Solution Approach 2:
The patent divides surgical videos into multiple segments and analyzes user activities within each segment. By segmenting the video and evaluating popularity scores for each segment, the system can identify and present only the valuable portions to surgeons, maintaining comprehensive understanding while reducing overall viewing time.
2Loss of information
If surgeons watch entire surgical videos for training and analysis, then complete procedural knowledge is improved, but network resource consumption increases
Solution Approach 1:
The system extracts only the essential procedural knowledge from complete surgical videos by identifying useful segments based on user activities. This extraction approach transmits minimal network resources while preserving complete procedural knowledge through targeted segment selection.
3Loss of information
If repetitive surgical operations are included in training videos, then completeness of training content is improved, but engagement and interest of surgeons decrease
Solution Approach 1:
The system removes repetitive and less engaging segments from surgical videos while retaining critical training content. By analyzing user activities (such as pausing, rewinding, fast-forwarding), the system identifies and extracts only the engaging and educationally valuable portions, maintaining training completeness while improving surgeon engagement.
Data Source
AI summary
One example method for identifying useful segments in surgical videos includes accessing a video of a surgical procedure and user activities of a plurality of users who have watched the video of the surgical procedure. The user activities include operations performed during playback of the video. The method further includes dividing the video into multiple segments and determining a popularity score for each of the multiple segments based on the operations. Useful segments are identified from the segments based on the popularity scores. The method further includes generating metadata for the video of the surgical procedure to include an indication of the identified useful segments and associating the metadata with the video of the surgical procedure.