Endoscope Field of View Control via History Data
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Solution Overview
Problem
Existing endoscope systems require significant labor from surgeons to adjust control parameters for maintaining an appropriate field of view during surgeries, which can be time-consuming and inefficient.
Innovation Solution
An endoscope system that stores history data on control parameters during surgeries, along with subsidiary information such as surgeon, operative method, and patient details, to calculate recommended values for control parameters, thereby reducing the need for manual adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual adjustment of control parameters is used to maintain field of view, then the field of view can be controlled, but significant labor and time are required from surgeons
Solution Approach 1:
The system automatically calculates recommended control parameter values using history data and machine learning models, enabling the endoscope system to self-adjust without requiring manual intervention from the surgeon. This resolves the contradiction by eliminating manual adjustment operations while maintaining field of view control.
Solution Approach 2:
The system collects history data on control parameter adjustments and uses this feedback to train machine learning models that predict optimal parameter values. This closed-loop feedback mechanism allows the system to learn from past adjustments and automatically provide recommended values, reducing both manual labor and time consumption.
2Ease of operation
If automatic calculation of control parameters is implemented, then labor required is reduced, but system complexity increases due to history data storage and processing requirements
Solution Approach 1:
The system pre-stores history data on control parameter adjustments in a database during and after surgeries. This preliminary accumulation of data enables the machine learning model to be trained offline, so that during actual surgery the system only needs to query pre-processed information, reducing real-time computational complexity while maintaining automatic calculation capabilities.
Data Source
AI summary
An endoscope system for controlling a field of view of an endoscope on a basis of a control parameter, the endoscope system including: a storage configured to store history data on the control parameter during a surgery in association with subsidiary information on the surgery, the subsidiary information including information related to at least one of a surgeon, an operative method, or a patient of the surgery; and one or more processors including hardware, wherein the one or more processors are configured to calculate a recommended value of the control parameter on a basis of the history data, and wherein the history data is an operation log of a user interface for changing the control parameter.