Adaptable Ultrasound Interface Using Usage Data
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Solution Overview
Problem
Current medical imaging systems lack the ability to customize and adapt their user interfaces based on individual user preferences and usage patterns, leading to inefficiencies and increased exam time.
Innovation Solution
A medical imaging system that dynamically modifies its user interface by analyzing usage data, such as keystroke patterns and control sequencing, to customize button layouts, visibility, and functionality using machine learning and AI models, allowing for personalized and efficient operation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a fixed user interface is used in medical imaging systems, then the system structure remains simple and stable, but user efficiency decreases and exam time increases
Solution Approach 1:
The user interface dynamically adjusts button visibility, layout, and functionality based on real-time analysis of user behavior patterns. The system monitors which controls are frequently used and automatically reconfigures the interface to prioritize those controls, transforming the static interface into an adaptive one that evolves with user preferences.
Solution Approach 2:
The system automatically analyzes user interaction data and performs interface customization without requiring manual user configuration. The processor monitors control usage patterns and autonomously adjusts the interface layout, freeing users from the burden of manual customization while improving their workflow efficiency.
2Ease of operation
If manual customization of user interface is allowed, then user preferences can be accommodated, but the complexity of operation increases and time is consumed
Solution Approach 1:
The system performs self-customization by automatically monitoring user interactions and adjusting the interface accordingly. Instead of requiring users to manually configure each control, the system observes usage patterns and autonomously optimizes the interface layout, eliminating the time users would otherwise spend on customization.
Solution Approach 2:
The system proactively analyzes user behavior patterns and pre-adjusts the interface before users need to access specific functions. By continuously monitoring control usage and anticipating user needs, the system prepares the optimal interface configuration in advance, reducing wait time and improving operational flow.
3Ease of operation
If all controls are displayed on the user interface, then complete functionality is available, but visual clutter increases and ease of operation decreases
Solution Approach 1:
The system extracts and highlights only the most relevant controls based on user behavior analysis. By identifying which controls are frequently used and removing or dimming less-used controls from the active view, the interface reduces visual clutter while ensuring that essential controls remain prominently accessible.
Solution Approach 2:
Different regions of the interface are assigned different levels of visibility and importance based on user interaction patterns. Frequently used controls are positioned in prominent locations with enhanced visibility, while less-used controls are moved to secondary positions or made less prominent, creating a differentiated interface that optimizes accessibility for each control type.
Data Source
AI summary
An ultrasound imaging system may include a user interface that may be adapted based, at least in part, on usage data of one or more users. The functions of soft or hard controls may be changed in some examples. The layout or appearance of soft or hard controls may be altered in some examples. In some examples, seldom used controls may be removed from the user interface. In some examples, the user interface may be adapted based on an anatomical feature being imaged. In some examples, the usage data may be analyzed by an artificial intelligence/machine learning model, which may provide outputs that may be used to adapt the user interface.