Touch Interaction Parameter Tuning for Adaptive HMI Control
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Solution Overview
Problem
Existing Human-Machine Interaction (HMI) devices struggle to accurately recreate end-user experiences, leading to increased risk in complex tasks due to heuristic-based techniques that lack realistic estimation and precision.
Innovation Solution
An electronic device controls rendering of user interfaces for inputting and modifying parameters based on user feedback, enabling accurate configuration of HMI devices through a two-step co-design process that incorporates qualitative and quantitative measures for enhanced user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If heuristic-based techniques are used to recreate end-user experience, then the HMI device can operate with simplified control, but the accuracy and precision of the interaction control deteriorates
Solution Approach 1:
The system implements a feedback mechanism where user interactions are captured and used to adjust control parameters. The electronic device receives user inputs, processes them through machine learning models, and refines the interaction control based on feedback loops, thereby improving accuracy while maintaining ease of operation.
Solution Approach 2:
The system dynamically changes control parameters based on user behavior patterns. By analyzing user interactions and adjusting parameters such as force, speed, and position in real-time, the system achieves both simplified control and high precision without requiring complex manual configuration.
2Productivity
If interview-driven processes with minimal exposure to actual interaction experience are used, then the development process is faster, but the reliability of end-user experience estimation deteriorates
Solution Approach 1:
The system creates digital twins or virtual models of user interactions that replicate actual interaction experiences. These copies allow developers to test and validate interactions in a virtual environment, maintaining development speed while improving the reliability of experience estimation through realistic simulation data.
Solution Approach 2:
The system performs preliminary analysis of user interactions by capturing and processing interaction data before final system deployment. This preliminary action allows the system to pre-adjust control parameters and validate interaction scenarios, ensuring reliable experience estimation without slowing down the overall development process.
3Device complexity
If pre-recorded videos are used as discussion prompts, then the analysis process is simplified, but the accuracy of interaction experience estimation deteriorates
Solution Approach 1:
The system replaces traditional video-based analysis with automated sensor data collection and machine learning-based interaction modeling. This substitution eliminates the need for manual video review while providing more accurate, quantifiable interaction metrics, thereby maintaining simplicity while improving precision.
Solution Approach 2:
The system automatically captures, processes, and analyzes interaction data without requiring manual intervention for video review. The automated processing pipeline extracts interaction patterns and generates insights independently, reducing analysis complexity while improving accuracy through consistent, objective data measurement.
4Device complexity
If the HMI device operates with fixed parameters, then the control system is simpler, but the adaptability to different user interactions deteriorates
Solution Approach 1:
The system transitions from fixed parameters to dynamic parameters that adapt in real-time based on user interactions. The electronic device continuously monitors interaction patterns and adjusts control parameters dynamically, enabling the system to maintain simplicity while achieving high adaptability through automated parameter optimization.
Solution Approach 2:
The system performs preliminary learning of user interaction patterns during initial use phases and stores optimized parameter configurations. This preliminary action allows the system to quickly adapt to different users without requiring complex real-time computation, maintaining control system simplicity while achieving versatility across different interaction scenarios.
Data Source
AI summary
An electronic device and a method for human-machine interaction (HMI) device touch-interaction control based on user-defined parameters. The electronic device controls rendering of a first electronic user interface (UI) including first UI elements for input of parameters for touch-interaction of HMI device with a user. The electronic device receives a first user input indicative of parameters through the first electronic UI and controls the HMI device to operate based on first user input. The electronic device controls rendering of a second electronic UI including second UI elements for input of a user-feedback associated with the touch-interaction of the HMI device. The electronic device receives a second user input indicative of a user-feedback through the second electronic UI. The electronic device modifies parameters based on second user input and controls the HMI device to operate based on the modified parameters.