Haptic Interface for Non-Intentional User Feedback Evaluation
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Solution Overview
Problem
Current systems lack effective methods to evaluate the quality of automatically composed digital content, particularly in virtual reality environments, where user feedback is crucial but often subjective and difficult to quantify.
Innovation Solution
The system utilizes a haptic interface to collect both intentional and non-intentional user feedback, processing this data to generate evaluation reports that assess the quality of digital content, allowing for the adjustment of composition rules to improve content generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If user feedback is collected through traditional methods (surveys, ratings), then subjectivity and difficulty in quantification increase, but implementation complexity remains low
Solution Approach 1:
The patent replaces traditional mechanical survey methods with a haptic interface system that captures physiological responses. The haptic device measures objective physical data (grip force, vibration sensitivity, touch patterns) instead of relying on subjective user ratings, thereby improving measurement precision while managing system complexity through automated data processing
Solution Approach 2:
The haptic interface acts as an intermediary between the user and the content evaluation system. It translates complex physiological responses into quantifiable metrics through haptic feedback markers embedded in the content, enabling precise quality measurement without requiring direct user input or complex survey mechanisms
2Measurement precision
If haptic interface is implemented to collect objective feedback, then measurement precision improves, but device complexity increases
Solution Approach 1:
The haptic interface system performs self-calibration and automatic data processing. The system autonomously captures haptic data, processes it through algorithms, and generates quality metrics without requiring manual configuration or complex external equipment, thereby reducing operational complexity while maintaining high measurement precision
Solution Approach 2:
The haptic interface is designed to serve multiple functions: delivering haptic feedback for content interaction, capturing user physiological responses, and enabling quality evaluation. This multi-functionality consolidates what would otherwise require separate systems into a single device, managing complexity while improving measurement capabilities
3Productivity
If automated content generation is used, then productivity increases, but content quality evaluation becomes more difficult
Solution Approach 1:
The system implements a closed-loop feedback mechanism where haptic data from user interactions with automatically generated content feeds back into the content generation process. This feedback loop enables continuous quality assessment and refinement, making it easier to evaluate and improve content quality while maintaining high productivity through automation
Solution Approach 2:
The system pre-embeds haptic feedback markers into automatically generated content before user interaction. This preliminary action enables automated tracking of user responses and quality metrics from the outset, simplifying the evaluation process for high-volume content generation while maintaining measurement capability
Data Source
AI summary
Systems and methods are provided for evaluating the quality of automatically composed digital content based on non-intentional user feedback obtained through a haptic interface. For example, a method includes accessing non-intentional user feedback collected by a haptic interface executing on a computing device, wherein the non-intentional user feedback comprises information regarding user interaction with elements of digital content rendered by the computing device. The digital content is content that is automatically generated using content generation rules. The method further includes evaluating a quality of the digital content based on the non-intentional user feedback, and generating an evaluation report that includes information regarding the quality of the digital content.