Activity-Dependent Audio Feedback for Gesture Inputs
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Solution Overview
Problem
Touch-based ambient devices face challenges in accurately recognizing user gestures due to variability, leading to reduced recognition rates and user frustration, and often fail to leverage activity-dependent data for input, limiting the available inputs and corpus of actions.
Innovation Solution
A computing system that includes input sensors, activity sensors, and control circuits to determine user activity states and gesture validity, providing audio feedback based on these determinations to enhance user interaction and training through line-specific audio feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If touch-based ambient devices use gestures as input mechanism, then user interaction capability is improved, but gesture recognition accuracy deteriorates due to variability in user motions
Solution Approach 1:
The patent applies feedback by providing real-time audio feedback to users during gesture recognition. The system analyzes gesture data and provides immediate auditory confirmation or correction, allowing users to adjust their motions. This feedback loop improves recognition accuracy by guiding users to perform gestures within acceptable parameter ranges while maintaining the versatility of touch-based interaction.
Solution Approach 2:
The patent utilizes parameter changes by dynamically adjusting recognition thresholds and acceptable gesture parameters based on activity state. The system modifies the parameters for gesture validation depending on the detected activity level, allowing more flexible interpretation of gestures during high-activity states and more precise interpretation during low-activity states. This resolves the contradiction by adapting measurement precision to the operational context.
2Device complexity
If devices fail to leverage activity dependent data for inputs, then device complexity is reduced, but the corpus of available inputs is limited
Solution Approach 1:
The patent applies dynamics by making the action set dynamically changeable based on detected activity state. The system transitions between different action sets corresponding to different activity levels (e.g., low activity, moderate activity, high activity). This dynamic adaptation expands the corpus of available inputs without requiring complex static processing, as the system adapts its input interpretation in real-time based on simple activity detection.
Solution Approach 2:
The patent implements universality by using a single activity sensor system to serve multiple functions: detecting activity state, determining appropriate action sets, and validating gestures contextually. This multi-functional approach expands input capabilities without proportionally increasing device complexity, as the same hardware infrastructure supports diverse input interpretation strategies across different activity contexts.
3Ease of operation
If visual or haptic feedback is provided for gesture recognition, then user guidance is improved, but user frustration increases due to confusion about acceptable versus unacceptable gestures
Solution Approach 1:
The patent substitutes mechanical feedback systems (visual and haptic) with an acoustic feedback system. Audio feedback provides clear, unambiguous auditory signals that indicate whether a gesture was recognized or needs adjustment. This substitution resolves the confusion inherent in visual/haptic feedback by using distinct audio patterns that clearly communicate recognition status, reducing user frustration while maintaining ease of operation.
Data Source
AI summary
Systems and methods that provide audio feedback in response to gesture validity can provide a more intuitive interface that can train users to correctly complete gestures. Moreover, systems and methods that provide line-specific audio feedback can provide more specific feedback that can allow a user to better understand what sensing line is being contacted. The systems and methods can further include basing the audio feedback based at least in part on obtained activity data, such that invalid and valid feedbacks can provide different sounds dependent on the determined activity state.