Multi-Stream Haptic Signal Modulation for Synchronized Feedback
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Solution Overview
Problem
Existing methods for generating haptic effects in electronic devices lack the capability to enhance user experience through improved haptic feedback.
Innovation Solution
A method and system that processes multiple media streams from different terminals, decodes and associates them with identifiers, generates initial haptic signals based on content analysis, and modulates these signals to output haptic control signals for actuators, utilizing a machine-learning module to customize haptic responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple media streams are processed concurrently to provide rich haptic feedback, then user experience is enhanced, but system complexity increases
Solution Approach 1:
The system segments the haptic signal generation process into distinct modules: initial haptic signal generation from each media stream, machine learning-based content analysis, and signal modulation. This segmentation allows independent processing of multiple media streams while managing system complexity through modular architecture.
Solution Approach 2:
The machine learning module serves as an intermediary that analyzes content from multiple media streams and generates modulation signals. This intermediary component coordinates the processing of multiple inputs, enabling concurrent media stream processing while maintaining system manageability through intelligent mediation.
2Measurement precision
If machine learning is used to analyze content and customize haptic signals, then haptic precision is improved, but processing time increases
Solution Approach 1:
The system performs preliminary machine learning-based content analysis on media streams before generating final haptic signals. By analyzing content characteristics in advance and pre-processing the media streams, the system prepares modulation signals that can be quickly applied, reducing latency in the overall haptic feedback process.
Solution Approach 2:
The patent replaces traditional rule-based haptic signal generation with machine learning-based content analysis. This substitution enables more precise understanding of media content characteristics, allowing the system to generate highly accurate haptic feedback while the machine learning model efficiently processes content features.
3Adaptability or versatility
If haptic signals are generated from multiple media streams, then haptic effect richness is improved, but signal synchronization becomes difficult
Solution Approach 1:
The system employs feedback mechanisms where the machine learning module continuously analyzes content from multiple media streams and adjusts modulation signals accordingly. This feedback loop ensures that haptic signals from different media streams remain synchronized by dynamically coordinating their generation based on real-time content analysis.
Solution Approach 2:
The machine learning module serves as a universal coordinator that handles content analysis for all media streams regardless of source or type. This multi-functional component provides a unified approach to signal synchronization, enabling the system to manage multiple media streams with consistent synchronization accuracy.
Data Source
AI summary
A method may include receiving a first media stream from a first terminal and a second media stream from a second terminal; decoding the first and second media streams to obtain a first and second contents in a playable format; associating the first media stream and the second media stream with a first identifier and a second identifier; generating a first initial haptic signal based on the first content and the first identifier and a second initial haptic signal based on the second content and the second identifier; processing the first/second content to generate a first/second analysis; modulating the first initial haptic signal according to the first analysis to output a first haptic control signal and the second initial haptic signal according to the second analysis to output a second haptic control signal; and driving an actuator according to the first and/or the second haptic control signal.