Dual-Earbud Motion Sensing for Accurate Running Dynamics
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Solution Overview
Problem
Existing devices struggle to accurately measure and analyze running dynamics using single-sided sensors, which are prone to noise and drift, and fail to provide comprehensive insights into stride length, gait symmetry, and other essential metrics for performance enhancement and injury prevention.
Innovation Solution
Utilizing dual-sided sensors, such as accelerometer and microphone sensors in headphones or earbuds, to analyze motion characteristics and apply machine learning models for precise running dynamics estimation, providing real-time feedback and recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If single-sided sensors are used in headphones, then device complexity is reduced, but measurement precision deteriorates due to noise and drift
Solution Approach 1:
The system divides the sensing function into two separate sensors positioned on opposite sides of the user's head (left and right headphones). Each sensor captures motion data from its respective side, and the system processes these segmented measurements independently before combining them to achieve comprehensive running dynamics analysis with improved precision.
2Measurement precision
If dual-sided sensors are deployed in headphones, then measurement precision improves through comprehensive motion analysis, but device complexity increases
Solution Approach 1:
The headphone device integrates multiple functions into a single wearable unit: audio playback, voice capture, and running dynamics measurement. The same headphone structure houses both audio components and motion sensors (accelerometers, gyroscopes), allowing the device to serve multiple purposes without requiring separate specialized equipment.
Solution Approach 2:
The system combines data from multiple sensor types (accelerometers, gyroscopes, microphones) positioned on both sides of the head into a unified processing framework. By merging these diverse sensor inputs and integrating them with audio functionality, the system achieves comprehensive motion analysis while maintaining a single cohesive device architecture.
3Ease of operation
If sensors are placed in headphones, then ease of operation improves for runners, but reliability deteriorates due to sensor noise and drift
Solution Approach 1:
The system continuously monitors sensor data from both headphones and compares measurements in real-time. By establishing feedback loops that cross-validate data from opposite sides of the head, the system can detect and correct anomalies, noise, or drift in individual sensors, thereby maintaining reliable measurements throughout the running activity.
Solution Approach 2:
The dual-sided sensor configuration enables self-validation of measurements. Each side's sensor data serves as a reference for the other, allowing the system to automatically identify and compensate for measurement errors without external intervention. The symmetric placement creates inherent redundancy that supports self-correcting measurement reliability.
Data Source
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AI summary
Aspects of the subject technology obtain sensor data from microphone and or movement sensors disposed in a device on each side of a user's body. The sensor data is used to provide running dynamics estimations including estimations involving differences between movement characteristics of the user's right side of the body versus the user's left side of the body. The estimations can further be used to provide feedback to the user regarding running style, running routes, and injury information.