Wearable Sensor for Real-Time Hand Movement Feedback
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current training systems for sports, particularly golf, lack devices that can accurately track hand position and movement discreetly while providing real-time feedback, leading to slow progress and reliance on bulky aids or costly coaching methods.
Innovation Solution
A wearable device equipped with sensors and AI/ML algorithms that track hand movements and provide immediate feedback through lighting or haptic cues, embedded in sporting apparel, allowing for discreet and effective training during actual play.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional training aids are used to provide feedback and correction, then learning effectiveness is improved, but the devices become big and bulky, obstructing natural ability and not allowing use during competitive play
Solution Approach 1:
The patent replaces bulky mechanical training aids with a lightweight wearable device containing sensors, processors, and feedback mechanisms that can be discreetly attached to the hand. This substitution enables real-time data collection and feedback without the physical obstruction of traditional training tools.
Solution Approach 2:
The wearable device integrates multiple functions including hand position tracking, movement analysis, real-time feedback delivery, and performance monitoring in a single compact unit. This multi-functionality eliminates the need for multiple separate training devices while maintaining comprehensive learning support.
2Measurement precision
If launch monitors and shot trackers are used to provide detailed information on ball flight, then measurement precision is improved, but the ability to provide real-time feedback and corrective action is lost
Solution Approach 1:
The system implements real-time feedback by continuously monitoring hand position and movement data, analyzing performance metrics, and immediately delivering corrective guidance to the athlete during practice sessions. This closed-loop feedback system eliminates the time delay between performance measurement and corrective action.
Solution Approach 2:
The device provides real-time guidance and corrective actions during performance execution, allowing athletes to make immediate adjustments rather than waiting for post-session analysis. This preliminary correction capability enables learning to occur during the actual practice activity.
3Reliability
If in-person coaching and simulators are used to provide detailed instruction, then learning quality is improved, but the time required to see progress increases to months or years
Solution Approach 1:
The wearable device enables continuous learning and feedback during every practice session and competitive play, eliminating gaps between training moments. This continuous engagement with real-time data and feedback accelerates skill acquisition compared to periodic coaching sessions spaced months apart.
Solution Approach 2:
The system empowers athletes to self-diagnose and self-correct performance issues in real-time through immediate feedback on hand position and movement metrics. This self-service capability reduces dependency on frequent personal coaching while maintaining high learning quality.
4Adaptability or versatility
If traditional coaching methods are used to provide personalized instruction, then adaptability to individual characteristics is improved, but the cost and time investment increase significantly
Solution Approach 1:
The system adapts to individual athlete characteristics by collecting and analyzing personal performance data, then adjusting feedback and guidance parameters accordingly. This data-driven personalization provides customized learning experiences without requiring extensive manual assessment and adjustment by coaches.
Data Source
AI summary
A data processing system and method for collecting data and providing feedback to a user on the proper movement associated with a task. The data processing system can include a sensor device worn by a user while performing the task. The sensor device includes a number of sensors and feedback devices for collecting user movement data while performing the task, analyzing the data and providing feedback based on the collected data. The data processing system can include a mobile device and application that receives collected data from the sensor device and can provide further analysis and insight to the user based on the collected data. Data processing method includes algorithms for processing collected data and providing feedback on the collected data.


