Running Method Determination Device Using Three-Axis Acceleration
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Solution Overview
Problem
Conventional training systems provide insufficient feedback for improving running ability, as they do not tailor training methods to individual user characteristics.
Innovation Solution
A running method determination device that acquires motion data during running and determines an appropriate running method based on this data, using a smartphone or similar device with a measurement recording device to analyze acceleration in three axial directions and classify running styles into specific types such as heel strike, midfoot, or forefoot methods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional training systems provide feedback based on general training standards, then users can receive basic training information, but the feedback is insufficient for efficient training that matches individual user characteristics
Solution Approach 1:
The system continuously acquires motion data during running and provides feedback by determining and communicating the user's running method. This feedback loop enables the system to adapt training recommendations to individual running characteristics, resolving the contradiction between providing basic feedback and delivering customized training information.
Solution Approach 2:
The system changes the parameters of training feedback by analyzing specific motion parameters (acceleration in three axial directions) to determine running methods. This allows the system to transform general feedback into customized training information based on individual running characteristics, improving both adaptability and information quality.
2Adaptability or versatility
If the system analyzes motion data in three axial directions to determine running methods, then training customization is improved, but device complexity increases
Solution Approach 1:
The system segments the motion data analysis into three independent axial directions (X, Y, Z), processing each dimension separately to determine running methods. This segmentation allows complex three-dimensional motion analysis to be broken down into manageable components, reducing overall processing complexity while maintaining classification accuracy.
Solution Approach 2:
The motion monitoring device performs multiple functions: it monitors speed, pace, distance, and now also determines running methods through three-axis acceleration analysis. This multi-functionality consolidates what would otherwise require separate systems into a single device, reducing overall system complexity while improving adaptability.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables efficient training by providing personalized running methods, allowing users to comprehend and correct their running techniques, thereby improving their running ability objectively and effectively.
Implementation Method 1
a measurement recording device that measures and records accelerations in three axial directions when the user runs
Data Source
AI summary
A running method determination device includes at least one processor that executes a program stored in at least one memory. The at least one processor acquires motion data at a time of running of a user, calculates, based on acceleration data in multiple axial directions included in the acquired motion data, a sum of acceleration vectors in the multiple axial directions as a resultant vector, and determines a type of a running method of the user using at least an angle of the calculated resultant vector as a standard of determination.