Wheelchair Race Runtime Prediction Using Six Ability Dimensions
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Solution Overview
Problem
Existing systems for predicting the run time of wheelchair athletes do not adequately consider factors beyond the applied position of driving force, such as physical abilities, limiting the accuracy of training suggestions.
Innovation Solution
A prediction device and method that utilizes a storage device to associate past measurements of physical abilities with run times, using a processor to calculate predicted run times based on expected values of speed, endurance, rhythm, recognition, and power abilities, employing sensors to gather data and regression analysis to develop a prediction model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If only the applied position of driving force is used for prediction, then the prediction system is simple, but the prediction accuracy is insufficient because it ignores other physical ability factors
Solution Approach 1:
The patent segments the physical ability assessment into six distinct ability dimensions (speed ability, movable angle ability, endurance ability, rhythm ability, recognition ability, and power ability). Each ability is measured separately using specific sensors and evaluation methods, allowing the system to handle complex predictions by breaking down the athlete's physical capabilities into manageable components that can be individually assessed and combined for overall performance prediction.
Solution Approach 2:
The patent transitions from a one-dimensional prediction approach (using only driving force applied position) to a six-dimensional prediction model by incorporating multiple physical ability dimensions. This dimensional expansion allows the system to capture the complexity of athletic performance by measuring and integrating six different aspects of physical ability, thereby significantly improving prediction accuracy while managing complexity through structured organization of the dimensions.
2Measurement precision
If multiple physical ability items are measured and considered, then the run time prediction becomes accurate, but the data collection and processing becomes complex
Solution Approach 1:
The patent employs a multi-functional sensor system that can measure multiple physical abilities simultaneously during wheelchair racing. The same sensor infrastructure (force sensors, angle sensors, timing devices) used to measure driving force applied position also serves to measure speed ability, endurance ability, rhythm ability, recognition ability, and power ability. This universal approach allows the system to collect comprehensive data without requiring separate specialized measurement systems for each ability dimension.
Solution Approach 2:
The patent implements continuous measurement and real-time data collection throughout the wheelchair racing process. Sensors continuously monitor driving force, wheel rotation angles, and race time, maintaining uninterrupted data streams that capture the athlete's performance across all six ability dimensions. This continuous action ensures that comprehensive data is gathered without requiring multiple separate measurement sessions, thereby reducing overall data collection complexity while maintaining high prediction accuracy.
3Measurement precision
If past measured values of physical abilities are stored and associated with run times, then a prediction model can be developed, but the storage and processing requirements increase
Solution Approach 1:
The patent applies local quality by storing and processing data selectively for each of the six physical ability dimensions rather than treating all data uniformly. The system maintains separate data structures and processing pathways for speed ability, movable angle ability, endurance ability, rhythm ability, recognition ability, and power ability. This localized approach allows the system to manage and process data volume efficiently by organizing information according to its specific characteristics and predictive importance, thereby reducing overall data processing complexity while maintaining comprehensive prediction capability.
Data Source
AI summary
A prediction device for predicting a run time of a target person who competes in a race by driving a wheelchair, the prediction device includes: a storage device configured to store a measured value of at least one item regarding a physical ability of an athlete who competes in the race and the run time of the athlete that were acquired in the past such that the measured value of the at least one item and the run time are associated with each other; and a processor configured to acquire an expected value corresponding to the at least one item, to calculate a predicted value of the run time corresponding to the expected value, and to output the predicted value.