Fitness Training System Energy Expenditure Calculation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Individuals face challenges in maintaining motivation for regular exercise, particularly with repetitive motions, and existing systems often fail to engage users by separating athletic activities from daily life, leading to decreased interest and participation.
Innovation Solution
A system and method that processes data from users performing athletic activities to estimate energy expenditure, such as calories burned, while monitoring form and type of exercise, using sensors and image-capturing devices to provide personalized feedback and motivation through virtual avatars and displays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensor inputs and image-capturing devices are used to calculate energy expenditure, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The system divides the complex measurement task into multiple independent sensor components (accelerometer, gyroscope, magnetometer, image-capturing devices) that each capture specific aspects of user activity. These segmented sensor inputs are then integrated through machine learning models to achieve precise energy expenditure calculation without requiring a single complex sensor system.
Solution Approach 2:
The system employs multiple sensors that serve universal purposes - the same sensor array can track various types of athletic activities (running, cycling, swimming) and perform multiple functions including motion detection, position tracking, and energy expenditure calculation. This multi-functionality reduces the need for specialized equipment for each activity type.
2Adaptability or versatility
If personalized feedback and motivation features are implemented, then user engagement is improved, but device complexity increases
Solution Approach 1:
The system continuously monitors user activity through multiple sensors and provides real-time feedback through virtual avatars and personalized messages. The feedback loop includes tracking form quality, comparing performance to goals, and delivering motivational content adapted to individual user responses. This creates an engaging experience where the system adapts to each user's needs and performance level.
Solution Approach 2:
The system dynamically adjusts feedback content, virtual avatar behavior, and motivational messages based on real-time sensor data and user performance. The virtual trainer modifies its instructions and encouragement according to the user's form quality, effort level, and progress toward goals, creating a personalized and adaptive interaction that enhances engagement without requiring manual configuration.
Data Source
Figure 1A
Figure 1B
Figure 2A~2B
AI summary
Systems and methods for prompting a user to perform an exercise and monitoring the exercise are provided. Multiple independent sensors or sensor systems may be used to calculate energy expenditure. Various criteria may be used to manually or automatically select the independent sensor or sensor system or combination that will be used with the energy expenditure calculations.