Adaptive Virtual Training Worlds for Real-Time Intensity Feedback
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Solution Overview
Problem
Existing virtual training environments for athletic activities lack adaptability to individual participant intensity, providing predefined training plans that do not allow for free control and feedback, and fail to dynamically adjust the virtual environment based on real-time training data.
Innovation Solution
A computer-implemented method that receives intensity data from exercise machines and participants, generating a virtual training world that adapts in real-time to the participant's speed and inclination based on this data, providing continuous visual feedback and allowing pseudo-random path generation for a dynamic and engaging experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a predefined training plan is provided in a virtual training environment, then the training structure and guidance are improved, but the adaptability to individual participant intensity and freedom of control deteriorate
Solution Approach 1:
The patent implements dynamic adaptability by continuously adjusting the virtual environment parameters (speed, inclination, path) based on real-time intensity data from the exercise machine. The system transitions from static predefined plans to a dynamic environment that automatically responds to participant effort levels, allowing both structured guidance and individual adaptability simultaneously
Solution Approach 2:
The system incorporates real-time feedback loops where intensity data from the exercise machine is continuously monitored and used to adjust the virtual training world parameters. This feedback mechanism enables the environment to respond to participant performance, providing adaptive guidance without requiring predetermined fixed plans
2Device complexity
If the virtual training world is fixed with the same path each visit, then the system complexity is reduced, but the user engagement and realism deteriorate
Solution Approach 1:
The patent introduces dynamic path generation where the virtual training world creates varied routes and landscapes based on training parameters rather than using fixed predetermined paths. This dynamic approach generates different virtual environments for each training session while maintaining manageable system complexity through algorithmic generation
Solution Approach 2:
The system performs preliminary generation of virtual training paths and environments based on expected training parameters before the actual training session begins. This allows the virtual world to be prepared in advance with appropriate complexity levels, balancing engagement and system requirements
3Adaptability or versatility
If real-time intensity data is received and processed, then the adaptability and feedback are improved, but the computational requirements and processing time increase
Solution Approach 1:
The patent implements preliminary establishment of the virtual training world and path generation based on expected training parameters before the actual training begins. This pre-computation reduces the real-time processing burden during exercise sessions, allowing rapid response to intensity changes without excessive computational delays
Data Source
AI summary
The present invention relates to a computer-implemented method for providing an interactive training environment for athletic activities performed by a participant on an exercise machine the method comprising the steps of, —receiving intensity data describing the intensity of an athletic activity being performed on said exercise machine; —generating a virtual training world and displaying a visual representation of the virtual training world, the visual representation representing the participant position in the virtual training world—continuously updating the visual representation of the virtual training world and thereby creating the visual impression that said participant is moving into the virtual training world with a speed or inclination which is determined based on the received intensity input. Thereby the virtual training environment adapts to the training intensity of the participant.