Flywheel Training System Adaptive Power Thresholds
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Solution Overview
Problem
Existing training methods and systems for physical conditioning are limited by effectiveness, variance, imprecision, undesirable fatigue, inconsistency, overtraining, injury risk, and poor measurement of training productivity and objectives.
Innovation Solution
A maximal power interval training method using a pedal-crank input unit connected to a flywheel machine, with a session management module that increments power output thresholds and adjusts duration of maximum power and rest periods, guided by user profiles and physical conditioning models to optimize training sessions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Strength
If high intensity training is performed to the point of momentary muscular failure, then strength and power are improved, but risk of injury and undesirable fatigue increase
Solution Approach 1:
The training system implements periodic action through structured interval training protocols that alternate between high-intensity exercise periods and recovery periods. The system automatically controls the duration and intensity of each interval, ensuring that high-intensity efforts are followed by adequate recovery time, thereby improving strength and power while preventing overtraining and injury.
Solution Approach 2:
The training system incorporates real-time feedback through sensors that monitor power output, heart rate, and other physiological parameters. The system provides immediate feedback to the user and automatically adjusts subsequent intervals based on performance data, ensuring that training remains in the optimal intensity range without exceeding safe limits.
2Productivity
If training intensity is increased to improve effectiveness, then training productivity is improved, but consistency and measurement precision deteriorate
Solution Approach 1:
The training system replaces manual measurement and tracking with automated electronic sensors and processors. Power output is measured precisely using strain gauges or torque sensors, while heart rate and other physiological parameters are captured through electronic sensors. This automated measurement system ensures high precision even at varying training intensities.
Solution Approach 2:
The system automatically calculates and tracks training metrics such as power output, energy expenditure, and training load without requiring manual input. The processor continuously monitors sensor data and generates performance reports, enabling precise measurement of training productivity across all intensity levels.
3Reliability
If rest periods are extended to reduce fatigue, then recovery is improved, but training duration and time investment increase
Solution Approach 1:
The training system dynamically adjusts rest period duration based on real-time physiological feedback. Recovery periods are extended or shortened according to the user's actual recovery status, as indicated by heart rate variability and power output metrics. This dynamic approach optimizes recovery efficiency while minimizing total training time.
Solution Approach 2:
The system changes multiple training parameters simultaneously, including rest period duration, interval intensity, and interval length, to achieve optimal training effects. By coordinating changes in these parameters, the system maintains effective training stimulus while managing fatigue and reducing overall training time.
Data Source
AI summary
The present disclosure provides a training method for operating a training system including a pedal-crank input unit drivingly connected in freewheeling relationship to a flywheel machine with inertial load of at least (0.5) kg·m2, an ergometer to determine power, a processor, a profile module, and a session management module, wherein the processor determines a minimum acceptable threshold value of maximum power output for a maximum power period, duration of the maximum power period, and increments the minimum acceptable threshold value of maximum power output for a next maximum power period where the minimum acceptable threshold value of maximum power output for a maximum power period is met.