Cycle-Based Workout Coaching via Heart Rate Variability
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Solution Overview
Problem
Existing technologies lack the ability to detect a user's hormonal cycle and provide synchronized adjustments to coaching recommendations for exercise, recovery, sleep, and diet.
Innovation Solution
A system that measures physiological parameters such as respiratory rate and heart rate variability to identify the phase of a hormonal cycle, allowing for automatic adjustments to coaching recommendations based on the cycle phase.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If physiological monitoring is used to detect hormonal cycle phase, then coaching recommendations can be synchronized with cycle phase, but device complexity increases
Solution Approach 1:
The patent uses heart rate variability (HRV) as an intermediary biomarker to indirectly detect hormonal cycle phase. Instead of directly measuring hormones, the system monitors HRV changes that correlate with different cycle phases, providing a non-invasive proxy measurement that enables cycle-aware coaching without requiring direct hormonal analysis
Solution Approach 2:
The patent replaces complex hormonal analysis systems with simpler physiological monitoring. By substituting direct hormone measurement with heart rate variability analysis, the system achieves cycle phase detection using standard wearable sensor technology rather than requiring complex biochemical analysis equipment
2Measurement precision
If continuous heart rate data is collected to identify hormonal cycle phase, then measurement precision improves, but energy consumption increases
Solution Approach 1:
The system implements periodic sampling of heart rate data at strategically selected intervals rather than truly continuous monitoring. By analyzing HRV at key moments (e.g., morning resting measurements, post-exercise recovery periods), the system accumulates sufficient data to identify cycle phase patterns while minimizing overall energy consumption compared to constant high-frequency sampling
Data Source
AI summary
Physiological parameters such as respiratory rate and/or heart rate variability can be measured over time for a user and correlated to physiological and/or hormonal cycles such as the menstrual cycle. By determining the phase of such a cycle in this manner, an automatic coach for the user can recommend phase-specific adjustments to activities such as sleep and exercise.


