Menstrual Cycle Data Integration for Phase-Based Workouts
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Solution Overview
Problem
Conventional exercise programs do not account for the four phases of a woman's menstrual cycle, leading to hormone imbalances, swelling, injuries, and poor mood regulation due to mismatched workout intensity and exercise types.
Innovation Solution
A system that determines a user's menstrual cycle phase and provides customized wellness information, including streaming workouts, nutrition profiles, and emotional insights, tailored to the user's physiological changes throughout the cycle, using AI and machine learning to recommend personalized fitness routines and nutrition based on menstrual cycle data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional exercise programs are used without considering menstrual cycle phases, then exercise routines are simple and consistent, but hormone imbalances, swelling, and injuries occur due to mismatched workout intensity
Solution Approach 1:
The exercise program dynamically adapts its intensity, type, and duration based on the user's menstrual cycle phase. The system automatically adjusts workout parameters (high intensity during follicular/ovulation phases, low intensity during luteal/menstrual phases) to maintain hormone balance and prevent injuries, transforming a static program into a dynamic one that responds to physiological changes
Solution Approach 2:
The system changes key exercise parameters (intensity, duration, type of exercise) according to menstrual cycle phase. During high-energy phases (follicular and ovulation), higher intensity and volume are permitted, while during low-energy phases (luteal and menstrual), intensity and volume are reduced to prevent hormone imbalance and injury
2Reliability
If exercise programs are customized to menstrual cycle phases, then health optimization and injury prevention improve, but the system requires complex tracking and determination of cycle phases
Solution Approach 1:
The system enables users to self-track their menstrual cycle phases through simple manual input or integration with wearable devices. Users input their period start date and cycle length, and the system automatically calculates and tracks their current phase, eliminating the need for complex medical monitoring while empowering users to participate in their own health management
Solution Approach 2:
The system uses an intermediary algorithm that translates simple user inputs (period start date, cycle length) into detailed cycle phase information. This intermediary processing layer converts basic data into actionable insights about current phase, energy levels, and recommended exercise intensity without requiring users to directly measure or understand complex physiological parameters
3Measurement precision
If users manually input menstrual cycle data each day, then data accuracy improves, but user convenience and daily engagement decrease
Solution Approach 1:
The system performs preliminary actions by automatically calculating cycle phases, energy levels, and exercise recommendations based on initial user inputs. Users only need to input their period start date and average cycle length once, and the system proactively generates daily personalized workout plans without requiring repeated manual inputs, maintaining both accuracy and convenience
Data Source
AI summary
A method for enabling users to input menstrual cycle data and receive customized wellness information, including streaming workouts, nutrition profiles, recipes, and physiological data such as science-based “horoscope-like” insights into the user's emotions, tailored to a user's expected physiology within a menstrual cycle phase is provided. The method includes receiving, from a device, menstrual cycle data for a user, wherein the menstrual cycle data includes one or more of a first date of the user's last menstrual cycle, a cycle length of the user's menstrual cycle and/or a length of the user's period, determining menstrual cycle phase data using the menstrual cycle data, determining feminine wellness information using the menstrual cycle phase data, wherein the feminine wellness information includes personalized interactive content, and transmitting, to the device, the menstrual cycle phase data and the feminine wellness information including the personalized interactive content.