# Data Types (Biomarker) Thryve supports a comprehensive range of health and fitness data types, each designed to enable specific product experiences and use cases. You can access the full list [here](https://airtable.com/appUsNn6CVszlBjfw/shroLjZ7pigt4oV7j). {% hint style="info" %} Data type availability varies significantly across data sources. Not every wearable or health platform supports all data types. Always check the availability matrix to understand which data sources provide the specific metrics you need for your product. {% endhint %} {% embed url="" %} ## Data type categories Our data types are organized into 18 categories designed around product use cases and user experiences: ### Body Composition & Measurements Foundation metrics for health tracking apps, weight management platforms, and fitness progress monitoring. Includes weight, height, BMI, muscle mass, bone mass, and body fat measurements. **Key Use Cases**: Weight loss apps, fitness progress tracking, health monitoring dashboards, body composition analysis tools. ### Activity Daily movement and general activity metrics for lifestyle and wellness applications. Covers steps, calories burned, active duration, distance covered, and general activity tracking. **Key Use Cases**: Daily wellness apps, step challenges, lifestyle coaching platforms, general fitness tracking. ### Workouts Exercise-specific performance metrics for fitness and training applications. Includes pace, speed, training intensities, sport-specific metrics, and cycling performance data. **Key Use Cases**: Fitness training apps, running coaches, cycling platforms, sports performance analysis, workout tracking. ### Heart Rate Basic cardiovascular monitoring for health and fitness applications. Covers resting heart rate, average heart rate, sleep heart rate, and heart rate zones. **Key Use Cases**: Fitness apps, health monitoring, workout intensity tracking, general cardiovascular health awareness. ### Sleep Comprehensive sleep tracking for wellness and health optimization apps. Includes sleep duration, sleep stages, sleep quality metrics, and sleep-related measurements. **Key Use Cases**: Sleep optimization apps, wellness platforms, health coaching, circadian rhythm tracking, sleep disorder monitoring. ### Stress & HRV Stress monitoring and heart rate variability for mental health and recovery applications. Combines stress indicators with HRV metrics that reflect autonomic nervous system activity. **Key Use Cases**: Stress management apps, mental health platforms, recovery optimization, meditation apps, wellness coaching. ### Cardiovascular Health Advanced cardiovascular metrics for medical and serious health monitoring applications. Includes blood pressure measurements, arterial pressure, and pulse wave velocity. **Key Use Cases**: Medical monitoring apps, hypertension management, cardiovascular health platforms, clinical health tracking. ### Advanced Cardiac Analysis Sophisticated cardiac monitoring for medical and research applications. Includes ECG data, arrhythmia detection, and advanced cardiac health indicators. **Key Use Cases**: Medical monitoring platforms, cardiac health apps, research applications, clinical-grade health tracking. ### Blood Glucose Blood sugar monitoring for diabetes management and metabolic health. Includes actual and estimated glucose measurements. **Key Use Cases**: Diabetes management apps, metabolic health platforms, medical monitoring tools, health coaching for pre-diabetes. ### Respiratory & Breathing Breathing and respiratory health metrics for wellness and medical applications. Includes respiratory rate, breathing patterns, and blood oxygen saturation. **Key Use Cases**: Wellness apps, meditation platforms, respiratory health monitoring, fitness recovery tracking. ### Movement Analysis Advanced biomechanical metrics for serious athletes and movement optimization. Includes stride length, ground contact time, vertical oscillation, and gait analysis. **Key Use Cases**: Running performance apps, injury prevention platforms, athletic coaching tools, biomechanical analysis. ### Detailed Nutrition Comprehensive nutritional tracking for diet and health management. Covers macronutrients, micronutrients, vitamins, minerals, and detailed dietary intake. **Key Use Cases**: Nutrition tracking apps, diet management platforms, health optimization tools, medical nutrition monitoring. ### Audio & Hearing Health Hearing protection and audio exposure monitoring. Tracks audio exposure levels for hearing health awareness. **Key Use Cases**: Hearing protection apps, audio exposure monitoring, occupational health tools, hearing wellness platforms. ### Location & GPS Geographic data for activity context and location-based health insights. Includes latitude, longitude, and location-specific measurements. **Key Use Cases**: Activity mapping, location-based health insights, outdoor fitness tracking, geographic health analysis. ## Choosing the Right Data Types #### For General Wellness Apps Focus on **Activity**, **Sleep and** **Heart Rate** categories. These provide comprehensive lifestyle tracking without overwhelming users with complex metrics. #### for Fitness and Training Apps Prioritize **Activity**, **Workouts**, **Heart Rate**, and **Movement Analysis**. Add **Sleep** and **Stress & HRV** for recovery optimization features. #### For Health Monitoring Platforms Emphasize **Body Composition**, **Cardiovascular Health**, **Blood Glucose**, and **Advanced Cardiac Analysis** for comprehensive health tracking. #### For Specialized Applications Utilize **Advanced Cardiac Analysis**, **Blood Glucose**, **Cardiovascular Health**, and **Respiratory & Breathing** --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.thryve.health/thryve-product-overview/access/data-types-biomarker.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. 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