Building a Workout Tracking App with Wearable Data

Many fitness apps fail because they only integrate with one device ecosystem, usually Apple Health Kit or Health Connect, yet users expect support for the device they already wear and the same level of data granularity from their advanced wearables. Users with devices like Whoop, Garmin, or Oura expect to see the detailed metrics they're used to, such as recovery scores, HRV data, training load, and device-specific analytics, not just basic step counts and heart rate that aggregator platforms provide.

A unified Wearables API like Spike gives you access to 500+ devices through a single API integration, eliminating the need to integrate with dozens of separate device APIs; however, you still receive the same data depth as you would building custom integrations. 

This guide shows you how to build a competitive fitness app faster, reduce engineering overhead, and add features powered by real wearable activity and biometric data.

Why choose a unified wearables API

21% of the US population is wearing a fitness tracker, and usage spans dozens of different brands and models. Integrating each of these separately means months of engineering time, constant version updates, and fragmented codebases.

Spike solves this by providing a unified Wearables API that supports over 500 devices. You connect once, and every major manufacturer becomes compatible with your app, from Garmin and Fitbit to emerging brands like Luna.

This allows you to serve a bigger user base, as well as increase user retention and satisfaction, and puts your app ahead of the competition in a saturated market.

Essential wearable integration features for workout tracking apps

Activity data collection

A fitness API integration should capture workout sessions with accurate timestamps, duration, and activity type. Fast syncing is also important as users expect to see results as soon as they finish working out, so your integration should support data delivery through webhooks or SDK integration to keep activity data current.

Biometric performance metrics

Users want to see and analyze detailed performance insights, such as heart rate zones, calories burned, distance, pace, and elevation changes. Your integration should provide these, and keep in mind that different activities require specific metrics, such as laps for swimming and power output for cycling.

Historical data and trends

Your app should access historical wearables data to show weekly summaries, monthly progress reports, and year-over-year comparisons. Historical wearable data enables personalized workout recommendations and recovery suggestions based on training patterns. A great wearable data layer API ensures reliable access to both recent and historical activity metrics.

Why do fitness app developers choose Spike API?

Spike Wearables API is purpose-built for developers who want fast, reliable integrations without managing device-specific logics.

Plug-and-play integration with dedicated support

Spike documentation pages are designed to be easy to understand and guide you through every step of implementation. Also, every client gets support from a dedicated implementation engineer. This hands-on support accelerates development and helps you avoid common integration pitfalls.

After switching to Spike, OuiLive reduced support tickets by 40% and freed up their development team to focus on new features. Showcasing the importance or the right API partner to help your app work smoothly. 

Raw and normalized data access

Spike Wearable API gives you access to data in two formats. The normalized format provides unified metrics across all devices, making it easy to build features such as analytics that work consistently. Raw format gives you access to device-specific wearable data when you need granular details or unique sensor capabilities.

Built for AI analytics

Our Wearables API is compatible with LLM models via Spike MCP layer, delivering enterprise-grade infrastructure for large-scale data volumes. It provides structured, model-compatible data that reduces data preparation time for AI applications.

If you're building an AI-powered fitness coach or predictive analytics, leverage our MCP layer for LLM-compatible data pipelines to avoid extensive preprocessing.

No maintenance burden

Device manufacturers regularly update their APIs, release new sensors, and change requirements. Spike monitors these changes and handles updates. Your app continues working with no modifications when manufacturers update their platforms.

Working with Spike API

Spike provides the fastest path from idea to production-ready wearable data integration across 500+ devices. Add a single API integration, receive data via webhooks or SDKs, and start building insights-driven fitness features immediately.

Ready to build your workout tracking app? Schedule a demo to see how Spike can accelerate your development.