Client Objective
To create an intelligent mobile application that accurately tracks and predicts the stages of sleep using smartwatch sensor data, offering actionable insights for both healthcare providers and individuals focused on improving sleep health.
Solution Overview
We developed Sleep Stage Prediction, a smart healthcare app that uses AI algorithms to analyze smartwatch data and deliver precise predictions of sleep stages such as:
- Light Sleep
- Deep Sleep
- REM Sleep
- Awake Periods
The system is designed for real-time sleep monitoring and includes both online and offline functionality, making it accessible and reliable for everyday use.
Key Features
✅ AI-powered sleep stage classification
✅ Works with popular smartwatch platforms
✅ Provides visual sleep trend dashboards
✅ Personalized recommendations for sleep improvement
✅ Offline tracking and data sync
Technologies Used
- Time-Series Analysis with Deep Learning (LSTMs, RNNs)
- Wearable Integration (WearOS, Apple Watch, Fitbit APIs)
- Mobile App Development (React Native / Flutter)
- Edge AI for offline predictions
Impact & Results
- Delivered accurate sleep stage predictions with high reliability
- Enabled personalized sleep insights to improve user health habits
- Helped healthcare providers monitor patients remotely
- Encouraged better sleep hygiene and self-awareness
Sleep Stage Prediction illustrates our ability to combine wearable tech, AI, and user-centric design to build meaningful digital health products that support proactive well-being.