Signal is a professional behavioral monitoring application designed specifically for healthcare professionals. By analyzing physiological and behavioral patterns—such as heart rate variability (HRV), sleep quality, and workload—Signal uses on-device machine learning to identify early indicators of clinical burnout before they manifest as exhaustion.
In high-pressure clinical environments, burnout often goes unnoticed until it's too late. Signal acts as an early-warning system, transforming raw health data into a "7-day Behavioral Index." The app focuses on five key pillars:
- Physiological Stress: Tracking HRV as a marker of nervous system recovery.
- Restoration: Monitoring sleep cycles and deficits.
- Movement: Encouraging non-strenuous activity to lower cortisol.
- Workload: Identifying dangerous patterns of sustained overwork.
- Mindful Exploration: Using location-based services to suggest nearby "green spaces" for mental resets.
- Dynamic Risk Dashboard: A sophisticated UI featuring a custom ring gauge that visualizes current burnout risk levels (Low, Moderate, High) using real-time Core ML inference.
- Behavioral Sparklines: A "This Week" grid providing at-a-glance trends for sleep, steps, HRV, and shift hours with embedded sparkline charts.
- Actionable Insights: Intelligent cards that don't just report data but suggest concrete next steps (e.g., "Schedule a break," "Talk to a colleague").
- Explore Nearby: A MapKit-integrated feature that surfaces nearby parks and landmarks, encouraging clinicians to take scenic routes or brief urban "quests" for mental recovery.
- Calm UI Design: A nature-inspired aesthetic using a palette of forest greens, sages, and warm ambers to reduce interface-induced stress.
- UI Framework: Pure UIKit (no SwiftUI in core modules) utilizing Compositional Layout and Diffable Data Sources for high-performance, fluid scrolling.
- Reactive Logic: Combine for state management and binding ViewModels to the view layer.
- Intelligence: Core ML for on-device, privacy-preserving risk prediction.
- Location: MapKit and CoreLocation for proximity-based "Mindful Explorer" features.
- Aesthetics: SF Symbols 6 with dynamic symbol effects (Pulse, Bounce, Variable Color) for a "live" feel.
- Data Layer: Protocol-oriented service layer with Mock and Live providers.
Modules/Dashboard/: The heart of the app; contains the complex Compositional Layout and ViewModel logic.CoreML/: contains theBurnoutRiskEngineand scoring algorithms.Services/: Data fetching and Insight generation logic.Resources/: TheDesignSystem.swiftfile, housing the central design tokens (colors, spacing, typography).Models/: Clean,Codabledata structures used across the app.
- Environment: Requires Xcode 16+ and iOS 17+ (for SF Symbols 6 effects).
- Clone:
git clone https://github.com/[username]/signal-ios.git - Run: Open
Signal.xcodeprojand run on an iPhone simulator. (Note: Proximity features work best with simulated locations in the debugger).