F.O.C.U.S. Assessment

Following Ongoing Cues Under Structure

F.O.C.U.S. Assessment Application

F.O.C.U.S. is a visual attention assessment tool built on Electron, designed for measuring attention metrics in research and educational settings.

About This Application

The F.O.C.U.S. Assessment is a computerized visual test that measures attention through a structured protocol of alternating target and non-target stimuli. Participants respond to target stimuli by pressing a key or clicking, and the system captures response timing, accuracy, and variability.

Core Features

• High-Precision Timing: Uses Node.js process.hrtime.bigint() for sub-millisecond timestamp capture on the CPU level
• 648-Trial Protocol: Standardized test with alternating stimuli over approximately 21.6 minutes
• Attention Metrics: Measures response time, response variability, commission errors, omission errors, and signal detection (d-prime)
• ACS Scoring: Attention Comparison Score with Z-score normalization against age/gender normative data
• Local Data Storage: Encrypted SQLite database with GDPR-compliant 7-day retention
• Cross-Platform: Windows, macOS, and Linux support

Intended Use

Research and Educational Use

This application is well-suited for:

• Academic research studies on attention
• Educational psychology experiments
• Cognitive science investigations
• Screening in non-clinical settings
• Training and practice assessments

The application provides precise timing measurements and standardized protocols that make it appropriate for research purposes where the focus is on relative comparisons and group-level analysis.

Limitations for Clinical Practice

This application is NOT designed for clinical diagnosis or medical decision-making. Key limitations include:

1. Monitor-Dependent Temporal Accuracy: Stimulus presentation timing varies based on display technology (see timing accuracy table below)
2. No FDA/Medical Device Clearance: Not certified as a medical device
3. Normative Data Limitations: Reference data may not represent all populations
4. No Healthcare Integration: Current version lacks FHIR compatibility and EMR integration
5. No Quality Assurance Protocol: No calibration verification or drift detection

Clinical attention assessments require specialized hardware and validated medical devices that meet regulatory standards.

Timing Accuracy

CPU-Level Precision

The application captures timestamps using process.hrtime.bigint(), which provides nanosecond-resolution timing from the CPU's high-performance counter. This ensures consistent temporal ordering of events within the application.

Monitor-Dependent Presentation Accuracy

The actual time when the visual change appears on screen depends heavily on display technology. The following table compares expected temporal accuracy for different monitor types:

Display Type	Typical Latency	Refresh Rate	Expected Accuracy	Notes
CRT	1-3 ms	60-120 Hz	±2-5 ms	Analog display with near-instant response; gold standard for timing research
LCD	5-15 ms	60-144 Hz	±8-20 ms	Response time varies by pixel transition; common in older displays
LED	1-8 ms	60-240 Hz	±3-12 ms	Backlight technology; lower latency than CCFL LCD
OLED	0.1-1 ms	60-120 Hz	±1-3 ms	Individual pixel illumination; excellent for timing-critical applications
QLED	2-10 ms	60-144 Hz	±4-15 ms	Quantum dot enhancement; similar to LED latency characteristics

Why Monitor Timing Matters

Even with perfect CPU-level timestamp capture, the actual visual stimulus appears on screen according to the display's refresh cycle and response characteristics. For research requiring precise temporal alignment, consider:

• Using OLED or high-refresh-rate LED displays
• Measuring end-to-end latency with a photodiode
• Synchronizing with external stimulus presentation systems
• Documenting display specifications in research publications

Konsulin Ecosystem Integration

This application is a component of the Konsulin Integrated Health Record Ecosystem, a modular platform designed to provide healthcare facilities with flexible, standards-based clinical tools.

Architecture Philosophy

The Konsulin ecosystem emphasizes:

• Modularity: Standalone tools that work independently or as part of the ecosystem
• Standards Compliance: FHIR, HL7, and healthcare interoperability standards
• Privacy-First Design: Local data processing with user consent
• Research Accessibility: Tools available for academic use without licensing barriers

Getting Started

System Requirements

• Node.js >=24.0 and npm 11+ (managed via mise for reproducibility)
• Platform-specific build tools (Xcode, Visual Studio, or build-essential)
• 4GB RAM minimum, 8GB recommended
• Any display supported by the operating system

Installation

For mise installation and activation, refer to the project documentation.

# Clone the repository
git clone https://github.com/konsulin-care/focus.git
cd focus

# Install dependencies using mise-managed Node.js
mise install  # Installs tools from mise.lock

At this point, you can check whether the installed tools are available in your environment, e.g., the command mise where node and which node should return the same path.

# Rebuild native modules for Electron
npm run electron-rebuild

# Build the project
npm run build

# Start development mode
npm run dev

Building for Production

# Build for current platform
npm run build:platform

# Platform-specific builds
npm run build:win    # Windows portable app
npm run build:mac    # macOS DMG package
npm run build:linux  # Linux AppImage

Support

For questions about research applications or ecosystem integration:

• GitHub Issues for bug reports and feature requests
• Documentation for technical questions
• Contact hello@konsulin.care for enterprise support options

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Disclaimer: This software is provided for research and educational purposes only. It is not a medical device and should not be used for clinical diagnosis, treatment decisions, or any healthcare-related activities requiring regulatory clearance.