Project Overview
A comprehensive web-based behavioral testing platform built with jsPsych, designed for conducting online experiments in auditory processing and speech perception research. The platform features real-time data collection, advanced analytics, and seamless integration with research databases.
Technology Stack
Frontend
jsPsych 7.3, JavaScript ES6+, HTML5, CSS3
Backend
Node.js, Express, PostgreSQL, RESTful APIs
Analytics
R, Python, Data Visualization, Statistical Analysis
Key Features
🎯 Experiment Design
- Drag & Drop Interface: Visual experiment builder for non-programmers
- Template Library: Pre-built templates for common audiology tests
- Custom Stimuli: Support for audio, visual, and text stimuli
- Randomization: Advanced randomization and counterbalancing
📊 Data Collection
- Real-time Analytics: Live monitoring of participant responses
- Multi-format Export: CSV, JSON, R-ready datasets
- Quality Control: Automated validation and screening
- GDPR Compliance: Secure data handling and privacy protection
Code Example
// Speech-in-Noise Test Implementation
const speechInNoiseTest = {
type: jsPsychAudioKeyboardResponse,
stimulus: () => generateStimulusPath(),
choices: ['1', '2', '3', '4'],
prompt: 'Which word did you hear?
',
trial_duration: 5000,
response_ends_trial: true,
on_finish: function(data) {
// Real-time accuracy calculation
data.correct = checkResponse(data.response, data.target);
updatePerformanceMetrics(data);
}
};
Performance Metrics
500+
Participants Tested
15
Research Studies
98%
Uptime Reliability
2.3s
Avg. Load Time
Technical Implementation
The platform leverages jsPsych's plugin architecture to create custom experiment components specifically designed for auditory research. The backend API handles participant management, data validation, and real-time analytics through WebSocket connections.
Architecture Highlights
- Microservices: Modular design for scalability and maintenance
- Docker Containers: Consistent deployment across environments
- CI/CD Pipeline: Automated testing and deployment workflows
- Load Balancing: Nginx configuration for high availability
Future Enhancements
AI Integration
Machine learning algorithms for adaptive testing and personalized difficulty adjustment.
Mobile App
Native mobile applications for iOS and Android with offline capabilities.