Our Project Use Case Diagram
Our team aims to divide the entire system into the following six core modules. We have chosen to work on the Recovery Analysis & Prediction Module.
Main Functions and Key Technologies
1. Data Collection Module
Functions:
- Real-time collection of lower limb motion data using angle sensors (e.g., MPU-6050)
- Data transmission to the mobile device via Bluetooth Low Energy (BLE)
- Sensor data preprocessing (data formatting, time synchronization, etc.)
Key Technologies:
- Hardware interfaces (I2C/SPI for MEMS sensor data retrieval)
- BLE wireless communication (Bluetooth module connection & low-power data transfer)
- Data time synchronization (sensor timestamp correction)
2. Data Processing Module
Functions:
- Filtering & noise reduction (minimizing sensor errors and environmental interference)
- Calculation of joint angles, motion trajectories, velocity, and acceleration
- Data interpolation and smoothing (Kalman filter)
Key Technologies:
- Signal processing (Kalman filter, moving average filter)
- Mathematical modeling (Euler angle conversion, kinematics computation)
- Optimization algorithms (noise reduction, precision enhancement)
3. Data Storage Module
Functions:
- Local & cloud storage of patient rehabilitation data
- Maintenance of historical data for trend analysis & forecasting
- Fast data retrieval (search by time, recovery progress)
Key Technologies:
- Database storage (SQLite / Firebase / cloud storage)
- Data indexing (improving query efficiency)
- Data synchronization (ensuring consistency between local & cloud data)
4. Recovery Analysis & Prediction Module
Functions:
- Calculation of patient recovery progress (comparison with normal recovery curves)
- AI-based prediction (forecasting future recovery trends based on historical data)
- Generation of personalized reports (rehabilitation data visualization)
Key Technologies:
- Machine learning (linear regression / ARIMA time series prediction)
- Statistical analysis (mean, standard deviation, recovery trends)
- Data visualization (Matplotlib / D3.js for chart rendering)
5. Rehabilitation Training Recommendation Module
Functions:
- Personalized rehabilitation training plan based on the patient’s current data
- Video / GIF demonstrations of rehabilitation exercises
- Recording training effectiveness to optimize future plans
Key Technologies:
- AI recommendation algorithms (matching optimal training plans to user data)
- Video / animation playback (embedding training demonstration videos)
- User feedback system (patient feedback after training & adaptive adjustments)
6. User Interface & Mobile App Module
Functions:
- Intuitive display of real-time motion data
- Presentation of rehabilitation progress, training plans, and AI predictions
- Remote data sharing functionality (allowing doctors to monitor patient data)
Key Technologies:
- Cross-platform development (Flutter / React Native / Android / iOS)
- Data visualization (ECharts / Chart.js)
- Remote data access (RESTful API / WebSocket)
Module Relationships
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