RehabGait is an advanced remote gait analysis system designed to revolutionize physiotherapy and rehabilitation using modern wearable technology and cloud-based data processing. Traditional methods are subjective, localized, and often impractical for regular monitoring.
Our system solves these limitations by using:
- 🦶 Pressure-sensitive insoles
- 🧭 Inertial Measurement Units (IMUs)
- ☁️ Real-time cloud data processing
- 💻 An intuitive web platform for clinics, doctors, and patients
We offer a complete end-to-end solution:
- Wearable insole and IMU-based sensors capture biomechanical data
- ESP32 microcontrollers transmit data over MQTT (AWS IoT Core)
- Real-time visualization (heatmaps, gait parameters, angles)
- Secure backend architecture using Spring Boot and PostgreSQL
- Python microservices generate analytics and reports
- Users access reports via a responsive web interface (React + MUI)
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👣 Real-time Plantar Pressure Heatmap
View live pressure distribution for each step on the foot sole. -
🔍 Comprehensive Gait Analysis
Includes stride length, step duration, ankle/hip/knee angles, cadence, and more. -
📋 Auto-Generated Reports
Includes plots, feedback summaries, and patient-specific diagnostics. -
👥 Role-Based Multi-User Platform
Supports Admin, Clinic Manager, Doctor, and Patient roles. -
🧪 Calibration & Session Launch
Device calibration, test session controls, and real-time streaming. -
🔐 Secure & Scalable Backend
TLS, JWT, X.509 certificates, and microservices for modular deployment.
| Component | Description |
|---|---|
| Insole Sensor | FS-INS-16Z Pressure Array with 3.3V logic and FPC connector |
| IMU Sensor | BN0055 – 9DOF with sensor fusion and orientation tracking |
| Microcontroller | ESP32-WROOM with UART communication |
| Other | Custom PCB, battery-powered, NTP time sync, WiFi-enabled |
The RehabGait system combines wearable sensors, secure IoT communication, cloud processing, and a user-friendly web interface.
- Sensor Node collects data from the insole pressure array and IMU sensor.
- Data is transmitted via UART to a WiFi Node, which publishes it to AWS IoT Core using MQTT.
- AWS IoT Core routes the data to:
- A Time-Series Database for real-time storage.
- A Processing Queue consumed by a Python Microservice, which analyzes gait patterns and generates visual reports.
- The Main Backend (Spring Boot) handles user roles, data management, and report retrieval.
- The Frontend (React + MUI) provides role-specific dashboards and live session monitoring via WebSocket and HTTP.