🦶 Gait Analysis System using IMU Sensors

A Python-based gait analysis system built with Raspberry Pi 4B and LSM6DS3 IMU sensors.
This project enables real-time gait event detection, temporal-spatial parameter extraction, and automated report generation, designed to assist physiotherapists and healthcare professionals in monitoring patient rehabilitation.

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🚀 Features

• IMU Data Collection

  • Collects accelerometer & gyroscope data from multiple LSM6DS3 sensors via Qwiic multiplexer.
  • Controlled wirelessly using a Qwiic button (no HDMI needed).

• Data Processing

  • Filtering, bias correction, smoothing of raw signals.
  • Removal of static/non-gait periods.

• Event Detection

  • Detects Initial Contact (IC) & Final Contact (FC).
  • Uses peak-grouping strategy for accuracy.

• Parameter Extraction

  • Step time, stride time
  • Stance time, swing time
  • Step length, stride length
  • Walking speed, cadence

• Force Estimation

  • Calculates heel-strike impact force per step.
  • Configurable based on patient’s mass.

• Automated Report Generation

  • PDF/PNG reports with:
    • Acceleration & gyroscope time-series plots
    • Event detection visualization
    • Stride-wise speed & cadence trends
    • Violin plots & summary tables

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🛠 Tech Stack

• Hardware

  • Raspberry Pi 4B
  • Qwiic Hat & Qwiic Multiplexer
  • IMU Sensors (LSM6DS3)
  • Qwiic Button

• Software

  • Python (NumPy, SciPy, Pandas, Matplotlib, ReportLab)
  • pigpio (for I²C communication)
  • OpenSim (optional for biomechanical modeling)

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🔌 Hardware Setup

1. Connect LSM6DS3 sensors to the Qwiic Multiplexer (e.g., channels 1, 2, 3).
2. Attach the Qwiic Button to channel 0 (start/stop trigger).
3. Connect the multiplexer to the Qwiic Hat on Raspberry Pi 4B.
4. Ensure pigpiod service is running for I²C communication.

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📊 Example Output

• Step Length (m): 0.712 ± 0.008
• Walking Speed (m/s): 0.414 ± 0.056
• Cadence (steps/min): 55.3 ± 21

Reports include:
✅ Time-series graphs of accelerometer & gyroscope data
✅ Event detection visualization
✅ Stride-wise gait parameter plots
✅ PDF summary tables for clinical use

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🩺 Applications

• Clinical gait assessment
• Rehabilitation monitoring
• Sports biomechanics
• Research in human movement

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👨‍💻 Author

Chinmay Mhatre

• 🎓 B.Tech IT, K.J. Somaiya College of Engineering (2021–2025)
• 🔬 Project Lead, Gait Analysis System
• 📧 Email: [chinmaymhatre02003@gmail.com]
• 🔗 LinkedIn