Step-Scope

Click the image above to watch the project demo video.

📋 Project Overview

Step Scope is a project developed as part of the Biomedical Engineering Course at the Faculty of Engineering, Ain Shams University. The main objective of this project is to design and develop a wireless, portable, and wearable system that utilizes inertial measurement units (IMUs) and force-sensitive resistors (FSRs) to monitor foot plantar pressure and gait in individuals with diabetic foot disease (DFD) or other neurological abnormalities affecting gait.

Please note that the system has been thoroughly tested on both healthy subjects and patients/simulated patients to ensure its effectiveness and accuracy.

✨ Key Features

The system provides the following features:

• Real-time visualization of foot pressure using color coding (Heatmap).
• Measurement of various spatiotemporal gait parameters.
• Detection of gait events and phases (Heel Strike, Mid-Stance, Toe Off, etc.).
• Analysis of shank kinematics using IMUs.
• Estimation of the center of pressure (CoP).
• Assessment of patient stability based on FSR and IMU data.
• Wireless Telemetry: Data is transmitted wirelessly to a PC for visualization, analysis, and reporting.

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⚙️ Hardware Architecture

The system is built around the ESP8266 (NodeMCU) microcontroller, which collects data from the sensor array and transmits it via TCP/IP to the ROS backend.

Components

• Microcontroller: NodeMCU v1.0 (ESP8266)
• IMU: 2x MPU6050 (Accelerometer & Gyroscope for Thigh and Shin)
• Force Sensors: 5x Force Sensitive Resistors (FSR) placed at key plantar pressure points.
• Multiplexer: 8-channel Analog Multiplexer (to handle 5 FSRs on the single ESP8266 Analog Pin).

Pinout Configuration

Component	NodeMCU Pin	GPIO	Description
Multiplexer S0	D7	13	Channel Select Bit 0
Multiplexer S1	D6	12	Channel Select Bit 1
Multiplexer S2	D5	14	Channel Select Bit 2
Multiplexer Sig	A0	ADC	Analog Signal Input
MPU6050 SDA	D2	4	I2C Data
MPU6050 SCL	D1	5	I2C Clock

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💻 Software Architecture

The PC-side software utilizes ROS (Robot Operating System) to modularize data handling, processing, and visualization.

1. Communication Node (comm_data.py): Establishes a TCP/IP socket connection with the ESP8266.
   • Publishes raw sensor strings to the /comm topic.
2. Parser Nodes:
   • fsr_data.py: Subscribes to /comm, parses FSR arrays, and publishes to /fsr_data.
   • imu_pub.py: Parses IMU angles and publishes to /imu_data.
3. Visualization Node (project.py): A Tkinter-based GUI that subscribes to all sensor topics.
   • Visualizes Heatmaps, Knee Angles, and Gait Phases in real-time using OpenCV and Matplotlib.

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🖥️ Graphical User Interface (GUI)

The GUI allows for patient data entry, real-time monitoring, and data recording.

Gait Phase Detection Example

Below is an example of the system detecting the "Mid Stance" phase during a live test.

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🚀 Getting Started

Prerequisites

• OS: Ubuntu 20.04 (Recommended for ROS Noetic)
• ROS Version: ROS Noetic Desktop Full
• Python: Python 3.8+

Installation

1. Clone the repository into your Catkin Workspace:

   cd ~/catkin_ws/src
   git clone https://github.com/mohamedeyaad/Step-Scope.git
   cd ..
   catkin_make
   source devel/setup.bash

2. Install Python Dependencies:

   pip3 install -r requirements.txt

   (Note: Ensure numpy, matplotlib, scipy, pandas, XlsxWriter, opencv-python, and Pillow are installed).

3. Upload Firmware:

   • Important: The firmware code is located in a separate branch.
   • Switch to the firmware branch:

     git checkout Arduino-Code

   • Open the .ino file in Arduino IDE.
   • Configure your WiFi credentials in the code.
   • Upload to the NodeMCU.

Running the System

1. Power on the Hardware: Ensure the NodeMCU is powered and connected to the WiFi.
2. Launch the System: Run the ROS launch file to start the communication, parsing, and GUI nodes simultaneously.

   roslaunch step_scope nodes.launch

📧 Contact

For any inquiries, please contact me at: mooeyad@gmail.com