Tracking Barbell Exercises with Motion Sensor Data

This project processes motion sensor data from strength exercises using a wearable MetaMotion device. It includes data cleaning, signal filtering, feature engineering, supervised classification, and repetition counting using Python and Jupyter.

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Features

• Motion data merging from accelerometer and gyroscope
• Time indexing and resampling (5Hz)
• Signal smoothing using LowPassFilter
• Rep counting via peak detection
• Outlier removal
• Supervised learning (Random Forest classifier)
• Confusion matrix and performance evaluation

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Setup Instructions

1. Clone the repository

    git clone https://github.com/mariocroix/S4-MotionRep-Analyzer.git
    cd S4-MotionRep-Analyzer.git
   

2. Create conda environment

    conda env create -f environment.yml
    conda activate tracking-barbell-exercises
   

3. Running the Code (Jupyter Interactive)
   All code snippets and scripts can be executed using Jupyter Interactive Mode. This mode was used throughout development:
   • Open a Python file in VS Code.
   • Select a code cell and press Shift + Return (Shift + Enter) to execute it.
   • The output appears in a separate interactive Jupyter panel.