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Revolutionizing Workout Efficiency with EMG-Enhanced Smart Clothing for Gym Enthusiasts

Inexperienced gym members often perform exercises incorrectly, leading to unproductive workouts and potential injuries. Concurrently, seasoned gym-goers struggle to maintain a balanced workout schedule due to impractical tracking methods. Our solution integrates EMG sensors into workout clothing, allowing users to monitor muscle activation in real-time. This unobtrusive and affordable technology enhances workout efficiency by logging exercise repetitions while also providing valuable insights and motivation for users. Our implementation plan focuses on risk mitigation, effective data processing, and user-friendly interfaces.

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Revolutionizing Workout Efficiency with EMG-Enhanced Smart Clothing for Gym Enthusiasts

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Presentation Transcript

  1. Project: Surfing Mittens Group #44 Members: Dhananja Jayalath Ryan Mann Neil Olij Chris Wiebe Consultant: Dr. Hiren Patel

  2. Outline • Introduction • Problem • Solution • Risks And Mitigation • Block Diagram Implementation plan and details • Questions

  3. Problem • Inexperienced gym members often perform exercises incorrectly • Unproductive • Leads to injury • Experienced gym members have trouble maintaining a balanced workout schedule • Paper and pencil is impractical • Easy to lose track • Personal training is expensive

  4. Solution • EMG sensors integrated into workout clothing • Detects muscle activation • Displays real-time activation data to user • Logs exercise repetitions over time • Advantages: • Unobtrusive • Affordable • Intuitive

  5. Risks and Mitigation • Noise and interference – must reject common mode • Contact motion • ECG interference • AC coupling • Involuntary or unforced muscle activation – use calibration • Physical integration of sensors into suit – use flexible PCB

  6. Signal Acquisition • Differential dry-electrodes • Instrumentation (differential) amplifier • Band-pass filter (20 – 500 Hz) with 40 dB/dec roll-off • Rectifier • Integrator – low pass envelope Amplified/Filtered Rectified/Envelope Gerdle, B., Karlsson S., Day, S., Djupsjobacka, M. Analysis of the Surface Electromyogram. Modern Techniques in Neuroscience. Chapter 26, 732

  7. Proof of concept

  8. Data Aggregation & Processing • Analog multiplexing • Analog to Digital Conversion (ADC) • STM32 ARM Cortex A3 Microcontroller • Bluetooth module

  9. User Interface • Custom Android application • User-defined rep objectives • Real-time data visualization • Updated rep counting • Reviewable rep history

  10. Questions?

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