Scholarlink

This project presents the design and development of a low-cost Spasticity Assessment Tool utilizing 3D printing, surface EMG sensors, and a rotary encoder. Traditional methods for spasticity assessment, such as the Modified Ashworth Scale (MAS), are highly subjective and often yield inconsistent results. To address these limitations, this tool aims to gather precise, quantitative data on muscle activity and joint angles. The custom hardware includes 3D printed components, an ESP32 microcontroller for its processing power and connectivity, a surface EMG sensor to measure muscle activity, and a rotary encoder to detect joint angles. The ESP32 firmware collects and transmits the data, which is then stored for further analysis. Preliminary results indicate that the tool provides accurate and reliable measurements, demonstrating its potential as an affordable and accessible diagnostic option for spasticity, particularly in resource-limited settings. Future work will focus on refining the hardware and exploring software solutions for data visualization and analysis.

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Cost-Effective Elbow Spasticity Assessment Tool Leveraging 3D Printing and EMG Technology

  • 会议论文

  • 发表日期：

    2026年

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  • Mike Dan Degenstein,
  • Cheng Yee Low,
  • Uwe Gleiter

摘要

This project presents the design and development of a low-cost Spasticity Assessment Tool utilizing 3D printing, surface EMG sensors, and a rotary encoder. Traditional methods for spasticity assessment, such as the Modified Ashworth Scale (MAS), are highly subjective and often yield inconsistent results. To address these limitations, this tool aims to gather precise, quantitative data on muscle activity and joint angles. The custom hardware includes 3D printed components, an ESP32 microcontroller for its processing power and connectivity, a surface EMG sensor to measure muscle activity, and a rotary encoder to detect joint angles. The ESP32 firmware collects and transmits the data, which is then stored for further analysis. Preliminary results indicate that the tool provides accurate and reliable measurements, demonstrating its potential as an affordable and accessible diagnostic option for spasticity, particularly in resource-limited settings. Future work will focus on refining the hardware and exploring software solutions for data visualization and analysis.