Portable Face-Shielding Device Based on sEMG Considering the COVID-19 Scenario

Area of Science:

• Biomedical Engineering
• Rehabilitation Technology
• Assistive Devices

Background:

• Mask-wearing is crucial for infection control, yet poses challenges for individuals with upper limb amputations.
• Current methods for assisting mask-wearing can lead to bacterial contamination.
• There is a need for independent and hygienic mask-wearing solutions for amputees.

Purpose of the Study:

• To design and develop an automatic, portable face shield assistive device.
• To utilize surface electromyography (sEMG) signals for controlling the assistive device.
• To address the challenges faced by amputees in independently wearing face masks.

Main Methods:

• A 3D-printed face shield-wearing mechanism was engineered.
• A novel control method was developed using a 16-feature extraction model and a Softmax classification neural network.
• The system was tested on an STM32 microcontroller unit (MCU) with optimized carbon nanotube (CNT)/polydimethylsiloxane (PDMS) electrodes.

Main Results:

• The developed assistive device demonstrated successful operation based on sEMG signals.
• The feature extraction and neural network models were effectively implemented on the MCU.
• The integrated system showed promising results for practical application.

Conclusions:

• The automatic face shield assistive device offers a viable solution for individuals with upper limb amputations.
• The sEMG-based control system provides a novel approach to assistive technology.
• Further implementation and testing are recommended for widespread adoption.