Hardware System for Real-Time EMG Signal Acquisition and Separation Processing during Electrical Stimulation.

Area of Science:

• Biomedical Engineering
• Signal Processing
• Neuroscience

Background:

• Electrical stimulation can interfere with electromyography (EMG) signal acquisition.
• Integrating EMG acquisition with electrical stimulation requires modified signal processing techniques.
• Existing systems may struggle with real-time hybrid signal processing.

Purpose of the Study:

• To develop a real-time EMG signal acquiring and processing device capable of operating during electrical stimulation.
• To create a user-friendly and flexible system for hybrid EMG signal management.
• To overcome the challenges posed by electrical stimulation artifacts in EMG data.

Main Methods:

• Designed a novel system integrating EMG signal acquisition and electrical stimulation.
• Utilized an Altera Field Programmable Gate Array (FPGA) for real-time hybrid EMG signal processing.
• Employed power spectral density and cross-correlation for signal processing accuracy and delay evaluation.

Main Results:

• The developed system successfully acquired and processed EMG signals during electrical stimulation.
• The FPGA-based core efficiently processed real-time hybrid EMG signals, outputting isolated signals.
• Signal processing accuracy was validated using power spectral density, with cross-correlation revealing a processing delay of only 250 μs.

Conclusions:

• The developed device provides an efficient and accurate solution for real-time EMG signal acquisition during electrical stimulation.
• The FPGA-based approach enables high-speed processing of hybrid EMG signals, minimizing artifacts.
• This system offers a user-friendly and flexible platform for advanced EMG applications in research and clinical settings.