I-Spin live, an open-source software based on blind-source separation for real-time decoding of motor unit activity...

Area of Science:

• Neuroscience
• Biomedical Engineering
• Signal Processing

Background:

• Understanding neural control of movement is crucial for neuroscience.
• Non-invasive decoding of spinal motor neuron activity is possible via electromyographic (EMG) signal decomposition.
• Real-time EMG decomposition is essential for advanced neuro-feedback and brain-computer interfaces.

Purpose of the Study:

• To introduce an open-source software for real-time decoding of motor neuron firing activity from multichannel EMG signals.
• To provide a validated framework for researchers studying movement control at the motor neuron level.
• To enable real-time visual feedback of motor neuron activity for experimental paradigms.

Main Methods:

• Developed and implemented an open-source software utilizing a blind-source separation approach for EMG signal processing.
• Optimized separation vectors (motor unit filters) from baseline contractions and applied them in real-time.
• Validated the software using synthetic EMG signals and experimental data from lower limb muscles (gastrocnemius, vastus, tibialis anterior) using surface and intramuscular electrodes.

Main Results:

• The software successfully performs real-time decoding of motor unit firing activities from EMG signals.
• Validation with synthetic and real-world EMG data demonstrated the software's capability across various contraction patterns and intensities.
• Assessed the impact of muscle type and contraction intensity variations on the accuracy of real-time decomposition.

Conclusions:

• The developed open-source software offers a practical tool for neuroscientists to investigate movement control.
• Enables real-time feedback on spinal cord circuit output, facilitating novel experimental designs.
• Advances the field of non-invasive motor neuron activity decoding for research and potential clinical applications.