Improving localization and measurements of M-waves using high-density surface electromyography

Surface electromyography (sEMG) is useful for studying muscle function and controlling prosthetics, but cross talk from nearby muscles often limits its effectiveness. High-density surface EMG (HD-sEMG) improves spatial resolution, allowing for the isolation of M-waves in the densely packed forearm muscles. This study assessed HD-sEMG for localizing M-waves and evaluated the impact of spatial filters on cross talk reduction. We administered peripheral nerve stimulation to activate forearm muscles in five participants. We analyzed cross talk by correlating the shape of M-waves between electrodes and used ultrasound to confirm muscle identity and location. At low-stimulation intensities, we successfully isolated M-waves with minimal cross talk without spatial filtering. Higher recruitment levels produced significant cross talk, which was reduced by applying bipolar or tripolar spatial filters. M-waves from the monopolar HD-sEMG montage showed high correlations between electrodes (r = 0.97 transversely; r = 0.95 longitudinally), while bipolar and tripolar montages showed lower correlations (bipolar: r = 0.41 transversely; r = 0.19 longitudinally; tripolar: r = 0.17 transversely; r = 0.01 longitudinally). The tripolar filter significantly reduced cross talk (51.10% amplitude decay one electrode away) compared with no filter (10.32% amplitude decay one electrode away), effectively reducing cross talk to negligible levels at distances ≥2.55 cm. Ultrasound was crucial for distinguishing true activation from artifacts caused by converging signals along muscle boundaries. Spatially filtered HD-sEMG accurately detects and isolates M-waves in the forearm, and ultrasound imaging is useful for verifying the location and identity of the muscles underlying the HD-sEMG grids.NEW & NOTEWORTHY This study introduces an innovative approach to enhancing evoked potential measurements using high-density surface electromyography (HD-sEMG). The precision and localization of evoked potentials are significantly improved by spatial filters and ultrasound imaging, offering a novel method for better assessing motor pathway integrity. These advancements could lead to more accurate tools for detecting and treating neurological deficits, making it a significant contribution to neurophysiological research.