Artificial intelligence-based classification of motor unit action potentials in real-world needle EMG recordings

CONCLUSIONS: We developed a two-step ANN that classifies rest, muscle contraction and artifacts from real-world n-EMG recordings with very high accuracy. MUAP duration classification had moderate accuracy.SIGNIFICANCE: This is the first study to show that an ANN can classify MUAPs in real-world n-EMG recordings highlighting the potential for AI assisted MUAP classification as a clinical tool.PMID:37976609 | DOI:10.1016/j.clinph.2023.10.008

Source: Clinical Neurophysiology - November 17, 2023 Category: Neurology Authors: Deborah Hubers Wouter Potters Olivier Paalvast Sterre de Jonge Brian Doelkahar Martijn Tannemaat Luuk Wieske Camiel Verhamme Source Type: research