Mariscal Aguilar, CristinaNavallas Irujo, JavierMalanda Trigueros, ArmandoRecalde Villamayor, SilviaRodríguez Falces, Javier2025-04-282025-02-20Mariscal, C., Navallas, J., Malanda, A., Recalde-Villamayor, S., Rodriguez-Falces, J. (2025). EMG filling analysis, a new method for the assessment of recruitment of motor units with needle EMG. Neurophysiologie Clinique, 55(4), 1-8. https://doi.org/10.1016/j.neucli.2025.103059.0987-705310.1016/j.neucli.2025.103059https://academica-e.unavarra.es/handle/2454/54030Objectives: The progression of recruitment of motor unit potentials (MUPs) during increasing voluntary contraction can provide important information about the motor units (MUs) innervating a muscle. Here, we described a method to quantitate the recruitment level of the intramuscular electromyographic (iEMG) signal during an increasing force level. Methods: Concentric needle EMG signals were recorded from the tibialis anterior of healthy subjects as force was gradually increased from 0 to maximum force. The iEMG filling process was analyzed by measuring the EMG filling factor (FF), calculated from the mean rectified iEMG and the root mean square iEMG. Results: (1) The iEMG activity at low contraction forces was “discrete” (FF<0.3) for all participants. (2) The iEMG activity at maximal effort was “full” (FF>0.5) for 83 % of the participants, whereas it was “incompletely-reduced” (0.3<FF< 0.5) for 17 % of the participants. (3) The FF increased rapidly for forces up to 20 % MVC, and then levelled off for higher forces: thus, the FF curve had a typical exponential shape. Conclusions: The iEMG filling method can be considered of general applicability since the FF increased over a wide range in all healthy participants. Significance: The EMG filling analysis may have potential to detect scenarios of MU loss and remodelling in neurogenic and motor neuron diseases.application/pdfeng© 2025 The Authors. This is an open access article under the CC BY license.Intramuscular EMGFilling factorEMG fillingInterference patternConcentric needleProbability Density Function (PDF)info:eu-repo/semantics/article2025-04-28info:eu-repo/semantics/openAccess