Manual editing significantly improves the accuracy of motor unit recruitment threshold and discharge rate assessment from synthetic high-density surface electromyogramsMurks, Nina (Avtor) Škarabot, Jakob (Avtor) Kramberger, Matej (Avtor) Sedej, Gašper (Avtor) Valenčič, Tamara (Avtor) Connelly, Christopher D. (Avtor) Thomason, Haydn (Avtor) Divjak, Matjaž (Avtor) Holobar, Aleš (Avtor) high-density surface electromyographymotor unitsoleusbiceps brachiirecruitment thresholddischarge rateThis study examined the influence of manual editing on the accuracy of motor unit (MU) metrics derived from high-density surface EMG. Seven operators with varying levels of experience manually edited synthetic datasets from the Soleus and Biceps Brachii. We then calculated recruitment threshold (ReTh), derecruitment threshold (DeTh), discharge rate (DR), recruitment discharge rate (ReDR), and derecruitment discharge rate (DeDR) before and after editing. The effects of operator’s experience, contraction level, initial pulse-to-noise ratio (PNR), signal-to-noise ratio (SNR), muscle type, and editing status were analyzed. Manual editing significantly improved accuracy only for ReTh and DR, whereas with other metrics, it only had a minor, insignificant effect. Higher initial PNR consistently reduced errors across all metrics. Contraction level strongly influenced all metrics, whereas muscle type and SNR had minimal impact—SNR was significant only for DeTh, and muscle type only for ReTh. Operator’s experience did not significantly affect any metric. Overall, these results indicate that manual editing is critical for reliable estimation of ReTh and DR, but less essential for DeDR, particularly when initial PNR is high.20252026-02-23 14:47:28Znanstveno delo97207sl