This study examined the validity, reliability and sensitivity of a new EMG spectral index in assessing peripheral muscle fatigue during dynamic contractions. Seven healthy adults (28.7±7 years, 180±10 cm, 78±12 kg, mean±SD) performed metronome guided unilateral knee extension exercise lifting 50% of their one repetition maximum (10 sets x 15 repetitions, 2 min rest between the sets). Knee extensor maximal voluntary contractions (MVC) were performed before and immediately after exercise. Torque (T, Technogym UK Ltd), knee angle (Biometrics system, Gwent, UK) and rectus femoris EMG (bipolar surface electrode, B&L Engineering, CA, USA) were recorded simultaneously throughout the trial (CED, Cambridge, UK). Median (F_med) frequency of EMG power spectrum and the ratio between EMG spectral moments of order -1 and 5 (FI_nsmk) were calculated for a segment from each repetition of each set. The middle of each segment was selected to coincide with the maximal knee extension angle. Spectral moments (M_k) represent the area under the spectral curve after multiplication with the frequency raised to the power of k (where k is the order of the moment) as the weighting function [1]. where M_k is a spectral moment of order k, PS(f) denotes the EMG power frequency spectrum as a function of frequency f, and f_min and f_max delineate the bandwidth of the signal. Peripheral muscle fatigue development was assessed by the normalised relative changes (Δ) of the spectral indices against the first repetition of the corresponding set. The normalized percentage change between pre- and post- exercise MVC was used to evaluate the change in muscle isometric strength. Data were analysed using two-way repeated measures ANOVA (set vs. repetition). The F_med (0.78, P<0.0001) and FI_nsmk (0.75, P<0.0001) intraclass correlation coefficients calculated from the first repetition of each set demonstrated fair-to-good reliability (one-way random effects single measure (1,1) model). The maximal ΔFI_nsmk observed was approximately 8-fold, while that of ΔF_med was only 32%. ΔF_med and ΔFI_nsmk changed significantly between repetitions (both P<0.0001) but no between sets or set vs repetition interactions were observed for either parameter. ΔFI_nsmk variability between subjects was significant (P<0.0001). Hierarchical cluster analysis (average linkage method utilising Eucledian distance as the interval measure of dissimilarity) revealed three distinct subgroups of subjects: high (ΔFI_nsmk>400%), medium (200%<ΔFI_nsmk<400%), and low (ΔFI_nsmk<200%) muscle fatigability (Fig. 1). Linear regression analysis of ΔF_med and ΔFI_nsmk established different course of fatigue development between clusters. Muscle functional characteristics were significantly different between clusters during- and post- exercise (ΔMVC, P=0.012 and ΔT, P=0.03; one-way ANOVA), thus supporting the functional validity of the grouping. The new spectral index is a valid and reliable tool for assessment of muscle fatigability during dynamic contractions, and is more sensitive than the traditionally used median frequency of the EMG power spectrum.