Detection, quantification and analysis of muscle fatigue is crucial in occupational/rehabilitation and sporting settings. Sports organizations such as Australian Institute of Sports (AIS) currently monitor fatigue by a battery of tests including invasive techniques that require taking blood samples and/or muscle biopsies, the latter of which is highly invasive, painful, time consuming and expensive. SEMG is non-invasive monitoring of the muscle activation and is an indication of localized muscle fatigue based on the observed shift of the power spectral density of the SEMG. But the success of SEMG based techniques is currently limited to isometric contraction and is not acceptable to the human movement community. This paper proposes and tests a simple signal processing technique to identify the onset of muscle fatigue during cyclic activities of muscles such as VL and VM during cycling. Based on experiments conducted with 7 participants, using power output as a measure of fatigue, the technique is able to identify the muscle fatigue with 98% significance.