This study aimed to utilize the nonnegative matrix factorization (NNMF) algorithm for muscle synergy analysis, extracting synergy structures and muscle weightings and mining biomarkers reflecting changes in muscle fatigue from these synergy structures. A leg press exercise to induce fatigue was performed by 11 participants. Surface electromyography (sEMG) data from seven muscles, electrocardiography (ECG) data, Borg CR-10 scale scores, and the z-axis acceleration of the weight block were simultaneously collected. Three indices were derived from the synergy structures: activation phase difference, coactivation area, and coactivation time. The indicators were further validated for single-leg landing. Differences in heart rate (HR) and heart rate variability (HRV) were observed across different fatigue levels, with varying degrees of disparity. The median frequency (MDF) exhibited a consistent decline in the primary working muscle groups. Significant differences were noted in activation phase difference, coactivation area, and coactivation time before and after fatigue onset. Moreover, a significant correlation was found between the activation phase difference and the coactivation area with fatigue intensity. The further application of single-leg landing demonstrated the effectiveness of the coactivation area. These indices can serve as biomarkers reflecting simultaneous alterations in the central nervous system and muscle activity post-exertion.