In aviation manufacturing industry,fatigue is a common problem among operators. In order to monitor operators's muscle fatigue, sEMG signal and self-perceived fatigue level are collected between novice and skilled operators. The collected data are further analyzed. It is found that a few sEMG features indicated directional changes with the increase of dynamic muscle fatigue. Spearman correlation analysis indicates that Borg ratings have strong correlations with RMS and FInsm5 slopes. Significant differences in the sEMG signals between novice and skilled operators are found. Combined with experimental results, a model is proposed for muscle fatigue assessment. Furthermore, design implications to guide fatigue monitoring devices are discussed for aviation manufacturing workers:design of wearable device, how to apply the proposed model to assess muscle fatigue, and the design of the feedback signal. At last, the design and application of a wearable device for human-computer interaction in this context is explored.