Surface electromyography (sEMG) signals of spasticity patients can be problematic due to involuntary spikes and the poor signal quality. Also, the length of sEMG signals can be very short. In order to solve these problems, a stretch reflex onset (SRO) detection method based on modified sample entropy is proposed: Firstly, sEMG signals are framed by a fixedlength sliding window and the sample entropy of each frame is calculated. Afterwards, adaptive threshold is set to determine the SRO. The results show that the modified sample entropy achieves improved performance in SRO detection compared with the standard sample entropy, and shows better robustness in processing shorter time data series and against spurious background spikes. The recognition accuracy rate reaches 8906% using modified sample entropy but only reaches 4818% when using standard sample entropy. The findings from this study show that the proposed method can provide insight as to the mechanisms underlying the passive resistance.