RESUMO
Objective By comparing the fatigue strength of type A and type B locking compression plates (LCP) in distal femoral plate, a theoretical evaluation method was provided for type selection of bone plate when testing its bending strength and fatigue performance. Methods Through bending strength performance test and fatigue performance test on bone plates with different types, combined with ANSYS Workbench, the finite element analysis on total deformation, von Mises stress and fatigue service life of bone plates were conducted. Results The fatigue strength of type A plate was 30.7% higher than that of type B plate, the stress of type A plate was lower than that of type B plate, and the minimum fatigue service life of type A plate was 17% higher than that of type B plate. Conclusions The fatigue performance of type A plate is better than that of type B plate, so the failure possibility of type A plate was lower than that of type B plate.The results provide references for assisting selection of different bone plates when testing the performance of two newly developed bone plates.
RESUMO
At present, fatigue state monitoring of upper limb movement generally relies solely on surface electromyographic signal (sEMG) to identify and classify fatigue, resulting in unstable results and certain limitations. This paper introduces the sEMG signal recognition and motion capture technology into the fatigue state monitoring process and proposes a fatigue analysis method combining an improved EMG fatigue threshold algorithm and biomechanical analysis. In this study, the right upper limb load elbow flexion test was used to simultaneously collect the biceps brachii sEMG signal and upper limb motion capture data, and at the same time the Borg Fatigue Subjective and Self-awareness Scale were used to record the fatigue feelings of the subjects. Then, the fatigue analysis method combining the EMG fatigue threshold algorithm and the biomechanical analysis was combined with four single types: mean power frequency (MPF), spectral moments ratio (SMR), fuzzy approximate entropy (fApEn) and Lempel-Ziv complexity (LZC). The test results of the evaluation index fatigue evaluation method were compared. The test results show that the method in this paper has a recognition rate of 98.6% for the overall fatigue state and 97%, 100%, and 99% for the three states of ease, transition and fatigue, which are more advantageous than other methods. The research results of this paper prove that the method in this paper can effectively prevent secondary injury caused by overtraining during upper limb exercises, and is of great significance for fatigue monitoring.