Work

Surface Electromyography and Gait Features in Patients after Anterior Cruciate Ligament Reconstruction

Year: 2024
Type: article
Study design: Observational Study
Abstract: OBJECTIVE: An important reason for the poor recovery of anterior cruciate ligament (ACL) injuries is the poor recovery of muscle function. Therefore, we used surface electromyography (sEMG) and gait analysis to explore the muscle activation patterns and gait characteristics between lower limbs under different exercise states in patients, following anterior cruciate ligament reconstruction (ACLR). METHODS: Forty-one adults with unilateral ACL injuries in Binzhou Medical University Hospital from October 2022 to June 2023 were allocated to three groups according to the time after ACL reconstruction: group A (≤3 months, 16), group B (3 months-1 year, 13), and group C (>1 year, 12). Patients were tested by sEMG and gait, while straight leg raising (SLR), walking at normal speed, fast walking, and walking up and down the stairs. Two related sample tests were performed for the normalized root mean square (RMS) values and gait parameters. RESULTS: Muscle function changes varied in different training tasks. The RMS value of the involved side was more than the uninvolved side in biceps femoris and semitendinosus of group A (p < 0.010), and for the bilateral rectus femoris (RS), vastus medialis (VM), and vastus lateralis in group B, only the comparison of the RS was significant in group C during fast walking and going up and down the stairs. The ground impact (0.90 [0.63, 1.33] vs. 0.71 [0.43, 1.02], p = 0.035) of the uninvolved side was significantly decreased compared to those of the involved side in patients with ACLR when going down the stairs. CONCLUSION: Different muscles need to be focused on at different stages of the postoperative period. sEMG and gait analysis can guide the development of a rehabilitation program.
Language: English
Subfield: Surgery
Field: Medicine
Open Access status: gold
Estimated APC paid: $2,500
OpenAlex ID: W4403155834
FWCI: 2.276
Cites: 28
Cited by: 6
Related to: 10