Department of Orthopedic Surgery, Mayo Clinic, Rochester, MN, USA.
Program in Physical Therapy, Mayo Clinic School of Health Sciences, Mayo Clinic, Rochester, MN, USA; Department of Physical Medicine & Rehabilitation, Mayo Clinic, Rochester, MN, USA.
Clin Biomech (Bristol). 2023 Apr;104:105929. doi: 10.1016/j.clinbiomech.2023.105929. Epub 2023 Mar 3.
Despite widespread use of return to sport testing following anterior cruciate ligament reconstruction, studies suggest inadequacy in current testing criteria, such as limb symmetry index calculations, to determine athletes' readiness to return to play. Recurrence quantification analysis, an emerging non-linear data analysis tool, may reveal subtle neuromuscular differences between the injured and uninjured limb that are not captured by traditional testing. We hypothesized that isokinetic torque curve data of the injured limb would demonstrate lower determinism and entropy as compared to the uninjured limb.
102 patients (44 M, 58F, 10 ± 1 months post-anterior cruciate ligament reconstruction) underwent isokinetic quadriceps strength testing using a HumacNorm dynamometer. Patients completed maximum effort knee extension and flexion at 60°/sec. Data were post-processed with a MATLAB CRQA Graphical User Interface and determinism and entropy values were extracted. Paired-sample t-tests (α = 0.05) were used to compare data from the injured and uninjured limb.
Determinism and entropy values in the torque curves were lower in the injured limb than the uninjured limb (p < 0.001). Our findings indicate there is less predictability and complexity present in the torque signals of injured limbs.
Recurrence quantification analysis can be used to assess neuromuscular differences between limbs in patients who have undergone anterior cruciate ligament reconstruction. Our findings offer further evidence that there are changes to the neuromuscular system which persist following reconstruction. Further investigation is needed to establish thresholds of determinism and entropy values needed for safe return to sport and to evaluate the utility of recurrence quantification analysis as a return to sport criterion.
尽管在进行前交叉韧带重建后广泛应用了重返运动测试,但研究表明,目前的测试标准(例如肢体对称性指数计算)不足以确定运动员的复出准备情况。新兴的非线性数据分析工具——递归定量分析,可能会揭示受伤和未受伤肢体之间细微的神经肌肉差异,而这些差异是传统测试无法捕捉到的。我们假设与未受伤肢体相比,受伤肢体的等速扭矩曲线数据的确定性和熵值较低。
102 名患者(44 名男性,58 名女性,前交叉韧带重建后 10±1 个月)使用 HumacNorm 测功机进行等速股四头肌力量测试。患者以 60°/秒的速度进行最大努力的膝关节伸展和屈曲。数据使用 MATLAB CRQA 图形用户界面进行后处理,并提取确定性和熵值。使用配对样本 t 检验(α=0.05)比较受伤和未受伤肢体的数据。
受伤肢体的扭矩曲线中的确定性和熵值低于未受伤肢体(p<0.001)。我们的发现表明,受伤肢体的扭矩信号的可预测性和复杂性较低。
递归定量分析可用于评估前交叉韧带重建后患者肢体之间的神经肌肉差异。我们的发现进一步证明,重建后神经肌肉系统仍存在变化。需要进一步研究以确定用于安全复出的确定性和熵值阈值,并评估递归定量分析作为复出标准的效用。