Nixon Ryan M, Vincent Kevin R, Pezzullo Lydia, Vincent Heather K
Department of Physical Medicine and Rehabilitation, College of Medicine, Gainesville, FL, 112730, USA.
The Orthopaedic Institute, Alachua, FL, USA.
Sci Rep. 2025 Aug 30;15(1):31964. doi: 10.1038/s41598-025-17773-w.
This three-part study investigated alternative pre-processing techniques to better understand the differences in patterns of ground reaction force (GRF) and load rate (LR) among runners with running-related injury (RRI). 534 runners were assessed on an instrumented treadmill with 3D kinematic data capture. Participants were classified as "injured" or "uninjured" and "rearfoot" (RF) or "non-rearfoot" (non-RF) strikers. The raw net GRF is normalized by time and then averaged across at least ten steps for the left and right foot; a double Gaussian characterizes the biphasic double-mass-spring model of running gait. Six parameters from the Gaussians were used to describe the relative differences and shape change based on injury condition. LRs were calculated using a central difference numerical derivative of the raw normalized net force data. 32% of runners reached peak negative LR (unloading) within the first 20% of stance. Injured RF strikers had 18% higher peak positive LR and 6% shorter time to peak than uninjured RF strikers (p < 0.05). Injured non-RF strikers showed peak negative LR 10% earlier in normalized stance, with a 10% shorter interval between positive and negative peaks (p < 0.05). The magnitude and timing of impact and active phases of GRF waveforms differed in runners with history of tibial stress fractures and current Achilles tendinopathy (p < 0.05). LR and LR timing are important in relation to specific RRI. These alternative pre-processing methods may help improve mechanistic understanding of GRF and LR and identify gait retraining foci for specific injury diagnoses in the future.
这项分为三个部分的研究调查了替代预处理技术,以更好地理解跑步相关损伤(RRI)的跑步者之间地面反作用力(GRF)和负荷率(LR)模式的差异。534名跑步者在配备3D运动数据采集的仪器化跑步机上进行了评估。参与者被分为“受伤”或“未受伤”以及“后足”(RF)或“非后足”(非RF)着地者。原始净GRF按时间进行归一化,然后对左右脚至少十个步幅进行平均;双高斯分布表征了跑步步态的双质量弹簧双相模型。使用来自高斯分布的六个参数来描述基于损伤状况的相对差异和形状变化。LR使用原始归一化净力数据的中心差分数值导数进行计算。32%的跑步者在站立的前20%内达到负向LR峰值(卸载)。受伤的RF着地者的正向LR峰值比未受伤的RF着地者高18%,达到峰值的时间短6%(p<0.05)。受伤的非RF着地者在归一化站立中负向LR峰值提前10%出现,正负峰值之间的间隔短10%(p<0.05)。有胫骨应力性骨折病史和当前跟腱病的跑步者,GRF波形的冲击和主动阶段的大小和时间不同(p<0.05)。LR和LR时间与特定的RRI相关。这些替代预处理方法可能有助于提高对GRF和LR的机制理解,并在未来为特定损伤诊断确定步态再训练重点。