Field Measure to Estimate Vertical and Leg Stiffness
Marshall, Margaret E
Background: Achilles tendinopathy is a common injury in male athletes, especially those frequently involved in sports that require hopping. Athletes with Achilles tendinopathy jump with reduced vertical and leg stiffness. High levels of vertical stiffness are thought to be related to greater jumping and running economy (Maquirriain, 2012). Vertical stiffness (Kvert), defined as the body’s resistance to vertical displacement upon addition of ground reaction force, and leg stiffness (Kleg), defined as the leg’s resistance to change in length upon addition of internal or external forces, are readily calculated in laboratory settings (Dalleau et al., 2004). However, these techniques require an expensive 3D motion capture system and force plate. A surrogate measurement for calculating vertical stiffness using just a contact mat to quantify flight and stance times while hopping has been developed (Dalleau et al., 2004). We sought to determine if vertical stiffness and leg stiffness during hopping could be accurately predicted using high speed 2D video and open source software. We hypothesized stiffness measurements calculated from 2D video during single leg hopping would be correlated (r>0.80) with error rates within 10% of values obtained via the gold standard. Methods: Thirteen healthy males (21.8 yrs + 2.6) who regularly participated (≥3x/week) in activities that involve running and jumping completed a series of hopping trials. In a counterbalanced order, paced hopping trials consisting of 14 consecutive single-leg hops (132 Hz) and self-paced hopping trials to failure on each leg were collected. Kinematic data were sampled with a 10 camera 3D motion capture system (200Hz, Qualysis, Gothenburg, SWE) and a 2D high speed camera (100 Hz, Basler, Austin, TX, USA), while ground reaction forces were sampled via force plate (1000 Hz, Bertec, Columbus, OH, USA). Right leg data were extracted from the paced hopping trial, and the beginning and end of the hopping to failure trial (total samples: 117 hops). The gold standards were calculated using 3D motion capture, a force plate and custom written LabVIEW software. The surrogates were calculated using 2D video and Kinovea (kinovea.org) open source software. Data were analyzed via Pearson’s correlation and 95% limits of agreement (95% LOA). Results: Kvert calculated via 2D video was highly correlated (p<0.001, r=0.90) with a minimal 95% LOA of -2.1 kN·m-1 and maximal 95% LOA of +2.2 kN·m-1 compared with the gold standard. Kleg calculated via 2D video was highly correlated (p<0.001, r=0.81) with a minimal 95% LOA of -7.5 kN· m-1 and maximal 95% LOA of +0.9 kN·m-1 compared with the gold standard. While2D estimates of the Kvert and Kleg gold standards were highly proportional, absolute values exceeded 10% error rates (13.4% and 36.2%, respectively). Discussion: Calculation of vertical and leg stiffness using 2D video yielded acceptable estimates compared with the gold standard. These methods will enable clinicians to estimate vertical and leg stiffness in the field. Potential applications include providing in the field feedback on vertical stiffness to enhance jumping performance and identify athletes with low leg stiffness who are at-risk for Achilles tendinopathy. These methods can be incorporated in mobile phone applications for widespread implementation. Future research will apply these methods to running or other dynamic tasks.
Marshall, Margaret E. (May 2018). Field Measure to Estimate Vertical and Leg Stiffness (Honors Thesis, East Carolina University). Retrieved from the Scholarship. (http://hdl.handle.net/10342/6863.)
Marshall, Margaret E. Field Measure to Estimate Vertical and Leg Stiffness. Honors Thesis. East Carolina University, May 2018. The Scholarship. http://hdl.handle.net/10342/6863. March 04, 2021.
Marshall, Margaret E, “Field Measure to Estimate Vertical and Leg Stiffness” (Honors Thesis., East Carolina University, May 2018).
Marshall, Margaret E. Field Measure to Estimate Vertical and Leg Stiffness [Honors Thesis]. Greenville, NC: East Carolina University; May 2018.
East Carolina University