Running gait retraining via peak tibial shock biofeedback has been previously shown to reduce impact loading and mitigate running-related symptoms. In previous research, peak tibial shock is typically measured and trained for one limb at a single constant training speed during all training sessions. The goal of this study was to determine how runners transfer learning in the trained limb to the untrained limb at different unconstrained speeds.
Thirteen runners (3 females, age = 41.1 ± 6.9 yr, running experience = 6.8 ± 4.4 yr, weekly running distance = 30.7 ± 22.2 km) underwent running gait biofeedback retraining via continuous tibial acceleration measured at the right distal tibia. Before and after the training, participants were asked to run at their self-selected constrained training speeds (2.8 ± 0.2 m·s−1) and at 110% and 90% of the training speed. Pretraining and posttraining peak tibial shock values for each limb were compared.
Participants reduced peak tibial shock in the trained limb by 35% to 37% (P < 0.05, Cohen’s d = 0.78–0.85), and in the untrained limb by 20% to 23% (P < 0.05, Cohen’s d = 0.51–0.71) across the three testing speeds. The reduction was not significantly different between the trained and untrained limbs (P = 0.31–0.79, Cohen’s d = 0.18–0.45). Similarly, there was no difference in peak tibial shock reduction among the three running speeds (P = 0.48–0.61, Cohen’s d = 0.06–0.45).
Participants demonstrated transfer learning effects evidenced by concomitant reduced peak tibial shock in the untrained limb, and the learning effects were retrained when running at a 10% variance of the training speed.
1Gait & Motion Analysis Laboratory, Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, HONG KONG SAR
2Department of Biomedical Engineering, Boston University, Boston, MA
3School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, CHINA
Address for correspondence: Janet Hanwen Zhang, M.B.B.S., ST004, Gait & Motion Analysis Laboratory, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong SAR; E-mail: Janet.HW.Zhang@connect.polyu.hk.
Submitted for publication September 2018.
Accepted for publication April 2019.
Online date: April 10, 2019