Author Identifiers

Ryan T Schroeder

ORCID: 0000-0002-0613-3440

Date of Award


Degree Type


Degree Name

Doctor of Philosophy


School of Medical and Health Sciences

First Advisor

Dr James Croft

Second Advisor

Dr John E. A. Bertram


Empirical evidence suggests that parameters of human gait (e.g. step frequency, step length) tend to minimize energy expenditure. However, it is unclear if individuals can adapt to dynamic environments in real time, i.e. continuously optimize energy expenditure, and to what extent. Two coupled oscillator systems were used to test the learned interactions of individuals within dynamic environments: (1) experienced farmworkers carrying oscillating loads on a flexible bamboo pole and (2) individuals walking on a treadmill while strapped to a mechatronics oscillator system providing periodic forces to the body. Reductionist trajectory optimization models predicted energy-minimizing gait interactions within the coupled oscillator systems and were compared to experimental data assessed with linear mixed models. On average, pole carriers significantly adjusted step frequency by 3.3% (0.067 Hz, p=0.014) to accommodate the bamboo pole – consistent with model predictions of energy savings. Novice subjects entrained (i.e. synchronized) their step frequency with machine oscillations up to ±10% of preferred step frequency and at amplitudes as low as 5% body weight (or ~33 N). Still, some subjects rarely entrained at all, and many exhibited transient entrainment, i.e. they drifted in and out of step frequencies matching the machine oscillations. Overall, subject entrainment was more robust and consistent with lower frequencies and higher amplitudes (20-30% of body weight). Although no systematic difference was found between the metabolic consumption of subjects during and not during entrainment, the net mechanical work done on subjects by the force oscillations had a strong effect on metabolic output (p