passages: 2088
passages: document
passages: Distinct fast and slow processes contribute to the selection of preferred step frequency during human walking . Humans spontaneously select a step frequency that minimizes the energy expenditure of walking . This selection might be embedded within the neural circuits that generate gait so that the optimum is pre-programmed for a given walking speed . Or perhaps step frequency is directly optimized , based on sensed feedback of energy expenditure . Direct optimization is expected to be slow due to the compounded effect of delays and iteration , whereas a pre-programmed mechanism presumably allows for faster step frequency selection , albeit dependent on prior experience . To test for both pre-programmed selection and direct optimization , we applied perturbations to treadmill walking to elicit transient changes in step frequency . We found that human step frequency adjustments ( n = 7 ) occurred with two components , the first dominating the response ( 66 ± 10 % of total amplitude change ; mean ± SD ) and occurring quite quickly ( 1.44 ± 1.14 s to complete 95 % of total change ) . The other component was of smaller amplitude ( 35 ± 10 % of total change ) and took tens of seconds ( 27.56 ± 16.18 s for 95 % completion ) . The fast process appeared to be too fast for direct optimization and more indicative of a pre-programmed response . It also persisted even with unusual closed-loop perturbations that conflicted with prior experience and rendered the response energetically suboptimal . The slow process was more consistent with the timing expected for direct optimization . Our interpretation of these results is that humans may rely heavily on pre-programmed gaits to rapidly select their preferred step frequency and then gradually fine-tune that selection with direct optimization .
entities: 2089
entities: Intervention_Physical
entities: perturbations to treadmill walking
entities: 2090
entities: Outcome_Physical
entities: human step frequency adjustments
entities: 2091
entities: Participant_Condition
entities: human