If the hole is wide but shallow, it’s easier to step down and up; if it’s narrow but deep, it’s better to jump over—people pick the option that uses less energy based on the hole’s shape.
Scientific Claim
The optimal locomotor strategy for crossing a hole obstacle shifts from 'step-down-and-up' to 'step-over' as the obstacle becomes shorter and deeper, and from 'step-over' to 'step-down-and-up' as it becomes longer and shallower, based on integrated mechanical energy cost.
Original Statement
“The energetically optimal traversal strategy was dependent on both obstacle length and obstacle depth... CoT was lower for the IN strategy than for the OVER strategy when the obstacle was long and shallow, and lower for the OVER strategy than the IN strategy when the obstacle was short and deep.”
Evidence Quality Assessment
Claim Status
appropriately stated
Study Design Support
Design supports claim
Appropriate Language Strength
definitive
Can make definitive causal claims
Assessment Explanation
This is a direct empirical observation from controlled manipulation of obstacle dimensions and quantification of mechanical cost, supported by polynomial regression models and visualized in figure 2b.
Gold Standard Evidence Needed
According to GRADE and EBM methodology, here is what ideal scientific evidence would look like to definitively prove or disprove this specific claim, ordered from strongest to weakest evidence.
Randomized Controlled TrialLevel 1aThat systematically varying obstacle geometry (length/depth) causes predictable shifts in strategy preference based on energy cost.
That systematically varying obstacle geometry (length/depth) causes predictable shifts in strategy preference based on energy cost.
What This Would Prove
That systematically varying obstacle geometry (length/depth) causes predictable shifts in strategy preference based on energy cost.
Ideal Study Design
A within-subject RCT with 50 healthy adults performing obstacle negotiation across 25 randomized obstacle geometries (0.1l–0.5l depth, 0.5l–1.1l length), with strategy choice recorded and compared to modeled CoTtot thresholds; primary outcome is the accuracy of strategy selection matching predicted optimal transition boundaries.
Limitation: Cannot determine if participants use heuristics instead of full energy calculation.
Prospective Cohort StudyLevel 2bThat individuals who more accurately predict the energy cost transition point across obstacle geometries show superior locomotor efficiency in real-world terrain.
That individuals who more accurately predict the energy cost transition point across obstacle geometries show superior locomotor efficiency in real-world terrain.
What This Would Prove
That individuals who more accurately predict the energy cost transition point across obstacle geometries show superior locomotor efficiency in real-world terrain.
Ideal Study Design
A 3-month cohort study of 80 adults navigating natural uneven terrain (e.g., hiking trails with variable steps/holes), using wearable sensors to record strategy choice and metabolic cost, correlating accuracy of geometric energy prediction with overall energy savings.
Limitation: Cannot control for environmental unpredictability or prior experience with similar terrain.
Evidence from Studies
Supporting (1)
Human locomotion over obstacles reveals real-time prediction of energy expenditure for optimized decision-making
People choose how to cross a hole based on which way uses the least energy, and they decide before they even get there — this study proves they pick 'step-over' for deep, narrow holes and 'step-down-and-up' for shallow, wide ones to save energy.