People can look ahead and decide how to step over a hole without feeling it first—they use what they see to guess which way will use less energy.
Scientific Claim
Visual information alone is sufficient for humans to predict and select the energetically optimal locomotor strategy before encountering an obstacle, without requiring real-time proprioceptive or metabolic feedback during the maneuver.
Original Statement
“Vision-based remote sensing was sufficient to select the strategy associated with the lowest prospective energy cost in advance of obstacle encounter, demonstrating the capacity for energetic optimization... in the absence of online proprioceptive or chemosensory feedback mechanisms.”
Evidence Quality Assessment
Claim Status
overstated
Study Design Support
Design supports claim
Appropriate Language Strength
association
Can only show association/correlation
Assessment Explanation
The study infers visual sufficiency from the absence of feedback during trials, but does not manipulate or measure visual input directly (e.g., by obscuring vision). The claim 'was sufficient' implies causation without experimental control.
More Accurate Statement
“Visual information is associated with the selection of the energetically optimal locomotor strategy before obstacle encounter, suggesting it may be sufficient for prospective energy cost prediction in the absence of online proprioceptive feedback.”
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 blocking visual input during approach directly impairs the ability to select the optimal energy-minimizing strategy.
That blocking visual input during approach directly impairs the ability to select the optimal energy-minimizing strategy.
What This Would Prove
That blocking visual input during approach directly impairs the ability to select the optimal energy-minimizing strategy.
Ideal Study Design
A within-subject RCT with 40 healthy young adults performing obstacle negotiation under three conditions: full vision, blurred vision (simulating low acuity), and complete darkness during approach (with auditory cues only); primary outcome is deviation from optimal strategy selection based on modeled CoTtot.
Limitation: Cannot isolate whether visual or cognitive processing is impaired under degraded conditions.
Prospective Cohort StudyLevel 2bThat individuals with visual impairments show reduced accuracy in selecting energetically optimal obstacle strategies compared to sighted peers.
That individuals with visual impairments show reduced accuracy in selecting energetically optimal obstacle strategies compared to sighted peers.
What This Would Prove
That individuals with visual impairments show reduced accuracy in selecting energetically optimal obstacle strategies compared to sighted peers.
Ideal Study Design
A prospective cohort comparing 50 individuals with congenital visual impairment (e.g., retinitis pigmentosa) and 50 age-matched controls performing real-world obstacle navigation tasks, measuring strategy selection accuracy against modeled energy cost predictions.
Limitation: Cannot control for compensatory strategies developed over time in visually impaired individuals.
Cross-Sectional StudyLevel 3That neural activation patterns during visual anticipation of obstacles correlate with subsequent energy-minimizing strategy selection.
That neural activation patterns during visual anticipation of obstacles correlate with subsequent energy-minimizing strategy selection.
What This Would Prove
That neural activation patterns during visual anticipation of obstacles correlate with subsequent energy-minimizing strategy selection.
Ideal Study Design
A cross-sectional fMRI/EEG study of 30 healthy adults viewing images of obstacles (varying depth/length) while brain activity is recorded, followed by physical obstacle negotiation; correlation between visual processing regions and strategy choice accuracy is measured.
Limitation: Cannot establish whether neural activity drives choice or reflects post-hoc justification.
Evidence from Studies
Supporting (1)
Human locomotion over obstacles reveals real-time prediction of energy expenditure for optimized decision-making
People looked at obstacles ahead and picked the easiest way to cross them without feeling or sensing their body during the move—just by seeing. Their choices saved the most energy, proving vision alone is enough to plan the best move.