Dynamic–Static Perceptual Weight Reversal in 3D-Printed Climbing Holds: A Multi-Modal Biomechanical and Sensory Study

This study investigated how material stiffness and surface texture differentially influence climbers’ sensory perception and biomechanical force patterns under dynamic versus static conditions. Twelve climbing hold designs—three materials (PLA, PEBA, TPU) crossed with four surface patterns—were tested on 30 climbers across three skill levels using sensory evaluation, six-axis force measurement, and physical characterization. Surface pattern dominated perception during dynamic climbing, while material properties became primary during static grasping, constituting a dynamic–static perceptual weight reversal. A three-layer association model revealed progressively decreasing correlation strength from physical properties through biomechanical force to sensory perception. Machine learning identified two grip strategy types varying with skill level. Individual grip force varied 22.7-fold, exceeding material or pattern effects. Gender differences in pattern preference were also observed. These findings challenge the assumption of a single optimal hold design and support context-specific, individualized climbing hold engineering.

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Publication Details

Journal
Sensors
Published
2026-10-30
DOI
https://doi.org/10.3390/s26216863
Primary Topic
Motor Control and Adaptation
Type
article
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article

Dynamic–Static Perceptual Weight Reversal in 3D-Printed Climbing Holds: A Multi-Modal Biomechanical and Sensory Study

Pengcheng Gao, Junjie Wang, Hanyi Wang, Di Niu
Sensors
Motor Control and Adaptation
article

Dynamic–Static Perceptual Weight Reversal in 3D-Printed Climbing Holds: A Multi-Modal Biomechanical and Sensory Study

Pengcheng Gao, Junjie Wang, Hanyi Wang, Di Niu
article en

Abstract

This study investigated how material stiffness and surface texture differentially influence climbers’ sensory perception and biomechanical force patterns under dynamic versus static conditions. Twelve climbing hold designs—three materials (PLA, PEBA, TPU) crossed with four surface patterns—were tested on 30 climbers across three skill levels using sensory evaluation, six-axis force measurement, and physical characterization. Surface pattern dominated perception during dynamic climbing, while material properties became primary during static grasping, constituting a dynamic–static perceptual weight reversal. A three-layer association model revealed progressively decreasing correlation strength from physical properties through biomechanical force to sensory perception. Machine learning identified two grip strategy types varying with skill level. Individual grip force varied 22.7-fold, exceeding material or pattern effects. Gender differences in pattern preference were also observed. These findings challenge the assumption of a single optimal hold design and support context-specific, individualized climbing hold engineering.

SensorsVol. 26(21)
China University of Geosciences (CN), Wuhan University of Science and Technology (CN), Huazhong University of Science and Technology (CN)
Openalex Percentile: Top 14%
Motor Control and Adaptation
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