Hong Kong Polytechnic University and Beijing Institute of Fashion Technology researchers used a dynamic 3dMDbody system to capture dynamic breast motion during running, informing high-support sports bra design.
These findings advance the understanding of cutaneous mechanics in sports science and offer empirical guidelines for optimizing compression garment design, particularly for running-related compression legging applications.
The experiment aimed to compare breast motion during different activities (running, jumping rope, high knee skipping) at different intensities.
This study demonstrates the inadequacy with which radiographic assessments evaluate shoulder height asymmetry and highlights the use of 3D surface topography measurements.
This study investigates whether surface topography measurements of body volume difference and torso volume difference between maximum inhale and exhale correlate to values determined on pulmonary function tests.
Tomorrow’s digital ‘human’ creation will be based on AI learning from authentic real-world data of people recorded physically in action with the utmost 3D fidelity.
3dMD acquires dynamic 3D surface data during motion including soft tissues of the breasts to examine the complex movements.
Imperial College London builds Design2Cloth (2024), a 3D garment generation model, with 3dMD’s real-world 2,010-subject dataset.
RAESTAC incorporates a 3D printed arm generated from a 3dMD digital scan which is inserted into an inflated lower arm pressure garment assembly (pressure bladder and restraint).
To develop sports bras that effectively limiting breast movement while minimize stress on the breast tissues, it is crucial to gain a comprehensive understanding of the breast movement and deformation patterns.