Motion Capture Technologies for Ergonomics: A Systematic Literature Review

S Salisu, NIR Ruhaiyem, TAE Eisa, M Nasser, F Saeed… - Diagnostics, 2023 - mdpi.com
Muscular skeletal disorder is a difficult challenge faced by the working population. Motion
capture (MoCap) is used for recording the movement of people for clinical, ergonomic and …

Automatic classification and segmentation of teeth on 3D dental model using hierarchical deep learning networks

S Tian, N Dai, B Zhang, F Yuan, Q Yu, X Cheng - Ieee Access, 2019 - ieeexplore.ieee.org
To solve the problem of low efficiency, the complexity of the interactive operation, and the
high degree of manual intervention in existing methods, we propose a novel approach …

Soft computing applications in the field of human factors and ergonomics: A review of the past decade of research

E Çakıt, W Karwowski - Applied Ergonomics, 2024 - Elsevier
The main objectives of this study were to 1) review the literature on the applications of soft
computing concepts to the field of human factors and ergonomics (HFE) between 2013 and …

A hybrid data-driven model for geotechnical reliability analysis

W Liu, A Li, W Fang, PED Love, T Hartmann… - Reliability Engineering & …, 2023 - Elsevier
Tunnel boring machines are widely used to construct underground rail networks in urban
areas. However, ground settlement due to complex geological conditions is an ever-present …

Machine learning for rapid estimation of lower extremity muscle and joint loading during activities of daily living

WS Burton II, CA Myers, PJ Rullkoetter - Journal of Biomechanics, 2021 - Elsevier
Joint contact and muscle forces estimated with musculoskeletal modeling techniques offer
useful metrics describing movement quality that benefit multiple research and clinical …

Geotechnical risk modeling using an explainable transfer learning model incorporating physical guidance

F Liu, W Liu, A Li, JCP Cheng - Engineering Applications of Artificial …, 2024 - Elsevier
While Artificial intelligence (AI) has been successfully applied in assessing geotechnical
risk, such methods heavily rely on data quality to achieve satisfactory performance, and their …

Simple method integrating OpenPose and RGB-D camera for identifying 3D body landmark locations in various postures

PL Liu, CC Chang - International Journal of Industrial Ergonomics, 2022 - Elsevier
Ergonomic assessments of posture are indispensable for reducing the risk of physical
discomfort in the workplace. However, it is challenging to measure postural data in field …

Applying deep neural networks and inertial measurement unit in recognizing irregular walking differences in the real world

B Hu, S Li, Y Chen, R Kavi, S Coppola - Applied Ergonomics, 2021 - Elsevier
Falling injuries pose serious health risks to people of all ages, and knowing the extent of
exposure to irregular surfaces will increase the ability to measure fall risk. Current gait …

Assessment of a novel deep learning-based marker-less motion capture system for gait study

S Vafadar, W Skalli, A Bonnet-Lebrun, A Assi, L Gajny - Gait & Posture, 2022 - Elsevier
Background Marker-less systems based on digital video cameras and deep learning for gait
analysis could have a deep impact in clinical routine. A recently developed system has …

Improving data acquisition speed and accuracy in sport using neural networks

C Papic, RH Sanders, R Naemi, M Elipot… - Journal of Sports …, 2021 - Taylor & Francis
Video analysis is used in sport to derive kinematic variables of interest but often relies on
time-consuming tracking operations. The purpose of this study was to determine speed …