Harih / Plesec Advances in Digital Human Modeling III
Erscheinungsjahr 2026
ISBN: 978-3-032-30159-8
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
Proceedings of the 10th International Digital Human Modeling Symposium, DHM 2026, July 1-3, 2026, Maribor, Slovenia
E-Book, Englisch, 432 Seiten
Reihe: Engineering (R0)
ISBN: 978-3-032-30159-8
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark
This book presents the latest advancements in digital human modeling, with a specialized focus on the integration of ergonomics, biomechanics, and human-centered engineering. It explores a wide array of cutting-edge technologies, including wearable sensors, machine vision, collaborative systems, and industrial robotics, alongside the evolving role of digital human twins and mixed-reality environments. Beyond technical modeling, the book investigates anthropometry, cognitive simulation, and advanced computational techniques. The included chapters report on both fundamental theoretical research and applied experimental studies, showcasing practical implementations in healthcare, automotive design, transportation safety, and assistive technologies. Based on the 10th International Digital Human Modeling Symposium (DHM 2026), held July 1–3, 2026, in Maribor, Slovenia, this book serves as a definitive reference for researchers and professionals. It highlights the state-of-the-art in digital manufacturing and human factors, offering a comprehensive overview of how digital human modeling is shaping a safer, more efficient, and human-centric future.
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
Effect of Ligament Loss on Scaphotrapeziotrapezoid (STT) Arthrodesis: A Finite Element Study.- Ground Reaction Force Prediction in Industrial Context: a Comparison between AnyBody and the OpenSim-based Tool OpenGRF.- Predicting zero-shear seat pan angle using a musculo-skeletal human model.- Feasibility Study on the Use of Current Large Language Model-Based Reasoning on Image-Derived Postures for Automated Physical Workload Assessment.- Prediction of Shoulder and Elbow Motion in Tai Chi Push-Hands Using Surface Electromyography.
