Artificial neural network for studying human performance - Bataineh, Mohammad
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The vast majority of products and processes in industry and academia require human interaction. Thus, digital human models (DHMs) are becoming critical for improved designs, injury prevention, and a better understanding of human behavior. Although many capabilities in the DHM field continue to mature, there are still many opportunities for improvement, especially with respect to posture- and motion-prediction. Thus, this work investigates the use of artificial neural network (ANN) for improving predictive capabilities and for better understanding how and why human behave the way they do.

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Produktbeschreibung
The vast majority of products and processes in industry and academia require human interaction. Thus, digital human models (DHMs) are becoming critical for improved designs, injury prevention, and a better understanding of human behavior. Although many capabilities in the DHM field continue to mature, there are still many opportunities for improvement, especially with respect to posture- and motion-prediction. Thus, this work investigates the use of artificial neural network (ANN) for improving predictive capabilities and for better understanding how and why human behave the way they do.
Autorenporträt
Mohammad Bataineh is a graduate researcher in the Biomedical Engineering department at The University of Iowa and works in virtual soldier research (VSR) with Dr. Marler. His research studies focus on studying human performance prediction using artificial neural networks, posture and motion predictions, decision engines, and biomechanics.