Source avec lien : Ergonomics, (En ligne). 10.1080/00140139.2023.2221411
L’objectif est de développer un modèle d’évaluation informatisé pour une nouvelle évaluation posturale dynamique à l’aide de RULA. La présente étude propose un modèle d’estimation de la posture humaine dynamique en trois dimensions (3D) basé sur une caméra et utilisant « BlazePose » avec un ensemble de données de 50 000 images basées sur l’action.
The aim is to develop a computer-based assessment model for novel dynamic postural evaluation using RULA. The present study proposed a camera-based, three-dimensional (3D) dynamic human pose estimation model using ‘BlazePose’ with a data set of 50,000 action-level-based images. The model was investigated using the Deep Neural Network (DNN) and Transfer Learning (TL) approach. The model has been trained to evaluate the posture with high accuracy, precision, and recall for each output prediction class. The model can quickly analyse the ergonomics of dynamic posture online and offline with a promising accuracy of 94.12%. A novel dynamic postural estimator using blaze pose and transfer learning is proposed and assessed for accuracy. The model is subjected to a constant muscle loading factor and foot support score that could evaluate one person with good image clarity at a time.Practitioner summary: A detailed investigation of dynamic work postures is largely missing in the literature. Experimental analysis has been performed using transfer learning, BlazePose, and RULA action levels. An overall accuracy of 94.12% is achieved for dynamic postural assessment.