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Development of an Integrated Virtual Reality System with Wearable Sensors for Ergonomic Evaluation of Human–Robot Cooperative Workplaces

This work proposes a novel virtual reality system which makes use of wearable sensors for testing and validation of cooperative workplaces from the ergonomic point of view. The main objective is to show, in real time, the ergonomic evaluation based on a muscular activity analysis within the immersiv...

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Detalles Bibliográficos
Autores principales: Caporaso, Teodorico, Grazioso, Stanislao, Di Gironimo, Giuseppe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8955201/
https://www.ncbi.nlm.nih.gov/pubmed/35336584
http://dx.doi.org/10.3390/s22062413
Descripción
Sumario:This work proposes a novel virtual reality system which makes use of wearable sensors for testing and validation of cooperative workplaces from the ergonomic point of view. The main objective is to show, in real time, the ergonomic evaluation based on a muscular activity analysis within the immersive virtual environment. The system comprises the following key elements: a robotic simulator for modeling the robot and the working environment; virtual reality devices for human immersion and interaction within the simulated environment; five surface electromyographic sensors; and one uniaxial accelerometer for measuring the human ergonomic status. The methodology comprises the following steps: firstly, the virtual environment is constructed with an associated immersive tutorial for the worker; secondly, an ergonomic toolbox is developed for muscular analysis. This analysis involves multiple ergonomic outputs: root mean square for each muscle, a global electromyographic score, and a synthetic index. They are all visualized in the immersive environment during the execution of the task. To test this methodology, experimental trials are conducted on a real use case in a human–robot cooperative workplace typical of the automotive industry. The results showed that the methodology can effectively be applied in the analysis of human–robot interaction, to endow the workers with self–awareness with respect to their physical conditions.