Publicação

ErgoReport: a holistic posture assessment framework based on inertial data and deep learning

Ver documento

Detalhes bibliográficos
Resumo:Awkward postures are a significant contributor to work-related musculoskeletal disorders (WRMSDs), which represent great social and economic burdens. Various posture assessment tools assess WRMSD risk but fall short in providing an elucidating risk breakdown to expedite the typical time-consuming ergonomic assessments. Quantifying, automating, but also complementing posture risk assessment become crucial. Thus, we developed a framework for a holistic posture assessment, able to, through inertial data, quantify the ergonomic risk and also qualitatively identify the posture leading to it, using Deep Learning. This innovatively enabled the generation of a report in a graphical user interface (GUI), where the ergonomic score is intuitively associated with the postures adopted, empowering workers to learn which are the riskiest postures, and helping ergonomists and managers to redesign critical work tasks. The continuous posture assessment also considered the previous postures' impact on joint stress through a kinematic wear model. As use case, thirteen subjects replicated harvesting and bricklaying, work tasks of the two activity sectors most affected by WRMSDs, agriculture and construction, and a posture assessment was conducted. Three ergonomists evaluated this report, considering it very useful in improving ergonomic assessments' effectiveness, expeditiousness, and ease of use, with the information easily understandable and reachable.
Autores principais:Martins, Diogo Renato Dias
Outros Autores:Cerqueira, Sara Maria Brito Araújo; Pombeiro, Ana; Ferreira da Silva, Alexandre; Rocha, Ana Maria A. C.; Santos, Cristina
Assunto:Deep learning Ergonomic risk assessment Inertial-based posture recognition Posture monitoring Work-related musculoskeletal disorders Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática Engenharia e Tecnologia::Engenharia Médica Saúde de qualidade Indústria, inovação e infraestruturas
Ano:2025
País:Portugal
Tipo de documento:artigo
Tipo de acesso:acesso aberto
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho

Registos relacionados

Registos relacionados