Is low-cost motion capture with artificial intelligence applicable for human working posture risk assessment during manual material handling? A pilot study.
Work
; 74(1): 283-293, 2023.
Article
en En
| MEDLINE
| ID: mdl-36245349
BACKGROUND: Assessing working posture risks is important for occupational safety and health. However, low-cost assessment techniques for human motion injuries in the logistics delivery industry have rarely been reported. OBJECTIVE: To propose a novel approach for posture risk assessment using low-cost motion capture with artificial intelligence. METHODS: A Kinect was adopted to obtain red-green-blue (RGB) and depth images of the subject with 24 postures, and the human joints were extracted using artificial intelligence. The images were registered to obtain the actual three-dimensional (3D) human joint angle. RESULTS: The root mean square error (RMSE) significantly decreased. Finally, two common methods for evaluating human working posture injuries-the Rapid Upper Limb Assessment and Ovako Working Posture Analysis System-were investigated. CONCLUSIONS: The outputs of the proposed method are consistent with those of the commercial ergonomic evaluation software.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Inteligencia Artificial
/
Enfermedades Profesionales
Tipo de estudio:
Etiology_studies
/
Health_economic_evaluation
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
Work
Asunto de la revista:
MEDICINA OCUPACIONAL
Año:
2023
Tipo del documento:
Article
País de afiliación:
China
Pais de publicación:
Países Bajos