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- W4306178654 abstract "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.To propose a novel approach for posture risk assessment using low-cost motion capture with artificial intelligence.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.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.The outputs of the proposed method are consistent with those of the commercial ergonomic evaluation software." @default.
- W4306178654 created "2022-10-14" @default.
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- W4306178654 date "2023-01-13" @default.
- W4306178654 modified "2023-09-26" @default.
- W4306178654 title "Is low-cost motion capture with artificial intelligence applicable for human working posture risk assessment during manual material handling? A pilot study" @default.
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- W4306178654 doi "https://doi.org/10.3233/wor-205204" @default.
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