DEVELOPMENT OF A WORKERS’ POSTURE ESTIMATION SYSTEM BASED ON THE OWAS METHOD USING HELMET-MOUNTED TERMINALS

Abstract

 Improving working posture through quantitative evaluation is crucial because deterioration of working posture can cause occupational injuries including musculoskeletal disorders. Mechanical motion capture systems have been used in previous research on construction workers’ posture evaluation, but the deployment of them in practice could increase the project cost. Considering this concern, this paper proposes a method for estimating workers’ postures using Long Short-Term Memory (LSTM) and helmet-mounted terminals, which have been applied to construction sites. In the verification experiment, we confirmed that the proposed method was able to estimate the posture of a rebar worker with a large physical load by using the Ovako Working Posture Analyzing System (OWAS) method with a recall rate of over 80 %. This method can be used to quantify working posture and utilized in safety management at construction sites.