Automated Musculoskeletal Disorders Assessment Using OWAS and Kinect
Authors: Te-Hsiu Suna, Rong-He Linb, Mei-Lin Liub, Fang-Chih Tienb, Yi-Tsong Panc
Abstract: Workers musculoskeletal occupational injury is closely related to worker's job status and posture. Short-term or long-term excessive exercise and poor posture may cause temporary or permanent musculoskeletal hazards, affect workers physical health. OWAS is a comomly used evaluation tool for working postures disorders assessment. It requires an ergonomics expert to evaluate through the musculoskeletal disorders risk table. Using OWAS evaluation system not only can provide injury prevention but also can calculate various influence of injury. However, this evaluation requires an expert to monitor an operator for a long period of time, which is tedious and high cost. This objective of this paper is to build an automated musculoskeletal disorders assessment system using the Microsoft Kinect with the OWAS system scuh that the related working postures disorders can be easily explored. The proposed system uses Kinect skeleton tracking system to collect worker’s skeleton information including head, hands, wrists, elbows, shoulders, trunk, hips, knees and foot (20 knots). By means of a self-developed algorithm, the system can automatically record, analyze, and assesse the joint positions and angles between joints such that the posture of a worker can be identified based on OWAS coding system. The proposed system was implemented using C# under Window 7 platform with Microsoft Kinect SDK. A set of experiments was conducted to verify and validate the Kinect skeleton tracking system and self-developed algorithms. The experimental results show that the proposed system effectively recorded and estimated the posture of workers such that manpower and resources are saved and the potential of job hazard can be explored.
Keywords: Musculoskeletal Disorders, Kinect, 3D Ergonomic, OWAS
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