들기 작업의 허리부하 평가 및 자세 추천을 위한 작업자 중심의 웹기반 전문가시스템 = A Web-Based Expert System to Evaluate Low Back Loading and Recommend Postures for Lifting Tasks

다국어 초록 (Multilingual Abstract)

Purpose Low back pain caused by lifting tasks accounts for the highest incidence of occupational diseases. This study aimed to analyze the effect of lifting tasks on low back pain and construct a web-based assessment system that can aid to prevent low back pain. Methods Lifting task-related factors (trunk angle, knee angle, stoop/squat lifting, trunk bending, foot position, lifting velocity, horizontal distance, and asymmetrical lifting) were investigated for their effect on the compressive force through theoretical, experimental, and biomechanical approaches. The compressive force was adjusted to reflect the influence of the load center of gravity. The information obtained from these analyses was used as the knowledge base for training the assessment system, termed as the “expert system.” Result The expert system provides the final compressive force and recommends lifting posture based on the values input or selected by the worker. The worker can obtain information about the low back loading level directly on the screen and can adjust the low back load by changing the posture according to the recommended lifting postures. Conclusion We designed a web-based expert system that can be self-operated by workers to measure low back loading and recommend lifting postures.
This system can help in overcoming the limitations of the existing low back loading measurement models and can be useful in small businesses that cannot hire experts, thereby helping in reducing direct and indirect costs related to musculoskeletal disorders, including low back pain.