Biomechanical Risk Assessment of Watermelon Harvesting Using AI-Based Motion Analysis

Abstract

Watermelon harvesting is a physically demanding task that places workers at high risk for developing work-related musculoskeletal disorders (MSDs). While previous studies have explored MSDs in the agricultural area, there is a notable research gap specifically addressing MSDs in watermelon harvesting. This study aims to address this gap by evaluating the physical demands of watermelon harvesting in a field condition. The primary objectives are: (1) to identify the regions of the body most susceptible to injury during watermelon harvesting, and (2) to analyze physiological and biomechanical changes in the body while performing watermelon lifting tasks. Ten workers performed tasks associated with watermelon harvesting in the field with a camera recording. Kinematic data were analyzed using an AI based software. Joint angles were analyzed to examine statistical changes, contributing to a better understanding of the risks associated with watermelon harvesting.