The present study tries to decrease the risk of work-related musculoskeletal disorders for industry workers by proposing a generic algorithm that recommends an optimal ergonomic posture for accomplishing tasks in an industrial environment. In the case of a dangerous ergonomic pose, the optimization algorithm starts by heuristically changing it to a more ergonomic one. Each recommended posture's feasibility is tested with an inverse kinematic method that can predict the worker's behavior for accomplishing a task. This iterative optimization procedure continues until the optimal ergonomic pose for the worker is achieved. The algorithm's validity is tested in thirteen cases, people with different gender (50 percent male, 50 percent female) aged between 20 and 35, and different height and body morphologies. According to studies, there is a connection between musculoskeletal disorders and the wrong posture for accomplishing tasks in industries. We suggest an optimization algorithm that can indicate the worker the optimal ergonomic pose by considering task constraints in real-time.

本研究通过提出一种通用算法，为在工业环境中完成任务推荐最佳的人体工程学姿势，试图为工业工人降低与工作相关的肌肉骨骼疾病的风险。在危险的人体工学姿势的情况下，优化算法从试探性地将其更改为更符合人体工程学的姿势开始。每个推荐姿势的可行性均通过反向运动学方法进行测试，该方法可以预测工人完成任务的行为。此迭代优化过程将继续进行，直到实现工人的最佳人体工程学姿势为止。在13个案例中测试了该算法的有效性，这些案例的性别不同（男性50％，女性50％）年龄在20至35岁之间，身高和身体形态也不同。根据研究，肌肉骨骼疾病和完成行业任务的错误姿势之间存在联系。我们建议一种优化算法，该算法可以通过实时考虑任务约束来指示工人最佳的人体工学姿势。