Analysis on Falling Risk of Elderly Workers when Mowing on a Slope via Motion Capture

Due to the aging of rural population, in Japan's terraced field areas, many elderly people have to do the mowing works of paddy levees manually. However, it takes the high risk of falling when mowing on slops, and many accidents are caused by the unstable postures. The analysis of their body motion becomes necessary. Based on our previous study, the personal factors could be important on affecting the mowing behaviors. Therefore, in this paper, we focus more on the mowing workers' personal factors (such as age and physique) and try to analyze the effect on their falling risk via a high precision motion capture device. A set of experiments was conducted in September 2020, and four new mowing workers over 60 years old were invited to participate in the experiments. Their joints angles data and related personal factor data were used to analyze the factors that have the greatest influence on body stability during slop mowing. The results of stepwise regression showed that the mowing workers' age and physique have significant effects on the stability of their body motion. The results of this study can clarify the factors that prevent accidents in the fall detection systems and offer useful insights for the training of new mowing workers.