TY - GEN
T1 - Analyzing Mowing Behaviors on Sloping Land via Motion Capture Device
AU - Wu, Bo
AU - Wu, Yuan
AU - Aoki, Yoko
AU - Nishimura, Shoji
AU - Kashiwagi, Masayuki
N1 - Funding Information:
ACKNOWLEDGMENTS This work was supported by the 2019 Waseda University Advanced Research Center for Human Sciences, Young Group Research Project “C Pro.”
Publisher Copyright:
© 2020 IEEE.
PY - 2020/8
Y1 - 2020/8
N2 - As the aging and depopulation in Japan's rural areas continues to increase, many manual lawn mowing jobs have been handed to senior citizens. However, mowing with an incorrect posture may unduly burden the body, and even lead to a fall or slip. In this paper, we focus on the motions involved in lawn mowing, design and execute a set of experiments to collect data on the worker's body while mowing on a slope by using a motion capture device, and use regression analysis to identify the relationship between the angles of the subject's joints and the angle of the slope/inclined plane. The results of an analysis of 9,600 items of motion-related data show that all the angles considered, excluding angles of the subject's right elbow and right wrist, were related to the angle of the inclined plane. The findings of the work here can provide guidelines for preventing accidents in the design of mowing assistance systems and offers useful insights for training workers for mowing.
AB - As the aging and depopulation in Japan's rural areas continues to increase, many manual lawn mowing jobs have been handed to senior citizens. However, mowing with an incorrect posture may unduly burden the body, and even lead to a fall or slip. In this paper, we focus on the motions involved in lawn mowing, design and execute a set of experiments to collect data on the worker's body while mowing on a slope by using a motion capture device, and use regression analysis to identify the relationship between the angles of the subject's joints and the angle of the slope/inclined plane. The results of an analysis of 9,600 items of motion-related data show that all the angles considered, excluding angles of the subject's right elbow and right wrist, were related to the angle of the inclined plane. The findings of the work here can provide guidelines for preventing accidents in the design of mowing assistance systems and offers useful insights for training workers for mowing.
KW - motion capture
KW - mowing-related behavior
KW - preventing accident; elderly support
UR - http://www.scopus.com/inward/record.url?scp=85097647760&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85097647760&partnerID=8YFLogxK
U2 - 10.1109/DASC-PICom-CBDCom-CyberSciTech49142.2020.00078
DO - 10.1109/DASC-PICom-CBDCom-CyberSciTech49142.2020.00078
M3 - Conference contribution
AN - SCOPUS:85097647760
T3 - Proceedings - IEEE 18th International Conference on Dependable, Autonomic and Secure Computing, IEEE 18th International Conference on Pervasive Intelligence and Computing, IEEE 6th International Conference on Cloud and Big Data Computing and IEEE 5th Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2020
SP - 406
EP - 409
BT - Proceedings - IEEE 18th International Conference on Dependable, Autonomic and Secure Computing, IEEE 18th International Conference on Pervasive Intelligence and Computing, IEEE 6th International Conference on Cloud and Big Data Computing and IEEE 5th Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 18th IEEE International Conference on Dependable, Autonomic and Secure Computing, 18th IEEE International Conference on Pervasive Intelligence and Computing, 6th IEEE International Conference on Cloud and Big Data Computing and 5th IEEE Cyber Science and Technology Congress, DASC/PiCom/CBDCom/CyberSciTech 2020
Y2 - 17 August 2020 through 24 August 2020
ER -