Host: The Japan Society of Mechanical Engineers
Name : [in Japanese]
Date : March 08, 2021 - March 09, 2021
In order to easily measure load on lower limb joints while walking, the inertial force of body part is calculated from acceleration measured by nine wearable inertial sensors attached to each body part without using motion capture and force plate, and the lower limb joint moments during single stance phase are estimated. However, the lower limb joint moments cannot be estimated only by the inertial sensors since the body in double stance phase has a statically indeterminate structure. Therefore, the purpose is to use deep learning to estimate the lower limb joint moments during the double stance phase using only the inertial sensors, but learning is performed with the correct answer value using the motion capture and force plates. This study uses simple RNN, which is a type of deep learning. As a result of changing the learning order for each joint, it was possible to estimate the load on the lower limb joints moments with a certain degree of accuracy.
