Work Recognition and Movement Trajectory Acquisition Using a Multi-Sensing Wearable Device

Musculoskeletal diseases such as low back pain may cause physical disabilities and make it difficult to continue working. From this point of view, logging of workers' conditions in the working environment is an important issue. So far, limited information acquisition such as smart watches has been realized, but comprehensive information has not been realized with a single device. Therefore, in this study, we estimated the wearer's state using a device called THINKLET, which can acquire image information and inertial information at the same time. By acquiring the pose of the hand from the image information, we were able to estimate the work. More detailed information can be obtained by calculating the position at the same time. By integrating image information with inertial information, it becomes possible to measure the position and posture of the wearer in the working environment. By complementing each other's sensor information, it is possible to obtain robust and accurate self-location. In this research, we developed these basic technologies and evaluated their performance.