TY - GEN
T1 - An approach to categorization analysis for human motion by Kinect and IMU
AU - Kim, Seonghye
AU - Nozaki, Takahiro
AU - Murakami, Toshiyuki
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/12/21
Y1 - 2016/12/21
N2 - The field of human motion analysis has researched with designing the rehabilitation robot system. In the present, there are many robot systems dealing with the human motion but they are heavy and hard to use simply at home. Moreover they especially have a particular purpose focused on the single human motion then the usability of these systems is low and fragmentary about a variety of motions. To classify the various motions, we propose the approach to categorization analysis for human motion by using information of the Kinect and IMUs. It is focused on the human motion which is classified into the walking, standing up and down, and falling down motion. The two COG points of the body from the sensing results are defined as the new indexes such as distance and incline, which are the indicator to classify the human motion. To verify the verification, the theoretical human model is designed and the experiment for the various human motions is carried out by using Kinect and IMU.
AB - The field of human motion analysis has researched with designing the rehabilitation robot system. In the present, there are many robot systems dealing with the human motion but they are heavy and hard to use simply at home. Moreover they especially have a particular purpose focused on the single human motion then the usability of these systems is low and fragmentary about a variety of motions. To classify the various motions, we propose the approach to categorization analysis for human motion by using information of the Kinect and IMUs. It is focused on the human motion which is classified into the walking, standing up and down, and falling down motion. The two COG points of the body from the sensing results are defined as the new indexes such as distance and incline, which are the indicator to classify the human motion. To verify the verification, the theoretical human model is designed and the experiment for the various human motions is carried out by using Kinect and IMU.
KW - Human motion
KW - Hybrid sensor application
KW - Motion detection
KW - Motion estimation
KW - Sensor system and application
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U2 - 10.1109/IECON.2016.7793391
DO - 10.1109/IECON.2016.7793391
M3 - Conference contribution
AN - SCOPUS:85010065598
T3 - IECON Proceedings (Industrial Electronics Conference)
SP - 6158
EP - 6162
BT - Proceedings of the IECON 2016 - 42nd Annual Conference of the Industrial Electronics Society
PB - IEEE Computer Society
T2 - 42nd Conference of the Industrial Electronics Society, IECON 2016
Y2 - 24 October 2016 through 27 October 2016
ER -