Proceedings Article | 20 April 2016
KEYWORDS: Gait analysis, Mobile robots, Biomimetics, Buildings, Dementia, Consciousness, Robotic systems, Biosensing, Data acquisition, Sensors, Measurement devices, Motion measurement, Environmental sensing, Calibration, 3D acquisition, Digital filtering
The needs for monitoring systems to be used in houses are getting stronger because of the increase of the single
household population due to the low birth rate and longevity. Among others, gait parameters are under the spotlight to be
examined as the relations with several diseases have been reported. It is known that the gait parameters obtained at a
walk test are different from those obtained under the daily life. Thus, the system which can measure the gait parameters
in the real living environment is needed. Generally, gait abilities are evaluated by a measurement test, such as Timed Up
and Go test and 6-minute walking test. However, these methods need measurers, so the accuracy depends on them and
the lack of objectivity is pointed out. Although, a precise motion capture system is used for more objective measurement,
it is hard to be used in daily measurement, because the subjects have to put the markers on their body. To solve this
problem, marker less sensors, such as Kinect, are developed and used for gait information acquisition. When they are
attached to a mobile robot, there is no limitation of distance. However, they still have challenges of calibration for gait
parameters, and the important gait parameters to be acquired are not well examined. Therefore, in this study, we extract
the important parameters for gait analysis, which have correlations with diseases and age differences, and suggest the
gait parameters extraction from depth data by Kinect v2 which is mounted on a mobile robot aiming at applying to the
living environment.
