Accurate Human Positioning Based on Human Movement Characteristics
Date Issued
2009
Date
2009
Author(s)
Lin, Yu-Chi
Abstract
Location-Based Life-Reality (LBLR) realized on mobile device is proved to be a user-friendly man-machine interface (MMI). However, it heavily relies on the fact that the system must continuously get accurate position and attitude information. Inertia positioning of micro sensors can continuously provide LBLR mobile device with needed state information. However, it has the problem that its integrator accumulates the sensor errors and its accuracy dramatically decays with time.he purpose of the current study was developing the new indoor positioning technology which was founded on human mathematical model constructed with human movement characteristic during common in indoor movement. When the signal of external positioning system (EPS) is unavailable, such as people under overhang of a building or indoors, our new positioning technology which was utilized the combination of the developed human movement mathematical models and the inertial data can effectively position the human location. his study aimed to develop different movement of human movement mathematical model during common indoor movements, including level walking, stair ascent and descent, sit-to-stand and stand-to-sit, and to apply the wavelet transformation technology in reorganization and classification of all the movements. For the human mathematical model during level walking, stair ascent and descent movements, movement of turning would be also considered in the establishment of this positioning technology for more accurate human positioning.n the strength of the consideration of the positioning effects and practicability of our newly developed positioning technology, we added the map and the coordinate system in the mapping process for displaying the positioning result and the coordinates below the map shown in the monitor of the mobile positioning device. n order to test the practicability of this positioning technology, we put the inertial sensors on different body positions of human for confirming the positioning effects and the minimum requirements of this technique. Otherwise, six subjects were recruited to participate in different motion experiments for confirming the reproduction and validity of the new positioning technology. The results of different motion experiments in the current study showed that the positioning error during level walking was below 3%, the rate of success for classifying different indoor movements was greater than 75%, and the best sensor placements were Xphoid process and shank.
Subjects
IMUs
human model
movement classification
map
calibration
positioning
Type
thesis
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