Abstract
Gait analysis is popular in many clinical and biomechanical applications, such as diagnosis of diabetic neuropathy, rehabilitation evaluation of stroke patients and performance measurement of sports training. With the rapid and in-depth development of flexible sensing technology, a large-area pressure-sensitive floor can be easily installed in many locations. Complex movement besides linear walking can be designed on large-area floors for gait analysis in clinical or sports research. To conduct those researches, as a basic step, a computational approach is necessary to track each footprint correctly during the movement process. A multi-stage methodology is proposed to solve two main subtasks in the tracking process: (1) the labeling of different footprints and (2) the detection of basic foot gestures in the movement process. The methodology consists of an initial clusters creating stage, a cluster labeling stage and an overlapped footprints separating process. Tai Chi Chuan, one of complex foot movements, was used as an example to evaluate the proposed approach. An overall accuracy of 99.07% for footprint labeling and 90.39% for basic foot gesture detecting were achieved by the method.
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