Left and right foot dynamic recognition method based on plantar pressure distribution information

Abstract

The invention discloses a left and right foot dynamic recognition method based on plantar pressure distribution information. The method includes the steps of plantar pressure data filtering, plantar pressure data clustering, single-step footprint image processing and left and right foot dynamic recognizing. An improved type IMF filtering algorithm is adopted for the plantar pressure data filtering. A K-means clustering algorithm is adopted for the analysis on the plantar pressure data clustering. The single-step footprint image processing includes the substeps of footprint image bilinear interpolation amplification, median filtering, morphological processing and the like. The left and right foot dynamic recognizing is achieved by conducting judgment on the basis of the extreme value distribution situations of fitted footprint profile curves and footprint width curves. By means of the method, plantar pressure data can be processed and analyzed in real time, and gait feature parameters in the walking process are calculated according to the starting and stopping time of each step of a footprint sequence. The method is simple, the recognition speed is high, the recognition accuracy is high, high robustness is achieved, and the method can be applied and popularized in hospitals, rehabilitation organizations and colleges, universities and research institutions working on related gait research.

Description

technical field [0001] The invention relates to the fields of sensor technology, sports biomechanics, medical care and sanitation, and pattern recognition, and in particular to a dynamic recognition method for left and right feet based on plantar pressure distribution information. Background technique [0002] Most plantar diseases are related to changes in the normal pressure distribution on the soles of the feet, and the two usually affect each other. Studies have shown that dynamic plantar pressure distribution information can enable us to discover abnormal gait, judge the status of the disease, and evaluate the effect of rehabilitation treatment of the disease. At present, researchers apply the information of plantar pressure distribution to clubfoot, early prediction, diagnosis and evaluation of treatment effects of various types of foot diseases, such as diabetic foot ulcers. In addition, in rehabilitation medicine, plantar pressure distribution information can also g...

AI Technical Summary

Problems solved by technology

The combination of the large-area flexible array pressure sensor and the left and right foot recognition algorithm can effectively avoid the following situations: (1) the situation that the step length, pace speed, and step width cannot be calculated due to the limitations of the built-in sensor; (2) the situation caused by manual recognition (3) The situation where dynamic gait characteristic parameters cannot be solved due to static acquisition

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