Gait classification method based on multi-sensor information fusion

Abstract

The invention relates to a gait classification method based on multi-sensor information fusion. The gait classification method includes the following steps that (1), plantar pressure information and ankle angle information in the walking process of multiple patients are collected; (2) according to the obtained plantar pressure information, gait stages of the patients are analyzed, the gait stages are divided into the stages of touching the ground with the feet and the stages of swinging the legs, and one gait cycle includes one stage of touching the ground with one foot and one stage of swinging the leg of the same foot of each patient; (3) a characteristic value of each gait cycle is set, so that gait characteristics of all the patients in the walking process are represented; (4), gait cluster analysis is performed on all the characteristic values of all the gait cycles of all the patients through a spectral clustering algorithm, so that the patients with the different gait characteristics are divided into different classifications. The patients are objectively classified, so that reference is provided for rehabilitation training and treatment of the patients, and a doctor can adopt different treatment modes and training intensities for the patients of the different classifications conveniently. The gait classification method can be widely used in the fields of gait analysis and medical rehabilitation.

Description

technical field [0001] The invention relates to a gait analysis method, in particular to a gait classification method based on multi-sensor information fusion (MSDF, Multi-sensor Data Fusion). Background technique [0002] The change of gait characteristic information reflects the change of human physiological function. In the process of rehabilitation treatment, obtaining accurate and credible gait characteristic information in time, and monitoring and evaluating gait characteristics for a long time has great significance for the diagnosis and treatment of some diseases. Important guiding significance, such as rehabilitation training for walking gait of stroke patients, gait correction training for patients with Parkinson's syndrome, rehabilitation guidance for patients with torn anterior cruciate ligament, etc. [0003] At present, in the field of medical clinical diagnosis, traditional gait analysis methods mainly rely on professional physicians to observe the patient's g...

AI Technical Summary

Problems solved by technology

However, due to the large subjective factors in this method, and the evaluation of gait feature information requires high accuracy, precision and objectivity, it will have a negative impact on the future diagnosis and rehabilitation of patients.

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