Gait feature extraction method based on weak foot COP features and fall risk discrimination system

Abstract

The invention relates to the field of gait and foot pressure data analysis, in particular to a gait feature extraction method based on weak foot COP features and a fall risk judgment system, and the system comprises a foot pressure signal preprocessing module, a weak foot judgment module, a feature extraction module and a fall risk judgment module. The foot pressure signal preprocessing module is used for segmenting, aligning and denoising input multi-channel pressure data of left and right feet and then extracting a single-foot COP time sequence; the weak foot judgment module judges the COP time sequence to obtain a weak foot COP sequence; a feature extraction module performs feature extraction on left and right foot COP sequences and weak foot COP sequences, extracts symmetry related features by combining the left and right foot COP sequences, and performs feature extraction on time sequence change and consistency for the weak foot COP sequence; and the falling risk judgment module performs risk judgment on the foot pressure data to distinguish high falling risk and low falling risk. According to the method, the falling risk can be accurately and effectively judged according to the plantar pressure signal, and the falling risk is prevented; and the medical burden is reduced.

Description

technical field [0001] The invention relates to the field of gait and foot pressure data analysis, in particular to a gait feature extraction method and a fall risk discrimination system based on weak foot COP (Center of pressure, center of pressure) features. Background technique [0002] Falls, as the most common cause of injury in the elderly, seriously endanger the physical and mental health of the elderly. Falling will not only cause fractures and sprains in the elderly, but in severe cases, the head and spine will be damaged, which is life-threatening. In addition to physical damage, it can also bring psychological shadows to the elderly; loss of confidence in the ability to walk safely may further lead to motor function decline, depression, feelings of helplessness and social isolation. In recent years, as the proportion of the elderly in the total population is increasing year by year, more elderly people are hospitalized for rehabilitation due to falls, which has b...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the problems existing in the prior art, the present invention provides a gait feature extraction method and a fall risk discrimination system based on weak foot COP features, by extracting and analyzing gait features from the single foot pressure data collected by the shoe system, and Real-time fall risk discrimination solves the problem that COP features are sensitive to spatial information, adding consideration of single-foot COP signal symmetry and timing consistency, and can quickly and accurately obtain risk discrimination results

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