Gait Feature Extraction Method and Fall Risk Discrimination System Based on Cop Features of Weak Foot

Abstract

The invention relates to the field of gait and foot pressure data analysis, and is a gait feature extraction method and a fall risk discrimination system based on weak foot COP features. The system includes 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 divides and aligns the input multi-channel pressure data of the left and right feet, and extracts the single-foot COP time series after denoising; the weak foot judgment module judges the COP time series to obtain the weak foot COP Sequence; the feature extraction module extracts the features of the left and right feet and the COP sequence of the weak foot respectively, extracts the symmetry-related features combined with the COP sequence of the left and right feet, and extracts the features of the timing change and consistency of the COP sequence of the weak foot; the fall risk judgment module Risk discrimination is performed on the foot pressure data to distinguish between high risk of falling and low risk of falling. The invention can accurately and effectively judge the risk of falling according to the plantar pressure signal, prevent it before it happens, and reduce medical burden.

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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