Sports state judgment method and foot wear

Abstract

A method for judging an exercise state and a foot wear, comprising the following steps: S10: collecting the pressure amplitudes of the forefoot and the rear soles in a period T, and obtaining effective step counting steps according to the pressure amplitudes, which are respectively defined as D1 and D3 , the average value of the effective step pressure amplitude, defined as M1 and M3, respectively, and the average value of the duration of the effective step pressure amplitude, defined as t1 and t3, respectively. S20: Comparing D1, D3, M1, M3, t1, and t3 with a plurality of different preset values ​​to determine and obtain a motion state. The above-mentioned motion state judgment method is less likely to be interfered by other irrelevant actions, and the judgment accuracy is high. The complexity of the algorithm adopted by the above motion state judging method is also relatively low. In addition, by introducing the characteristics of the acceleration amplitude, the maximum value of the absolute value of the angle amplitude, and the maximum value of the absolute value of the angular velocity amplitude, the motion state can be judged more accurately.

Description

technical field [0001] The invention relates to the technical field of motion state judgment, in particular to a motion state judgment method and a foot wear. Background technique [0002] With the rise and development of smart wearable devices, developers of smart wearable devices are constantly developing new functions of smart wearable devices in order to improve their competitiveness among similar products. Among them, implanting the user's motion status judgment function on smart wearable devices has become a new function for smart wearable devices to improve product competitiveness. [0003] At present, the existing methods for judging the user's motion state generally judge various motion states by extracting the characteristics of the acceleration curve of the user's movement. For example, if the acceleration of the user's movement is greater than a preset threshold, the user's exercise state is determined as a non-stationary state, and if the user's movement accele...

AI Technical Summary

Problems solved by technology

[0004] However, a single acceleration feature is susceptible to interference from various other irrelevant actions, and the accuracy of motion state judgment is low. Even if the SVM support vector machine algorithm in the complex machine learning field is used, it is still difficult to achieve high judgment accuracy.

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