Lower limb action recognition method based on pressure and acceleration sensor

Abstract

The invention discloses a lower limb movement recognition method based on a pressure and acceleration sensor. The specific implementation steps of the method are as follows: firstly, the pressure sensor signal of the lower limb movement of the human body is collected in real time, and after preprocessing the pressure sensor signal, according to the pressure sensor data rising The edge and falling edge mark the start and end of the lower limb movement. When the rising edge of the pressure is detected, the three-axis acceleration signal of the acceleration sensor will be collected and stored. When the falling edge of the pressure is detected, the three-axis acceleration signal of the acceleration sensor will be collected. The three-axis signal of the acceleration sensor collected between the edge and the falling edge is called the acceleration signal segment. Then the frequency domain features and statistical features are extracted from the acceleration signal segment extracted in the previous step. After the features are extracted, the data dimensionality reduction is performed on the extracted features. Finally, the trained classifier is used to classify the feature data after dimension reduction, and the classification result of the action pattern is obtained.

Description

technical field

[0001] The invention relates to the technical field of body motion pattern recognition, in particular to a lower body motion recognition method based on pressure and acceleration sensors. Background technique

[0002] Using single or multiple sensors to recognize and classify human action patterns has attracted extensive attention from researchers all over the world in recent years. By effectively processing sensor signals, it is possible to determine which action generated the signal, and thus to make a judgment. The person's intention and state of the action. At present, the acceleration sensor has received the favor of many researchers because of its small size, low power consumption, and portability. Most of the research on human motion pattern recognition uses the acceleration sensor as the focus of research. Human motion pattern recognition based on the acceleration sensor In addition to being applied to intelligent human-computer interaction, it can a...

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