Flexible filtering method of triaxial acceleration data for motion detection

Abstract

The invention discloses a flexible filtering method of triaxial acceleration data for motion detection. Different filtering modes are determined according to the current load value of the processor of an intelligent terminal. The length of each axial neighborhood data elongation annular buffer is determined according to the current sampling frequency of an acceleration sensing data acquisition unit. A corresponding axial filtering function is switched on or switched off according to an idle axial direction of a training template. Furthermore each axial neighborhood data annular buffer and each axial data buffer are set. Furthermore averaging filtering is performed on each axial data by means of each buffer and each filter. Furthermore when an external event is interrupted, the acceleration sensing data acquisition unit stops data acquisition or a triaxial acceleration sensor is cancelled for stopping data filtering. The flexible filtering method realizes effective filtering of a high-frequency noise in a low-frequency motion signal on the condition of relatively low system resource consumption in a motion detection process, and furthermore settles problems of incapability of effectively filtering noises in the motion signal and relatively high system resource consumption.

Description

technical field [0001] The invention belongs to the technical field of motion detection, and more particularly relates to a flexible filtering method for three-axis acceleration data used for motion detection. Background technique [0002] Gymnastics is a kind of micro-sports that is not limited by the venue. Because of its advantages of relieving fatigue, regulating emotions and exercising the body, people pay more and more attention to it. Work-time exercises can immediately unload the body's load, maintain a healthy body, and work efficiently. The traditional method is that office workers imitate the work-time exercise activities in pictures or videos, but they cannot know whether the posture is standard. If the posture is not standard, good exercise effects cannot be achieved. Based on the three-axis acceleration sensor in the smart device or smart phone worn on the human limbs, the three-axis acceleration sensor data can be used to monitor the corresponding human limb ...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the above defects or improvement needs of the prior art, the present invention provides a flexible filtering method for three-axis acceleration data used in motion detection. The current load value of the processor of the terminal device determines the different filtering methods that require different computing resources for the system. The length of the variable-length ring buffer for each axial neighborhood data is determined according to the current sampling frequency of the acceleration sensor data collector. According to the idle time of the training template Axial to switch the filter function of the corresponding axis, and use each buffer and filter to perform mean value filtering on the data of each axis, so as to realize the high-frequency motion signal in the low-frequency motion signal in the motion detection process under the condition of low system resource consumption Effective filtering of high-frequency noise, thus solving the technical problems in the prior art that the motion signal noise cannot be effectively filtered and the system resource consumption is high

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