Method for multi-source information self-adaption step number detection based on MEMS inertial measurement unit

Abstract

The invention discloses a method for multi-source information self-adaption step number detection based on an MEMS inertial measurement unit. According to the method, the low-cost MEMS inertial measurement unit is adopted to serve as a core component. The inertial measurement unit comprises a triaxial accelerometer and a three-axis gyroscope. First the inertial measurement unit is fixed to the foot under the conditions that users' normal walking is not affected, an upper computer is utilized to perform initial calibration on the measurement unit; the upper computer is utilized to collect acceleration and angular speed signals output by the measurement unit in the user's walking process, and performing low-pass filtering processing on the collected signals; gaining self-adaption thresholds for the filtered signals; and finally taking the self-adaption thresholds as conditions for step number detection to detect the step number. The pedestrian's step number is detected based on the low-cost MEMS inertial measurement unit, and the method is suitable for the field of personal health data monitoring and pedestrian navigation systems based on the MEMS inertial measurement unit.

Description

technical field [0001] The invention relates to a MEMS inertial measurement unit-based multi-source information self-adaptive step number detection method, which can be applied in the field of high-precision detection of personal health data corresponding to user's gait characteristics and pedestrian navigation system. Background technique [0002] With the continuous improvement of people's living standards and increasing attention to personal health, the demand for health, sports and medical markets has increased significantly. Wearable devices based on MEMS inertial sensors have entered people's daily life from concept. Sense, identification, connection and cloud services and other technologies are comprehensively embedded in people's eyes, rings, watches, wristbands, clothing, shoes and socks and other daily wear devices to realize the expansion of users' five senses, life housekeeper, social entertainment, health monitoring and other functions. [0003] Conventionally,...

AI Technical Summary

Problems solved by technology

However, due to the low precision of the device itself and the large influence of noise on the current step count detection method based on MEMS inertial devices, it is impossible to accurately detect the user's step count simply by relying on one data source.

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