An Algorithm for Waist Circumference Measurement Based on Kalman Filter

Waist-circumference measurement is an important function of wearable intelligent devices, but the performance of traditional measurement of waist circumference in the case of equal space sampling is not good, and the accuracy is generally not high. This paper mainly introduces a waist circumference measurement algorithm based on Kalman filter for wearable devices. The data of equal-displacement sampling is converted into motion data at any time by data processing, and then waist circumference data is calculated and predicted by Kalman filter. From the perspective of effect, compared with the traditional method, the waist circumference measurement algorithm proposed in this paper effectively improves the measurement accuracy and resolution of the waist measurement device, generally increasing the measurement accuracy by more than 30%.