Step Detection Algorithm For Accurate Distance Estimation Using Dynamic Step Length

In this paper, a new Smartphone sensor based algorithm is proposed to detect accurate distance estimation. The algorithm consists of two phases, the first phase is for detecting the peaks from the Smartphone accelerometer sensor. The other one is for detecting the step length which varies from step to step. The proposed algorithm is tested and implemented in real environment and it showed promising results. Unlike the conventional approaches, the error of the proposed algorithm is fixed and is not affected by the long distance. Keywords distance estimation, peaks, step length, accelerometer.Comment: this paper contains of 5 pages and 6 figure

Nonparametric Regression-based Step-length Estimation for Arm-swing Walking using a Smartphone

In this paper, we propose an adaptive step-estimation method to estimate the distance traveled for arm-swinging activities at three level-walking speeds, i.e., low, normal, and high speed. The proposed method is constructed based on a polynomial function of the pedestrian speed and variance of walking acceleration. We firstly apply a low-pass filter with 10 Hz cut-off frequency for acceleration data. Then, we analyze the acceleration data to find the number of steps in each sample. Finally, the traveled distance is calculated by summing all step lengths which are estimated by the proposed method during walking. Applying the proposed method, we can estimate the walking distance with an accuracy rate of 95.35% in a normal walking speed. The accuracy rates of low and high walking speeds are 94.63% and 94.97%, respectively. Furthermore, the proposed method outperforms conventional methods in terms of accuracy and standard deviation at low, normal, and high speeds