Nonparametric Regression-based Step-length Estimation for Arm-swing Walking using a Smartphone
Keywords:Walking distance estimation, Pedestrian Dead Reckoning (PDR), nonparametric regression, arm-swinging
AbstractIn 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.
Alvarez, D.; Gonzalez, R. C.; Lopez, A.; Alvarez, J. C. (2006); Comparison of step length estimators from wearable accelerometer devices, IEEE Engineering in Medicine and Biology Society, 5964-5967, 2006.
Capurso, N.; Song, T.; Cheng, W.; Yu, J.; Cheng, X. (2016); An Android-based mechanism for energy efficient localization depending on indoor/outdoor context, IEEE Internet of Things Journal, 4(2), 299-307, 2016.
Chen, K.Y.; Bassett, D.R. (2005); The technology of accelerometry-based activity monitors: current and future, Medicine and science in sports and exercise, 37(11), S490-S500, 2005.
Cleveland, W. S.; Loader, C. (1996); Smoothing by local regression: Principles and methods, Physica-Verlag HD, 10-49, 1996.
Cleveland, W. S.; Devlin, S. J. (1988); Locally weighted regression: An approach to regression analysis by local fitting, J. Am. Stat. Assoc., 83(403), 596-610, 1988. https://doi.org/10.1080/01621459.1988.10478639
Donoso, Y.; Montoya, G. A.; Solano, F. (2015); An Energy-Efficient and Routing Approach for Position Estimation using Kalman Filter Techniques in Mobile WSNs, International Journal of Computers Communications & Control, 10(4), 500-507, 2015. https://doi.org/10.15837/ijccc.2015.4.1990
Foxlin, E. (2005); Pedestrian tracking with shoe-mounted inertial sensors, IEEE Comput. Graph. Appl, 25, 38-46, 2005. https://doi.org/10.1109/MCG.2005.140
Ho, N.-H.; Truong, P. H.; Jeong, G.-M. (2016); Step-detection and adaptive step-length estimation for pedestrian dead-reckoning at various walking speeds using a smartphone, Sensors, 16(9), 14-23, 2016.
Jekabsons, G. (2016); Locally weighted polynomials toolbox for Matlab/Octave, 2016.
Lall, U.; Moon, Y.-I.; Kwon, H.-H.; Bosworth, K. (2006); Locally weighted polynomial regression: Parameter choice and application to forecasts of the Great Salt Lake, Water Resour. Res., 42, W05422, 2006.
Liu, Y.; Chen, Y.; Shi, L.; Tian, Z.; Zhou, M.; Li, L. (2015); Accelerometer based joint step detection and adaptive step length estimation algorithm using handheld devices, Journal of Communications, 10(7), 520-525, 2015.
Palais, B.; Palais, R.; Rodi, S. (2009); A disorienting look at Euler's theorem on the axis of a rotation, American Mathematical Monthly, 116(10), 892-909, 2009. https://doi.org/10.4169/000298909X477014
Skog, I.; Handel, P.; Nilsson, J.-O.; Rantakokko, J. (2010); Zero-velocity detection An algorithm evaluation, IEEE Trans. Biomed. Eng, 57, 2657-2665, 2010. https://doi.org/10.1109/TBME.2010.2060723
Suh, Y. S.; Nemati, E.; Sarrafzadeh, M. (2016); Kalman-filter-based walking distance estimation for a smart-watch, IEEE First Conference on Connected Health: Applications, Systems and Engineering Technologies, 150-156, 2016.
Susi, M.; Renaudin, V.; Lachapelle, G. (2013); Motion mode recognition and step detection algorithms for mobile phone users, Sensors, 13, 1539-1562, 2013. https://doi.org/10.3390/s130201539
Tian, Q.; Salcic, Z.; Wang, K.; Pan, Y. (2016); A multi-mode dead reckoning system for pedestrian tracking using smartphones, IEEE Sensors Journal, 16(7), 2079-2093, 2016. https://doi.org/10.1109/JSEN.2015.2510364
Truong, P. H.; Lee, J.; Kwon, A. R.; Jeong, G.-M. (2016); Stride counting in human walking and walking distance estimation using insole sensors, Sensors, 16(6), 8-23, 2016.
Weinberg, H. (2002); Using the ADXL202 in pedometer and personal navigation applications, Analog Devices, 2002.
ONLINE OPEN ACCES: Acces to full text of each article and each issue are allowed for free in respect of Attribution-NonCommercial 4.0 International (CC BY-NC 4.0.
You are free to:
-Share: copy and redistribute the material in any medium or format;
-Adapt: remix, transform, and build upon the material.
The licensor cannot revoke these freedoms as long as you follow the license terms.
DISCLAIMER: The author(s) of each article appearing in International Journal of Computers Communications & Control is/are solely responsible for the content thereof; the publication of an article shall not constitute or be deemed to constitute any representation by the Editors or Agora University Press that the data presented therein are original, correct or sufficient to support the conclusions reached or that the experiment design or methodology is adequate.