Step Length Estimation and Activity Detection in a PDR System Based on a Fuzzy Model with Inertial Sensors

  • Mariana Natalia Ibarra-Bonilla
  • Ponciano Jorge Escamilla-Ambrosio
  • Juan Manuel Ramirez-Cortes
  • Jose Rangel-Magdaleno
  • Pilar Gomez-Gil
Part of the Studies in Computational Intelligence book series (SCI, volume 547)


This chapter presents an approach on pedestrian dead reckoning (PDR) which incorporates activity classification over a fuzzy inference system (FIS) for step length estimation. In the proposed algorithm, the pedestrian is equipped with an inertial measurement unit attached to the waist, which provides three-axis accelerometer and gyroscope signals. The main goal is to integrate the activity classification and step-length estimation algorithms into a PDR system. In order to improve the step-length estimation, several types of activities are classified using a multi-layer perceptron (MLP) neural network with feature extraction based on statistical parameters from wavelet decomposition. This work focuses on classifying activities that a pedestrian performs routinely in his daily life, such as walking, walking fast, jogging and running. The step-length is dynamically estimated using a multiple-input–single-output (MISO) fuzzy inference system. Results provide an average classification rate of 87.49 % with an accuracy on step-length estimation about 92.57 % in average.



The first author acknowledges the financial support from the Mexican National Council for Science and Technology (CONACYT), scholarship No. 237756.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Mariana Natalia Ibarra-Bonilla
    • 1
  • Ponciano Jorge Escamilla-Ambrosio
    • 2
  • Juan Manuel Ramirez-Cortes
    • 1
  • Jose Rangel-Magdaleno
    • 1
  • Pilar Gomez-Gil
    • 3
  1. 1.Department of ElectronicsInstituto Nacional de Astrofísica, Óptica y ElectrónicaTonantzintlaMéxico
  2. 2.Centro de Investigacion en ComputacionInstituto Politécnico NacionalMexico CityMexico
  3. 3.Computer Science DepartmentInstituto Nacional de Astrofísica, Óptica y ElectrónicaTonantzintlaMéxico

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