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A Novel Walking Detection and Step Counting Algorithm Using Unconstrained Smartphones.

Xiaomin Kang1, Baoqi Huang2, Guodong Qi3

  • 1College of Computer Science, Inner Mongolia University, Hohhot 010021, China. kangxiaomin@mail.imu.edu.cn.

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This study introduces a new algorithm for accurate walking detection and step counting using smartphones. The method works reliably even with arbitrary phone placement, improving upon existing techniques.

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smartphonestep countingwalking detection

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Area of Science:

  • Mobile computing
  • Signal processing
  • Human activity recognition

Background:

  • Walking detection and step counting are crucial for applications like positioning and behavior recognition.
  • Existing methods often require specific smartphone placement, limiting their practicality.

Purpose of the Study:

  • To propose a novel algorithm for simultaneous walking detection and step counting using unconstrained smartphones.
  • To achieve high accuracy irrespective of smartphone placement or alterations during use.

Main Methods:

  • Utilizing gyroscope data and Fast Fourier Transform (FFT) to extract frequency domain features from 3D angular velocities.
  • Recursively updating step frequency for real-time step count evaluation.
  • Conducting experiments with multiple subjects in diverse real-world walking scenarios.

Main Results:

  • Achieved 93.76% precision and 93.65% recall for walking detection, outperforming known methods.
  • Demonstrated a step counting accuracy of 95.74%, surpassing several established algorithms and commercial products.

Conclusions:

  • The proposed algorithm offers a robust and accurate solution for unconstrained walking detection and step counting.
  • This method has significant potential for enhancing mobile health and activity tracking applications.