Abstract
Recently, with the development of artificial intelligence technologies and the popularity of mobile devices, walking detection and step counting have gained much attention since they play an important role in the fields of equipment positioning, saving energy, behavior recognition, etc. In this paper, a novel algorithm is proposed to simultaneously detect walking motion and count steps through unconstrained smartphones in the sense that the smartphone placement is not only arbitrary but also alterable. On account of the periodicity of the walking motion and sensitivity of gyroscopes, the proposed algorithm extracts the frequency domain features from three-dimensional (3D) angular velocities of a smartphone through FFT (fast Fourier transform) and identifies whether its holder is walking or not irrespective of its placement. Furthermore, the corresponding step frequency is recursively updated to evaluate the step count in real time. Extensive experiments are conducted by involving eight subjects and different walking scenarios in a realistic environment. It is shown that the proposed method achieves the precision of and recall of for walking detection, and its overall performance is significantly better than other well-known methods. Moreover, the accuracy of step counting by the proposed method is , and is better than both of the several well-known counterparts and commercial products.
Highlights
With the rapid development of MEMS (Micro-Electro-Mechanical System) techniques and wireless communications, the smartphone as a research platform is attracting more and more attention in both academia and industries due to its merits in the following aspects: easy to carry, ubiquitous operations, rich sensing abilities, etc
This paper deals with walking detection and step counting in a practical scenario in which the placement of a smartphone can be arbitrary and alterable during walking, and proposes a novel algorithm by employing a gyroscope and extracting frequency domain features of the three-dimensional (3D) angular velocities returned by the gyroscope
In general, the frequency domain methods outperform the time domain method (i.e., STD_TH), indicating that the frequency domain features are more suitable for walking detection than the time domain features; the proposed method outperforms its copy using accelerations (i.e., fast Fourier transform (FFT)+ACC), confirming the advantage of gyroscope over accelerometer in walking detection, and both of them outperform the other frequency domain method (i.e., short-term Fourier transform (STFT)), verifying the advantage of the frequency domain features based on FFT
Summary
With the rapid development of MEMS (Micro-Electro-Mechanical System) techniques and wireless communications, the smartphone as a research platform is attracting more and more attention in both academia and industries due to its merits in the following aspects: easy to carry, ubiquitous operations, rich sensing abilities, etc. This paper deals with walking detection and step counting in a practical scenario in which the placement of a smartphone can be arbitrary and alterable during walking, and proposes a novel algorithm by employing a gyroscope and extracting frequency domain features of the three-dimensional (3D) angular velocities returned by the gyroscope. Fast Fourier transform (FFT) is adopted to quickly derive the spectrum of the Euclidean norm of 3D angular velocities; a thorough experimental analysis illustrates distinct characteristics in the spectrum irrespective of the smartphone placement, motivating us to design a thresholding technique to decide whether walking is being performed On these grounds, walking frequency can be estimated given the spectrum result, so that the steps can be indirectly counted by multiplying the walking frequency and its duration. Extensive experiments are conducted by evaluating the well-known counterparts and several popular commercial products
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