Abstract
Recently, the techniques for monitoring and recognizing human walking patterns have become one of the most important research topics, especially in health applications related to fitness and disease progression. This paper aims at combining machine learning techniques with Smartphone sensors readings (i.e. accelerometer sensor) in order to develop a smart model capable of classifying walking patterns into different categories (fast, normal, slow, very slow or very fast) along with variable of gender, male or female and sensor place, waist, hand or leg. In this paper, we use several machine learning algorithms including: Neural Network, KNN, Random forest, and Tree to train and test extracted data from Smartphone sensors. The results indicate that Smartphone sensor can be exploited in developing a reliable model for identifying the human walking patterns based on accelerometer readings. In addition, results show that Random forest is the best performing classifiers with an accuracy of (92.3%) and (91.8%) when applied on waist datasets for both males and females respectively.
Highlights
With the development of mobile technology over the past few years, mobile devices have become prevalent and nowadays equipped with different kinds of sensors, such as GPS, accelerometer, etc. [1]
All variables were coded to their corresponding numeric values as shown in Table I; for instance, values of 1, 0 and 2, which will be expressed as (102), mean that smartphone was placed at the waist of a male user walking normally
Afterwards, we find and compare the accuracy for each classifier in terms of smartphone replacement; hand; waist or leg
Summary
With the development of mobile technology over the past few years, mobile devices have become prevalent and nowadays equipped with different kinds of sensors, such as GPS, accelerometer, etc. [1]. With the development of mobile technology over the past few years, mobile devices have become prevalent and nowadays equipped with different kinds of sensors, such as GPS, accelerometer, etc. Contemporary Smartphones equipped with many sensors such as Accelerometer, Gyroscope, Magnetometer, and GPS. These sensors can determine the phone’s orientation if portrait or landscape, and whether the phone’ screen is upward or downward. The accelerometer sensor can detect how fast your phone is moving in any linear direction [2]
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