Estimation of Gait Conditions Using Acceleration and Angular Velocity Sensors

Abstract

The worldwide epidemic of the Corona Virus Disease 2019 is forcing many people to stay indoors, indirectly causing more people to gain weight. As a result, people's awareness of the movement grew. The most popular form of simple exercise is walking, and many people use wearable devices to record their movements. Existing wearable devices do not take into account the wearer's walking speed or the road condition, resulting in poor calorie counting accuracy. In this study, we use acceleration and angular rate sensors for gait state estimation. We create a device using an Arduino Uno and a 9-axis sensor module and experimented with the device attached to the waist, thigh, and ankle of the subject. Based on the features obtained here, the objective is to minimize the computational process in the system. We focus on the "x-axis," "y-axis," and "z-axis" of each sensor, and verify what characteristics were observed in various walking conditions. Experiments were conducted on three patterns of "walking," "fast walking," and "running" in three road conditions of "level ground," "uphill," and "downhill," and the feature values were compared. The experiments reveal that the gait state is mainly represented by the y-acceleration and x-angular velocity. Experimental results also confirm the validity and reliability of the proposed method.

Keywords: acceleration, angular velocity, walking, training, feature analysis, Arduino

DOI: 10.54941/ahfe1004096