How to record the amount of exercise automatically? A general real-time recognition and counting approach for repetitive activities
Shugang Zhang, Zhen Li, Jie Nie, Lei Huang, Shuang Wang, Zhiqiang Wei · 2016
Exercise is considered as an effective mean against overweight and obesity-related diseases. In this paper, a real-time activity recognition and counting approach is proposed to evaluate amount of exercise only using a wearable smart watch. First, accelerometer and gyroscope data are collected to extract efficient features. Then Support Vector Machine classifiers are trained to recognize nine common exercise activities in real time. In order to measure the frequency of repetitive activity, a general activity counting algorithm based on gyroscope is proposed which is applicable for different types of activity. Various activities can be counted uninterruptedly using the proposed general method without frequently changing algorithms. Through experiments, it is demonstrated that the extracted features are efficient for real time exercise activity recognition. Moreover, our comparative experiments have shown that our counting approach is more accurate than other products on the market.