Real-Time Monitoring System of Exercise Status Based on Internet of Health Things Using Safety Architecture Model

As an emerging field of information technology, the Internet of Health Things has attracted great attention from governments, scholars, and related enterprises, and is seen as a major opportunity for development and change in the information field. The European Commission believes that the development and application of the Internet of Health Things will make a significant contribution to solving modern social problems in the next 5 to 15 years. In this paper, the corresponding motion detection algorithms such as pacing detection algorithm, sleep quality and sedentary reminder detection algorithm are designed for real-time detection of motion status. In addition, this paper builds a new safety architecture model based on real-time motion detection, and proposes a time-domain feature-based motion detection method for walking, walking upstairs and walking downstairs. The original acceleration signal is smoothed and denoised using a sliding-average filter. The acceleration signal is segmented by a rectangular window with 50% overlap, and the variance, X-quartile difference, and X-axis bias coefficient are extracted from a single time window.