3. Smart Gait Detection and Analysis

This chapter first introduces the basic principles and parameters of gait and then explains the laboratory equipment for gait analysis, including motion capture systems, force plates, and pressure pads. Real-life gait detection equipment is introduced, including video and sensor-based detection. Regarding visual perception, video surveillance systems, such as multiple CCTV cameras, can capture gait cycles by processing consecutive video frames using threshold filtering, edge detection, pixel counting, and background segmentation. Regarding wearable sensors, pressure pads and IMUs (inertial measurement units) can be used for gait detection. Pressure pads can be placed inside shoes to measure foot pressure distribution by detecting applied pressure and corresponding electronic changes. IMUs can measure and record motion data, including displacement, velocity, and acceleration. These wearable sensors can effectively detect gait and have good wearability and freedom, suitable for natural gait indoors and outdoors. The application of these technologies provides various options for gait detection and has comprehensive practical value in smart walking. It also covers the application of machine learning and deep learning in gait analysis, as well as research results on health-related walking applications. The chapter provides a comprehensive introduction and overview of the related technologies and applications of health-related walking detection and analysis.