Assessment of human motion using smartphone sensors: a tutorial for education, research and practice (Preprint)

Abstract

UNSTRUCTURED Sport science and rehabilitation are naturally evolving towards the implementation of data-driven technology for the analysis of human motion. Analysis of movement has traditionally been taught, researched, and implemented in practice either visually, or using equipment often unavailable outside specialized research centers. The motion sensors in contemporary smartphones can be used to collect acceleration and orientation data, making smartphones widely-available, low-cost devices that may provide useful in the characterization of human motion. The aim of this tutorial is to review basic concepts of how acceleration and orientation data collected with smartphone sensors can be used to assess human motion. We include six examples of data collection and analysis: jump height, balance, jogging cadence, joint range of motion, pelvic orientation during single-leg squat, timed up-and-go test. Acceleration and orientation data related to each example were analyzed using spreadsheet editors; video tutorials provide step-by-step guidance on how to analyze the data. Results are interpreted with respect to biomechanics, performance analysis and potential clinical relevance. We discuss this approach in the context of education, research and practice, hoping that it will help promote data-driven education and practice in fields that may benefit from objective analysis of human motion, such as sport science and rehabilitation.