title: Leveraging IMU data for accurate exercise performance classification and musculoskeletal injury risk screening.
abstract: Inertial measurement units (IMUs) are becoming increasingly prevalent as a method for low cost and portable biomechanical analysis. However, to date they have not been accepted into routine clinical practice. This is often due to a disconnect between translating the data collected by the sensors into meaningful and actionable information for end users. This paper outlines the work completed by our group in attempting to achieve this. We discuss the conceptual framework involved in our work, the methodological approach taken in analysing sensor signals and discuss possible application models. Our work indicates that IMU based systems have the potential to bridge the gap between laboratory and clinical movement analysis. Future studies will focus on collecting a diverse range of movement data and using more sophisticated data analysis techniques to refine systems.
authors.forename: Darragh
authors.initials: D
authors.lastname: Whelan
authors.forename: Martin
authors.initials: M
authors.lastname: O'Reilly
authors.forename: Bingquan
authors.initials: B
authors.lastname: Huang
authors.forename: Oonagh
authors.initials: O
authors.lastname: Giggins
authors.forename: Tahar
authors.initials: T
authors.lastname: Kechadi
authors.forename: Brian
authors.initials: B
authors.lastname: Caulfield
mesh_terms: D000465:Algorithms; D001696:Biomechanical Phenomena; D015444:Exercise; D006801:Humans; D009068:Movement / Q000502:physiology; D009141:Musculoskeletal System / Q000293:injuries*; D012306:Risk