Type

Conference Proceedings

Authors

Brian Caulfield
Tahar Kechadi
Oonagh M. Giggins
Bingquan Huang
Martin O'Reilly
Darragh Whelan

Subjects

Computer Science

Topics
clinical practice low cost data analysis conceptual framework personal sensing end users inertial measurement injury risk

Leveraging IMU Data for Accurate Exercise Performance Classification and Musculoskeletal Injury Risk Screening (2016)

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 tended to be accepted into routine clinical practice. This is often due to the 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. The work completed by our group indicates that IMU based systems have the potential to bridge the gap between laboratory and clinical movement analysis. Future work will focus on collecting a diverse range of movement data and using more sophisticated data analysis techniques to refine systems.
Collections Ireland -> University College Dublin -> Insight Research Collection
Ireland -> University College Dublin -> Computer Science Research Collection

Full list of authors on original publication

Brian Caulfield, Tahar Kechadi, Oonagh M. Giggins, Bingquan Huang, Martin O'Reilly, Darragh Whelan

Experts in our system

1
Brian Caulfield
University College Dublin
Total Publications: 273
 
2
Tahar Kechadi
University College Dublin
Total Publications: 68
 
3
Oonagh M. Giggins
University College Dublin
Total Publications: 9
 
4
Bingquan Huang
University College Dublin
Total Publications: 5
 
5
Martin O'Reilly
University College Dublin
Total Publications: 18
 
6
Darragh Whelan
Maynooth University
Total Publications: 14