Journal Article


Brian M Caulfield
Eamonn Delahunt
Tomas E Ward
Darragh F Whelan
Martin A O'Reilly


Computer Science

recent developments wearable technology mobile computing wearable sensors sensitivity and specificity lumbar spine real time strength and conditioning

Technology in S&C: Assessing Bodyweight Squat Technique with Wearable Sensors. (2017)

Abstract Strength and conditioning (S&C) coaches offer expert guidance to help those they work with achieve their personal fitness goals. However it is not always practical to operate under the direct supervision of an S&C coach and consequently individuals are often left training without expert oversight. Recent developments in inertial measurement units (IMUs) and mobile computing platforms have allowed for the possibility of unobtrusive motion tracking systems and the provision of real-time individualised feedback regarding exercise performance. These systems could enable S&C coaches to remotely monitor sessions and help individuals record their workout performance. One aspect of such technologies is the ability to assess exercise technique and detect common deviations from acceptable exercise form. In this study we investigate this ability in the context of a bodyweight (BW) squat exercise. IMUs were positioned on the lumbar spine, thighs and shanks of 77 healthy participants. Participants completed repetitions of BW squats with acceptable form and five common deviations from acceptable BW squatting technique. Descriptive features were extracted from the IMU signals for each BW squat repetition and these were used to train a technique classifier. Acceptable or aberrant BW squat technique can be detected with 98% accuracy, 96% sensitivity and 99% specificity when using features derived from all 5 IMUs. A single IMU system can also distinguish between acceptable and aberrant BW squat biomechanics with excellent accuracy, sensitivity and specificity. Detecting exact deviations from acceptable BW squatting technique can be achieved with 80% accuracy using a 5 IMU system and 72% accuracy when using a single IMU positioned on the right shank. These results suggest IMU based systems can distinguish between acceptable and aberrant BW squat technique with excellent accuracy with a single IMU system. Identification of exact deviations is also possible but multi-IMU systems outperform single IMU systems.
Collections Ireland -> Maynooth University -> PubMed

Full list of authors on original publication

Brian M Caulfield, Eamonn Delahunt, Tomas E Ward, Darragh F Whelan, Martin A O'Reilly

Experts in our system

Brian Caulfield
University College Dublin
Total Publications: 273
Eamonn Delahunt
University College Dublin
Total Publications: 115
Tomas Ward
Maynooth University
Total Publications: 177
Darragh Whelan
Maynooth University
Total Publications: 14
Martin O'Reilly
University College Dublin
Total Publications: 18