Conference Proceedings


Brian Caulfield
Tomás Ward
Eamonn Delahunt
Nial Friel
Charalampos Chanialidis
Daragh Whelan
Martin O'Reilly


Computer Science

feature extraction statistical analysis body sensor networks system analysis performance measurement biomedical measurement sensitivity analysis inertial measurement

Evaluating Squat Performance with a Single Inertial Measurement Unit (2015)

Abstract Inertial measurement units (IMUs) may be used during exercise performance to assess form and technique. To maximise practicality and minimise cost a single-sensor system is most desirable. This study sought to investigate whether a single lumbar-worn IMU is capable of identifying seven commonly observed squatting deviations. Twenty-two volunteers (18 males, 4 females, age: 26.09±3.98 years, height: 1.75±0.14m, body mass: 75.2±14.2 kg) performed the squat exercise correctly and with 7 induced deviations. IMU signal features were extracted for each condition. Statistical analysis and leave one subject out classifier evaluation were used to assess the ability of a single sensor to evaluate performance. Binary level classification was able to distinguish between correct and incorrect squatting performance with a sensitivity of 64.41%, specificity of 88.01% and accuracy of 80.45%. Multi-label classification was able to distinguish between specific squat deviations with a sensitivity of 59.65%, specificity of 94.84% and accuracy of 56.55%. These results indicate that a single IMU can successfully discriminate between squatting deviations. A larger data set must be collected and more complex classification techniques developed in order to create a more robust exercise analysis IMU-based system.
Collections Ireland -> University College Dublin -> Insight Research Collection
Ireland -> University College Dublin -> Public Health, Physiotherapy and Sports Science Research Collection

Full list of authors on original publication

Brian Caulfield, Tomás Ward, Eamonn Delahunt, Nial Friel, Charalampos Chanialidis, Daragh Whelan, Martin O'Reilly

Experts in our system

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