Title :
Evaluating squat performance with a single inertial measurement unit
Author :
Martin O´Reilly;Darragh Whelan;Charalampos Chanialidis;Nial Friel;Eamonn Delahunt;Tomás Ward;Brian Caulfield
Author_Institution :
Insight Centre for Data Analytics, University College Dublin
fDate :
6/1/2015 12:00:00 AM
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.
Keywords :
"Sensitivity","Knee","Accuracy","Joints","Hip","Yttrium","Gyroscopes"
Conference_Titel :
Wearable and Implantable Body Sensor Networks (BSN), 2015 IEEE 12th International Conference on
DOI :
10.1109/BSN.2015.7299380