Evaluating squat performance with a single inertial measurement unit

O’Reilly, Martin; Whelan, Darragh; Chanialidis, Charalampos; Friel, Nial; Delahunt, Eamonn; Ward, Tomás E.; Caulfield, Brian

doi:10.1109/bsn.2015.7299380

Cited by 33 publications

(23 citation statements)

References 20 publications

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“…This is not always possible due to cost and availability issues, meaning patients and clients are left to complete the exercise alone. This may result in ineffective training and rehabilitation in addition to increasing the risk of injury [23].…”

Section: Introductionmentioning

confidence: 99%

Evaluating Performance of the Lunge Exercise with Multiple and Individual Inertial Measurement Units

Whelan

O’Reilly

Ward

et al. 2016

Proceedings of the 10th EAI International Conference on Pervasive Computing Technologies for Healthcare

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The lunge is an important component of lower limb rehabilitation, strengthening and injury risk screening. Completing the movement incorrectly alters muscle activation and increases stress on knee, hip and ankle joints. This study sought to investigate whether IMUs are capable of discriminating between correct and incorrect performance of the lunge. Eighty volunteers (57 males, 23 females, age: 24.68± 4.91 years, height: 1.75± 0.094m, body mass: 76.01±13.29kg) were fitted with five IMUs positioned on the lumbar spine, thighs and shanks. They then performed the lunge exercise with correct form and 11 specific deviations from acceptable form. Features were extracted from the labelled sensor data and used to train and evaluate random-forests classifiers. The system achieved 83% accuracy, 62% sensitivity and 90% specificity in binary classification with a single sensor placed on the right thigh and 90% accuracy, 80% sensitivity and 92% specificity using five IMUs. This multi-sensor set up can detect specific deviations with 70% accuracy. These results indicate that a single IMU has the potential to differentiate between correct and incorrect lunge form and using multiple IMUs adds the possibility of identifying specific deviations a user is making when completing the lunge.

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Section: Introductionmentioning

confidence: 99%

Evaluating Performance of the Lunge Exercise with Multiple and Individual Inertial Measurement Units

Whelan

O’Reilly

Ward

et al. 2016

Proceedings of the 10th EAI International Conference on Pervasive Computing Technologies for Healthcare

Self Cite

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“…The results of this work demonstrated that a single IMU sensor is capable of classifying between seven different exercises with a high level of accuracy [14]. It was also shown that it is possible to classify between correct and incorrect performance of an exercise, and to classify the particular error in an exercise using data from a single IMU sensor with satisfactory levels of accuracy [1,19]. This work also indicated that the addition of extra IMU sensors does not significantly improve results [14,19].…”

Section: A Exercise Performance Evaluationmentioning

confidence: 71%

“…One IMU can classify performance in the single leg squat as acceptable or incorrect with 92% accuracy [6]. Furthermore, we have also shown the ability of a IMU based systems to quantify squat and lunge performance with moderate accuracy [1,15]. These movements are commonly completed screening tools with variations of them used in the FMS.…”

Section: B Musculoskeletal Injury Risk Screeningmentioning

confidence: 89%

“…This clinical consensus may be obtained through the use of previously validated frameworks [3,5]. This was the approach taken in our work where possible [1,6]. Where these published guidelines do not exist, it may be necessary to formulate new guidelines through the use of clinician-orientated questionnaires.…”

Section: Conceptual Frameworkmentioning

confidence: 99%

“…For exercise implementation, practitioners and strength and conditioning (S&C) coaches are faced with a myriad of issues associated with poor adherence and the inability to maintain good exercise technique. This can result in ineffective training and rehabilitation in addition to increasing the risk of injury [1]. When assessing for injury risk, practitioners have traditionally relied on visual observation and subjective evaluation using tools such as the Functional Movement Screen (FMS) [2] and other lower extremity screening tests [3].…”

Section: Introductionmentioning

confidence: 99%

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