Gyroscope-based assessment of temporal gait parameters during treadmill walking and running

McGrath, Denise; Greene, Barry R.; O’Donovan, Karol; Caulfield, Brian

doi:10.1007/s12283-012-0093-8

Cited by 55 publications

(64 citation statements)

References 23 publications

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“…They are able to acquire data pertaining to the inertial motion and 3D orientation of individual limb segments [11,12]. Selfcontained, wireless IMU devices are easy to set up, and allow for the acquisition of human movement data in unconstrained environments [13]. IMU systems can robustly track a variety of postures in the complex environment associated with training in the 'real-world', unlike camera-based systems, which are hampered by location, occlusion and lighting issues [14].…”

Section: Introductionmentioning

confidence: 99%

Wearable Inertial Sensor Systems for Lower Limb Exercise Detection and Evaluation: A Systematic Review

et al. 2018

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BackgroundAnalysis of lower limb exercises is traditionally completed with four distinct methods (i) 3D motion capture; (ii) depth-camera based systems (iii) visual analysis from a qualified exercise professional; (iv) self-assessment. Each method is associated with a number of limitations. ObjectiveThe aim of this systematic review is to synthesize and evaluate studies which have investigated the capacity for inertial measurement unit (IMU) technologies to assess movement quality in lower limb exercises. Data SourcesA systematic review of PubMed, ScienceDirect and Scopus was conducted. Study Eligibility CriteriaArticles written in English and published in the last 10 years which contained an IMU system for the analysis of repetition-based targeted lower limb exercises were included. Study Appraisal and Synthesis MethodsThe quality of included studies was measured using an adapted version of the STROBE assessment criteria for cross-sectional studies. The studies were categorised in to three groupings: exercise detection, movement classification or measurement validation. Each study was then qualitatively summarised. ResultsFrom the 2452 articles that were identified with the search strategies, 47 papers are included in this review. ConclusionsWearable inertial sensor systems for analysing lower limb exercises are a rapidly growing technology. Research over the past ten years has predominantly focused on validating measurements that the systems produce and classifying users' exercise quality. There have been very few user evaluation studies and no clinical trials in this field to date. Key PointsInertial measurement unit (IMU) systems have been extensively validated to successfully measure joint angle and temporal features during lower limb exercises.It is less understood if IMU systems can validly compute kinetic measures pertaining to lower limb exercises.IMU systems, which incorporate machine learning in to their data analysis pathways, have also been found to be effective in automated exercise detection and in classifying movement quality across a range of lower limb exercises.3

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Section: Introductionmentioning

confidence: 99%

Wearable Inertial Sensor Systems for Lower Limb Exercise Detection and Evaluation: A Systematic Review

et al. 2018

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“…These sensors are small, easy to set up and allow for the collection of data from subjects in an unconstrained environment [20]. Utilising IMUs for exercise monitoring is becoming increasingly popular, with commercially available products such as Jawbones TM and Fitbits TM using the sensors for activity tracking.…”

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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“…Of the 38 articles included in this review 23 articles utilised accelerometers and/or gyroscopes during running gait to identify coach orientated kinematic parameters (See Table 1.2). 48 Bergamini et al 17 Bichler et al 18 Cooper et al 19 Hausswirth et al 11 Heiden et al 49 Le Bris et al 31 Lee et al 32 Lee et al 47 McCurdy et al 50 McGrath et al 13 Mercer et al 35 Mercer et al 36 Neville et al 51 Neville et al 52 O'Donovan et al 20 Purcell et al 53 Stohrmann et al 22 Stohrmann et al 21 Stohrmann et al 23 Tan et al 14 Wixted et al 54 Yang et al 15 Step/Stride Frequency…”

Section: Coach Orientated Kinematic Output Parametersmentioning

confidence: 99%

“…O'Donovan et al 20 used a method by Aminian et al 57 which utilised mediolateral angular velocity. Bichler et al 18 stated that foot contact occurred between the first and last samples of angular velocity below 1rad in the respective foot and McGrath et al 13 utilised an algorithm which calculated thresholds based on angular velocity about the y-axis …”

Section: Temporal Parameters Secondary Coach Orientated Kinematic Pamentioning

confidence: 99%

Method analysis of accelerometers and gyroscopes in running gait: A systematic review

Norris

Anderson

Kenny

2013

Proceedings of the Institution of Mechanical Engineers, Part P:

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Purpose: To review articles utilising accelerometers and gyroscopes to measure running gait and assess various methodology utilised when doing so. To identify research and coaching orientated parameters which have been previously investigated and offer evidence based recommendations as to future methodology employed when investigating these parameters.Methods: Electronic databases were searched using key related terminology such as accelerometer(s) and gyroscope(s) and/or running gait. Articles returned were then visually inspected and subjected to an inclusion and exclusion criteria after which citations were inspected for further relevance. Thirty-eight articles were then included in the review.

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Gyroscope-based assessment of temporal gait parameters during treadmill walking and running

Cited by 55 publications

References 23 publications

Wearable Inertial Sensor Systems for Lower Limb Exercise Detection and Evaluation: A Systematic Review

Wearable Inertial Sensor Systems for Lower Limb Exercise Detection and Evaluation: A Systematic Review

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

Method analysis of accelerometers and gyroscopes in running gait: A systematic review

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