Advanced performance analysis of the Illinois agility test based on the tangential velocity and turning radius in wheelchair rugby athletes

Usma, Clara; Chua, Julian J.C.; Fuss, Franz Konstantin; Subic, Aleksandar; Burton, Michael L.

doi:10.1080/19346182.2011.564284

Cited by 16 publications

(20 citation statements)

References 4 publications

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“…Three subsequent steps were undertaken to meet that aim: 1) reduction of a large number of kinematic outcomes to a set of key kinematic outcomes; 2) seeking a way to display key kinematic features in a concise but clear fashion, usable for coach and athlete; 3) testing if key features discriminate well between athletes of different performance levels. Since mobility performance is known to strongly relate to classification in wheelchair rugby (Rhodes et al, 2015b;Sarro et al, 2010;Usma-Alvarez et al, 2010), it should do so in wheelchair basketball as well, since both games use the same classification principle. Given this assumed performance difference due to classification, the new method was rated accurate if indeed classification appeared to be a significant factor in measured kinematic outcomes.…”

Section: Introductionmentioning

confidence: 99%

From big data to rich data: The key features of athlete wheelchair mobility performance

Slikke

Berger

Bregman

et al. 2016

Journal of Biomechanics

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27Quantitative assessment of an athlete's individual wheelchair mobility performance is one prerequisite 28 needed to evaluate game performance, improve wheelchair settings and optimize training routines. 29Inertial Measurement Unit (IMU) based methods can be used to perform such quantitative 30 assessment, providing a large number of kinematic data. The goal of this research was to reduce that 31 large amount of data to a set of key features best describing wheelchair mobility performance in 32 match play and present them in meaningful way for both scientists and athletes. To test the 33 discriminative power, wheelchair mobility characteristics of athletes with different performance levels 34 were compared. 35The wheelchair kinematics of 29 (inter-)national level athletes were measured during a match using 36 three inertial sensors mounted on the wheelchair. Principal component analysis was used to reduce 37 22 kinematic outcomes to a set of six outcomes regarding linear and rotational movement; speed and 38 acceleration; average and best performance. In addition, it was explored whether groups of athletes 39 with known performance differences based on their impairment classification also differed with 40 respect to these key outcomes using univariate general linear models. For all six key outcomes 41 classification showed to be a significant factor (p<0.05). 42We composed a set of six key kinematic outcomes that accurately describe wheelchair mobility 43 performance in match play. The key kinematic outcomes were displayed in an easy to interpret way, 44 usable for athletes, coaches and scientist. This standardized representation enables comparison of 45 different wheelchair sports regarding wheelchair mobility, but also evaluation at the level of an 46 individual athlete. By this means, the tool could enhance further development of wheelchair sports in 47 general. 48

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Section: Introductionmentioning

confidence: 99%

From big data to rich data: The key features of athlete wheelchair mobility performance

Slikke

Berger

Bregman

et al. 2016

Journal of Biomechanics

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“…As regards quality assessment results, 28 papers had a quality score between 0.81 and 1 [ 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 ], 10 papers were between 0.61 and 0.8 [ 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 ] and only one paper was below 0.6 [ 74 ]. Overall, the checklist items that reported the lower levels of scoring (e.g., partial or no score) were those concerning (a) the adequacy of sample size (16 papers), (b) the description/appropriateness of the strategy of subject/comparison group selection (10 papers).…”

Section: Resultsmentioning

confidence: 99%

“…A large variety of sports were investigated, including team sports, cyclic sports and other sports ( Table 2 ). The most common were wheelchair sports, with studies on wheelchair basketball [ 41 , 42 , 49 , 64 , 71 , 73 ], rugby [ 36 , 43 , 44 , 45 , 51 , 66 ], racing [ 40 , 47 , 53 , 54 , 67 ], tennis [ 50 , 63 ] and curling [ 48 ] covering almost 50% of the analyzed papers. The other half included cyclic sports (running [ 60 , 61 , 62 , 72 ], handcycling [ 57 , 58 , 59 , 70 ], swimming [ 37 , 38 , 39 ], cycling [ 52 , 65 ], rowing [ 46 ]) and other sports (weightlifting [ 69 ], boccia [ 55 ], cross-country sit-skiing [ 56 , 68 ] and downhill skiing [ 74 ]).…”

Section: Resultsmentioning

confidence: 99%

Wearable Sensors in Sports for Persons with Disability: A Systematic Review

Rum

Sten

Vendrame

et al. 2021

Sensors

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The interest and competitiveness in sports for persons with disabilities has increased significantly in the recent years, creating a demand for technological tools supporting practice. Wearable sensors offer non-invasive, portable and overall convenient ways to monitor sports practice. This systematic review aims at providing current evidence on the application of wearable sensors in sports for persons with disability. A search for articles published in English before May 2020 was performed on Scopus, Web-Of-Science, PubMed and EBSCO databases, searching titles, abstracts and keywords with a search string involving terms regarding wearable sensors, sports and disability. After full paper screening, 39 studies were included. Inertial and EMG sensors were the most commonly adopted wearable technologies, while wheelchair sports were the most investigated. Four main target applications of wearable sensors relevant to sports for people with disability were identified and discussed: athlete classification, injury prevention, performance characterization for training optimization and equipment customization. The collected evidence provides an overview on the application of wearable sensors in sports for persons with disability, providing useful indication for researchers, coaches and trainers. Several gaps in the different target applications are highlighted altogether with recommendation on future directions.

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“…A total of 33% (5/15) of the records used only IMUs for tracking (Pansiot et al [ 16 ]; van der Slikke et al [ 14 , 20 , 30 ]; [ 24 ]). Xu et al [ 7 ] used a local reference GPS with an Extended Kalman Filter, and Usma-Alvarez et al [ 21 ] used manually synced video and timing data to enable positional information.…”

Section: Discussionmentioning

confidence: 99%

A Literature Review Informing an Operational Guideline for Inertial Sensor Propulsion Measurement in Wheelchair Court Sports

Shepherd

James²,

Espinosa

et al. 2018

Sports

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With the increasing rise of professionalism in sport, teams and coaches are looking to technology to monitor performance in both games and training to find a competitive advantage. Wheelchair court sports (wheelchair rugby, wheelchair tennis, and wheelchair basketball) are no exception, and the use of microelectromechanical systems (MEMS)-based inertial measurement unit (IMU) within this domain is one innovation researchers have employed to monitor aspects of performance. A systematic literature review was conducted which, after the exclusion criteria was applied, comprised of 16 records. These records highlighted the efficacy of IMUs in terms of device validity and accuracy. IMUs are ubiquitous, low-cost, and non-invasive. The implementation in terms of algorithms and hardware choices was evidenced as a barrier to widespread adoption. This paper, through the information collected from the systematic review, proposes a set of implementation guidelines for using IMUs for wheelchair data capture. These guidelines, through the use of flow-charts and data tables, will aid researchers in reducing the barriers to IMU implementation for propulsion assessment.

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Advanced performance analysis of the Illinois agility test based on the tangential velocity and turning radius in wheelchair rugby athletes

Cited by 16 publications

References 4 publications

From big data to rich data: The key features of athlete wheelchair mobility performance

From big data to rich data: The key features of athlete wheelchair mobility performance

Wearable Sensors in Sports for Persons with Disability: A Systematic Review

A Literature Review Informing an Operational Guideline for Inertial Sensor Propulsion Measurement in Wheelchair Court Sports

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