Literature DB >> 20386133

Evaluation of standing vertical jump by ankles acceleration measurement.

Livio Quagliarella1, Nicola Sasanelli, Giuseppe Belgiovine, Lorenzo Moretti, Biagio Moretti.   

Abstract

The use of accelerometers is discussed to evaluate standing vertical jump. Two accelerometers, mounted on each ankle and connected to a wearable system, were used for signal acquisition, and a piezoelectric platform was used to verify the results. Fifty-one subjects were enrolled, subdivided into a group of healthy subjects and 2 groups who had different surgery for Achilles tendon rupture. Each subject performed 5 countermovement and 5 squat jumps; 11 subjects also performed 5 countermovement jumps with voluntary leg rotations during the flight phase. A training set was used to assess signal processing, and a validation set was used to verify its accuracy. A peak detection algorithm was developed to quantify flight time from the acceleration modulus, and its results were compared with platform data. The Pearson correlation coefficient of ankle accelerations and the integral of each signal were adopted to describe, respectively, the movement coordination and the limbs rotation during the flight time. The flight times obtained from the accelerometers and force plate were highly correlated (Spearman's coefficient >0.95); they were compared, for each jump, and the maximum mean error, for subject, was 4.8%. The movement coordination was in good agreement with subjects' clinical features and with the different jump phases. The signal integral presented significant differences, among jumps, related to leg rotations (p < 0.0005). The method proposed allows the monitoring of standing vertical jump using the fight time and gives information on the legs coordination and on the motor strategies of the lower limbs. Therefore, it can be used to obtain performance reference also outside labs, both in clinical and sport settings.

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Year:  2010        PMID: 20386133     DOI: 10.1519/JSC.0b013e3181cb281a

Source DB:  PubMed          Journal:  J Strength Cond Res        ISSN: 1064-8011            Impact factor:   3.775


  10 in total

1.  Reliability and validity of a wireless microelectromechanicals based system (keimove™) for measuring vertical jumping performance.

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Journal:  J Sports Sci Med       Date:  2012-03-01       Impact factor: 2.988

Review 2.  Wearable Inertial Sensor Systems for Lower Limb Exercise Detection and Evaluation: A Systematic Review.

Authors:  Martin O'Reilly; Brian Caulfield; Tomas Ward; William Johnston; Cailbhe Doherty
Journal:  Sports Med       Date:  2018-05       Impact factor: 11.136

3.  Effects of Strength Training Combined with Specific Plyometric exercises on body composition, vertical jump height and lower limb strength development in elite male handball players: a case study.

Authors:  Alberto Carvalho; Paulo Mourão; Eduardo Abade
Journal:  J Hum Kinet       Date:  2014-07-08       Impact factor: 2.193

Review 4.  Inertial Sensor Technology for Elite Swimming Performance Analysis: A Systematic Review.

Authors:  Robert Mooney; Gavin Corley; Alan Godfrey; Leo R Quinlan; Gearóid ÓLaighin
Journal:  Sensors (Basel)       Date:  2015-12-25       Impact factor: 3.576

5.  Effects of different re-warm up activities in football players' performance.

Authors:  Eduardo Abade; Jaime Sampaio; Bruno Gonçalves; Jorge Baptista; Alberto Alves; João Viana
Journal:  PLoS One       Date:  2017-06-29       Impact factor: 3.240

6.  Quantification of Triple Single-Leg Hop Test Temporospatial Parameters: A Validated Method using Body-Worn Sensors for Functional Evaluation after Knee Injury.

Authors:  Niloufar Ahmadian; Milad Nazarahari; Jackie L Whittaker; Hossein Rouhani
Journal:  Sensors (Basel)       Date:  2020-06-19       Impact factor: 3.576

7.  A sport-specific wearable jump monitor for figure skating.

Authors:  Dustin A Bruening; Riley E Reynolds; Chris W Adair; Peter Zapalo; Sarah T Ridge
Journal:  PLoS One       Date:  2018-11-21       Impact factor: 3.240

8.  Validation of an inertial measurement unit to determine countermovement jump height.

Authors:  Emil Toft Nielsen; Peter Bo Jørgensen; Inger Mechlenburg; Henrik Sørensen
Journal:  Asia Pac J Sports Med Arthrosc Rehabil Technol       Date:  2018-10-08

9.  Determining jumping performance from a single body-worn accelerometer using machine learning.

Authors:  Mark G E White; Neil E Bezodis; Jonathon Neville; Huw Summers; Paul Rees
Journal:  PLoS One       Date:  2022-02-10       Impact factor: 3.240

10.  A Nonproprietary Movement Analysis System (MoJoXlab) Based on Wearable Inertial Measurement Units Applicable to Healthy Participants and Those With Anterior Cruciate Ligament Reconstruction Across a Range of Complex Tasks: Validation Study.

Authors:  Riasat Islam; Mohamed Bennasar; Kevin Nicholas; Kate Button; Simon Holland; Paul Mulholland; Blaine Price; Mohammad Al-Amri
Journal:  JMIR Mhealth Uhealth       Date:  2020-06-16       Impact factor: 4.773

  10 in total

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