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

Mooney, Robert; Corley, Gavin J.; Godfrey, Alan; Quinlan, Leo R.; ÓLaighin, Gearóid

doi:10.3390/s16010018

Cited by 115 publications

(112 citation statements)

References 132 publications

(343 reference statements)

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“…These systems also allow for long-term monitoring in ecologic settings, that is, for collecting data of patients at home, outdoor, and everywhere [1][2][3][4][5]. The design of integration between devices and smart textiles to produce products and services requires an interdisciplinary approach where electronic components together with different factors concerning clothes (anthropometric, aesthetical, elasticity, and washability) and the environment of use (on the ground, in the air, or in the water) must be merged [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

Method for Wearable Kinematic Gait Analysis Using a Harmonic Oscillator Applied to the Center of Mass

2018

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A model based on a harmonic oscillator describing human walking and balance with the sinusoidal trajectory of the center of mass of a subject during gait is presented. This model allows overcoming the traditional drift due to the double integration of raw acceleration data. The protocol uses a single 3D accelerometer worn at the pelvis level. The system computes the spatiotemporal gait and balance parameters when the subject is walking with or without aids. An incremental methodological approach is proposed and followed in the implementation and accuracy assessment. Eleven healthy subjects have participated to the study performing 6 trials over a fixed linear walking path at a self-selected speed. For reference, the protocol has imposed the execution of 52 steps whose length has been fixed at 60 cm. Different processing methods have been implemented and tested. The model identifies steps, walking time, and stepping frequency with an excellent reliability (absolute percentage accuracy error < 5%). When the information about the expected step length is given to the model, the percentage error in the measure of walking distance and speed is 3.25%. Without this input, this error rises to 4.95%, while for the anthropometric method is 3.68%.

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Section: Introductionmentioning

confidence: 99%

Method for Wearable Kinematic Gait Analysis Using a Harmonic Oscillator Applied to the Center of Mass

2018

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“…The raw data from accelerometers provide the swimming time, which is the major component in swimming performance (Mooney et al, 2015b). To compute it, the beginning and end of the swimming event are recorded.…”

Section: Determining Low-order Parameters: a First Level Of Analysis mentioning

confidence: 99%

Behavioral Dynamics in Swimming: The Appropriate Use of Inertial Measurement Units

Guignard¹,

Rouard

Chollet

et al. 2017

Front. Psychol.

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Motor control in swimming can be analyzed using low- and high-order parameters of behavior. Low-order parameters generally refer to the superficial aspects of movement (i.e., position, velocity, acceleration), whereas high-order parameters capture the dynamics of movement coordination. To assess human aquatic behavior, both types have usually been investigated with multi-camera systems, as they offer high three-dimensional spatial accuracy. Research in ecological dynamics has shown that movement system variability can be viewed as a functional property of skilled performers, helping them adapt their movements to the surrounding constraints. Yet to determine the variability of swimming behavior, a large number of stroke cycles (i.e., inter-cyclic variability) has to be analyzed, which is impossible with camera-based systems as they simply record behaviors over restricted volumes of water. Inertial measurement units (IMUs) were designed to explore the parameters and variability of coordination dynamics. These light, transportable and easy-to-use devices offer new perspectives for swimming research because they can record low- to high-order behavioral parameters over long periods. We first review how the low-order behavioral parameters (i.e., speed, stroke length, stroke rate) of human aquatic locomotion and their variability can be assessed using IMUs. We then review the way high-order parameters are assessed and the adaptive role of movement and coordination variability in swimming. We give special focus to the circumstances in which determining the variability between stroke cycles provides insight into how behavior oscillates between stable and flexible states to functionally respond to environmental and task constraints. The last section of the review is dedicated to practical recommendations for coaches on using IMUs to monitor swimming performance. We therefore highlight the need for rigor in dealing with these sensors appropriately in water. We explain the fundamental and mandatory steps to follow for accurate results with IMUs, from data acquisition (e.g., waterproofing procedures) to interpretation (e.g., drift correction).

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“…Outras limitações da coleta de dados por vídeo incluem a limitação da amostra (devido às limitações técnicas, o material coletado em vídeo costuma representar apenas um ciclo de braçada do nadador, em um trecho específico da piscina), a paralaxe do meio aquático e artefatos na imagem capturada (bolhas, turbulência, ocultamento de partes do corpo). Estes fatores contribuem para que _3971 treinadores percebam a videogrametria como tendo utilidade prática limitada, apesar dos mesmos reconhecerem a importância da análise quantitativa de desempenho (Mooney et al 2015). A Figura 2 mostra o procedimento de preparação de um atleta para o ensaio.…”

Section: Videogrametriaunclassified

Design De Wearables Para Uso Esportivo: Sensores Inerciais Aplicados À Natação Em Piscinas

Perry¹,

Becker²,

Marins³

2016

Blucher Design Proceedings

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Resumo: Este trabalho refere-se ao projeto e construção de wearables de baixo custo com foco na natação em piscinas, utilizando sensores inerciais para captura de dados com fins científicos. De forma ampla, os resultados deste projeto podem estender-se para diversas modalidades esportivas, com aplicações acadêmicas ou de ensino, tanto para atletas de alto rendimento como atletas amadores. Dispositivos desta natureza facilitam muito a coleta de dados "na borda da piscina", que atualmente são obtidos a muito custo. Estes dados são variáveis importantes na compreensão do rendimento do atleta, pois provavelmente se correlacionam com indicadores fisiológicos e biomecânicos. O esforço no sentido de desenvolver tais dispositivos tem se intensificado desde 2010, em função da diminuição do custo de componentes eletrônicos utilizados em tais dispositivos, e do desenvolvimento da tecnologia destes componentes. Palavras-chave:Wearables, sensores inerciais, natação.

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

Cited by 115 publications

References 132 publications

Method for Wearable Kinematic Gait Analysis Using a Harmonic Oscillator Applied to the Center of Mass

Method for Wearable Kinematic Gait Analysis Using a Harmonic Oscillator Applied to the Center of Mass

Behavioral Dynamics in Swimming: The Appropriate Use of Inertial Measurement Units

Design De Wearables Para Uso Esportivo: Sensores Inerciais Aplicados À Natação Em Piscinas

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