Human Movement Quality Assessment Using Sensor Technologies in Recreational and Professional Sports: A Scoping Review

Venek, Verena; Kranzinger, Stefan; Schwameder, Hermann; Stöggl, Thomas

doi:10.3390/s22134786

Cited by 10 publications

(4 citation statements)

References 36 publications

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“…Many published papers are concerned with ways to measure and model individual behaviour (among others, for position tracking and action recognition, performance and fatigue detection, and action quality recognition) e.g., a recent survey on human movement quality assessment ( 40 ). These papers focus on the measurement and tracking devices that can be used in various sports [e.g., ( 41 , 42 )], including highly customized measurement systems, for example for climbing holds ( 43 ) or bowling grips ( 44 ).…”

Section: Related Workmentioning

confidence: 99%

Enhancing volleyball training: empowering athletes and coaches through advanced sensing and analysis

Salim,

Postma,

Haider

et al. 2024

Front. Sports Act. Living

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Modern sensing technologies and data analysis methods usher in a new era for sports training and practice. Hidden insights can be uncovered and interactive training environments can be created by means of data analysis. We present a system to support volleyball training which makes use of Inertial Measurement Units, a pressure sensitive display floor, and machine learning techniques to automatically detect relevant behaviours and provides the user with the appropriate information. While working with trainers and amateur athletes, we also explore potential applications that are driven by automatic action recognition, that contribute various requirements to the platform. The first application is an automatic video-tagging protocol that marks key events (captured on video) based on the automatic recognition of volleyball-specific actions with an unweighted average recall of 78.71% in the 10-fold cross-validation setting with convolution neural network and 73.84% in leave-one-subject-out cross-validation setting with active data representation method using wearable sensors, as an exemplification of how dashboard and retrieval systems would work with the platform. In the context of action recognition, we have evaluated statistical functions and their transformation using active data representation besides raw signal of IMUs sensor. The second application is the “bump-set-spike” trainer, which uses automatic action recognition to provide real-time feedback about performance to steer player behaviour in volleyball, as an example of rich learning environments enabled by live action detection. In addition to describing these applications, we detail the system components and architecture and discuss the implications that our system might have for sports in general and for volleyball in particular.

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Section: Related Workmentioning

confidence: 99%

Enhancing volleyball training: empowering athletes and coaches through advanced sensing and analysis

Salim,

Postma,

Haider

et al. 2024

Front. Sports Act. Living

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“…Temporal analysis aims at the movement timing using variables such as the duration of the whole cycle of movement and the duration of the movement phases (the latter is expressed in seconds as well as by a percentage of the cycle of movement duration). Force plates [8][9][10][11], and motion capture systems [11,12] have traditionally been used in laboratory testing, whereas wearable inertial sensors have emerged as a portable and affordable tool for assessing human movement patterns in a field setting [1][2][3][4][5][6]13].…”

Section: Introductionmentioning

confidence: 99%

Two Repetitions May Be Enough! Reliability of Movement Timing in Physical Fitness Exercises Performed by Young, Trained Adults Using Inertial Sensors

Emmanouil,

Rousanoglou,

Boudolos

2024

Biomechanics

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This study aimed to determine the minimum number of repetitions for a high reliability of movement timing in fundamental physical fitness exercises using inertial sensors. Fifteen young men and fifteen women performed eight exercises (two-leg hop, forward lunge, squat, sit-up, shoulder abduction, hip abduction, back extension, and push-up) (preferred tempo, 3 trials, 20 repetitions per trial). The movement timing (cycle of movement in seconds and its phases in seconds and %tcycle) was tested for intra- and inter-trial reliability (SPSS 28.0, p ≤ 0.05). Just two repetitions were adequate for excellent intra- and inter-trial relative reliability (ICCs ≥ 0.75, isolated exceptions only for durations expressed as %tcycle, in only three out of the eight exercises: hip abduction, back extension, and push-up), as well as for high absolute intra- and inter-trial reliability (average SEM% at 5.9%, respectively, and 6.8% and average MDC95% at 13.7% and 15.9%, respectively, which was consistently higher than the upper boundary limit of SEM%, and a rather low CV% ranging from 1.5% to 4.9% and averaging at 3.1%). A total of four repetitions, excluding the initial and the final one, appears adequate for high overall reliability of movement timing in the eight physical fitness exercises examined.

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“…Both strength and neuromuscular imbalances are directly related to injury risk factors [4,5]. The movement quality is characterized by capacity to execute motions in a precise and efficient manner [6]. Thus, the neuromuscular imbalances are usually labelled as an important part of human quality of movement, defined as the movement executed with proper posture, breathing, mobility and coordination in activities or specific tasks performed optimally and efficiently [7].…”

Section: Introductionmentioning

confidence: 99%

Single-Leg Countermovement Jump Compensation Assessment: Content Validity of a Checklist

Barrio,

Hernández-García,

Ramirez-Campillo

et al. 2024

Int J Sports Med

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Jump actions are common in several sports, and its performance is related to a myriad of biomechanical and physiological factors, with links to athletic performance and imbalances. Currently, a valid, field-based, easy-to-use tool to assess the quality of an explosive jump movement, similar to the required sports movements, is unavailable. Thus, the present study aimed to design and validate a field-based, easy-to-use tool that can be used to assess the quality of movement during an explosive single-leg countermovement jump (SL-CMJ). Ten experts participated in the content validation process of the checklist including item relevance, definition accuracy, and scoring adequacy. Content validity was measured using the Aikens V format. The checklist included the items “Foot orientation”, “Knee valgus/varus”, “Internal/external hip flexed orientation”, “Pelvis tilt”, “Thorax tilt”, “Thorax rotation”, “Foot pronation/supination”, “Asymmetrical hip”, and “Lumbo-pelvic association”. The items achieved a 0.60-0.99 in relevance, 0.70-1.00 in definition accuracy, and 0.80-0.83 in scoring adequacies in the Aikens V proof. The results from the context validation process suggest that the tool may be appropriate to assess athletes’ quality of explosive movement. Furthermore, the results derived from such assessment may help to design better and safer training interventions.

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Human Movement Quality Assessment Using Sensor Technologies in Recreational and Professional Sports: A Scoping Review

Cited by 10 publications

References 36 publications

Enhancing volleyball training: empowering athletes and coaches through advanced sensing and analysis

Enhancing volleyball training: empowering athletes and coaches through advanced sensing and analysis

Two Repetitions May Be Enough! Reliability of Movement Timing in Physical Fitness Exercises Performed by Young, Trained Adults Using Inertial Sensors

Single-Leg Countermovement Jump Compensation Assessment: Content Validity of a Checklist

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