What and how well you exercised? An efficient analysis framework for fitness actions

Li, Jianwei; Hu, Qingrui; Guo, Tianxiao; Wang, Siqi; Shen, Yanfei

doi:10.1016/j.jvcir.2021.103304

Cited by 9 publications

(12 citation statements)

References 19 publications

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“…The consecutive blinded title and abstract screening of the remaining 132 articles resulted in 41 eligible and 91 excluded papers. After the full-text screening, 16 articles were included in this review [23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38], consisting of journal articles and conference proceedings from 2017 to 2021 (see Figure 3).…”

Section: Resultsmentioning

confidence: 99%

“…Two studies of karate and alpine skiing included only professional athletes (2 and 19, respectively) [33,38]. Ten articles included solely recreational athletes performing body-weight exercises, Nordic walking, pair dance or treadmill running [23][24][25][26][27][28]32,[35][36][37]. Four studies included recreational and professional athletes in the fields of karate, table tennis, triathlon and canoeing [29][30][31]34].…”

Section: Study Populations and Sport Disciplinesmentioning

confidence: 99%

“…Due to drop-outs, the sex composition in one paper differed between first (given in Table 1) and second experiment with 18 female and 37 male participants [23]. Four studies did not report the sex composition [29,[33][34][35]. Three studies did not report the age of their participants [29,34,35].…”

Section: Study Populations and Sport Disciplinesmentioning

confidence: 99%

“…Four studies did not report the sex composition [29,[33][34][35]. Three studies did not report the age of their participants [29,34,35]. One paper documented the age range instead of giving mean and standard deviation (18-54 years) [27].…”

Section: Study Populations and Sport Disciplinesmentioning

confidence: 99%

See 3 more Smart Citations

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

Venek¹,

Kranzinger²,

Schwameder

et al. 2022

Sensors

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The use of sensor technology in sports facilitates the data-driven evaluation of human movement not only in terms of quantity but also in terms of quality. This scoping review presents an overview of sensor technologies and human movement quality assessments in ecologically-similar environments. We searched four online databases to identify 16 eligible articles with either recreational and/or professional athletes. A total of 50% of the studies used inertial sensor technology, 31% vision-based sensor technology. Most of the studies (69%) assessed human movement quality using either the comparison to an expert’s performance, to an exercise definition or to the athletes’ individual baseline performance. A total of 31% of the studies used expert-based labeling of the movements to label data. None of the included studies used a control group-based study design to investigate impact on training progress, injury prevention or behavior change. Although studies have used sensor technology for movement quality assessment, the transfer from the lab to the field in recreational and professional sports is still emerging. Hence, research would benefit from impact studies of technology-assisted training interventions including control groups as well as investigating features of human movement quality in addition to kinematic parameters.

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Section: Resultsmentioning

confidence: 99%

Section: Study Populations and Sport Disciplinesmentioning

confidence: 99%

Section: Study Populations and Sport Disciplinesmentioning

confidence: 99%

Section: Study Populations and Sport Disciplinesmentioning

confidence: 99%

See 2 more Smart Citations

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

Venek¹,

Kranzinger²,

Schwameder

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…Yoga pose grading aims to quantitatively evaluate yoga poses so that it can realize yoga pose recognition (how a yoga pose is performed) and evaluate pose quality (how well a yoga pose is performed) [ 1 , 2 ]; which can distinguish different movements by analyzing pose characteristics. The most important aspect of yoga exercise is to do it correctly, since any wrong position can be counterproductive and possibly lead to injury [ 3 , 4 , 5 ].…”

Section: Introductionmentioning

confidence: 99%

A Computer Vision-Based Yoga Pose Grading Approach Using Contrastive Skeleton Feature Representations

Lin

Yang

et al. 2021

Healthcare

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The main objective of yoga pose grading is to assess the input yoga pose and compare it to a standard pose in order to provide a quantitative evaluation as a grade. In this paper, a computer vision-based yoga pose grading approach is proposed using contrastive skeleton feature representations. First, the proposed approach extracts human body skeleton keypoints from the input yoga pose image and then feeds their coordinates into a pose feature encoder, which is trained using contrastive triplet examples; finally, a comparison of similar encoded pose features is made. Furthermore, to tackle the inherent challenge of composing contrastive examples in pose feature encoding, this paper proposes a new strategy to use both a coarse triplet example—comprised of an anchor, a positive example from the same category, and a negative example from a different category, and a fine triplet example—comprised of an anchor, a positive example, and a negative example from the same category with different pose qualities. Extensive experiments are conducted using two benchmark datasets to demonstrate the superior performance of the proposed approach.

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Vision-based human action quality assessment: A systematic review

Liu,

Wang,

Stawarz

et al. 2025

Expert Systems with Applications

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What and how well you exercised? An efficient analysis framework for fitness actions

Cited by 9 publications

References 19 publications

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

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

A Computer Vision-Based Yoga Pose Grading Approach Using Contrastive Skeleton Feature Representations

Vision-based human action quality assessment: A systematic review

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