Physical Exercise Quality Assessment Using Wearable Sensors

Müller, Philipp Niklas; Rauterberg, Felix; Achenbach, Philipp; Tregel, Thomas; Göbel, Stefan

doi:10.1007/978-3-030-88272-3_17

Cited by 7 publications

(17 citation statements)

References 10 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%

“…One paper documented the age range instead of giving mean and standard deviation (18-54 years) [27]. Two studies worked with participants with mean ages of 30.3 years [36] and 26.4 years [25], however, standard deviations were not given. The skill levels of the participants varied between novice and expert.…”

Section: Study Populations and Sport Disciplinesmentioning

confidence: 99%

“…Four articles stated that they recruited from local exercise groups [26], Chinese sports teams [30,34] or their institution [27]. Six articles reported ethical approvals [23,24,28,32,37,38], three reported informed consents prior data collection [25,31,34], and seven did not report any ethical information [26,27,29,30,33,35,36].…”

Section: Study Populations and Sport Disciplinesmentioning

confidence: 99%

“…Weich et al [31] used indoor and outdoor environments to simulate the triathlon transition run from cycling to running. Four articles did not report where the studies were conducted, but from figures a lab-like environment for the exercise studies could be assumed [26,28,32,36].…”

Section: Study Populations and Sport Disciplinesmentioning

confidence: 99%

See 4 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%

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

View full text Add to dashboard Cite

show abstract

Recognition of TaeKwonDo kicking techniques based on accelerometer sensors

Liu,

Yang,

et al. 2024

Heliyon

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Assessing Human Motion During Exercise Using Machine Learning: A Literature Review

et al. 2022

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The World Health Organization promotes healthy living through regular physical activities, such as exercise and sports, as well as access to healthcare and rehabilitation services for people with motor dysfunctions. However, there is a lack of specialized personnel and increased costs associated with such activities. These have led to the increased use of machine learning for the analysis and evaluation of human motion during exercise. To study the latest advancements in this area, a systematic literature review focusing on publications from 2017 to 2021 was performed. As a result, 88 relevant publications were identified, which developed both shallow machine learning and deep learning algorithms. The results indicated that algorithms for human motion assessment should provide personalized and informative assessments, with explainable and interpretable outcomes, that can be computed in real-time or concurrently with the execution of an exercise. Furthermore, they should be easy to adapt based on the needs of applications and should be able to perform with different motion capture systems. This has been challenging because of the usually small amount of collected data, the lack of large open datasets, and the unique characteristics of exercise motions. Based on the above findings, guidelines for the development of such algorithms are proposed and discussed. They relate to the selection of the type of assessment, handling data imbalances, selecting of motion capture technologies, balancing between accuracy and speed, selecting the right algorithm, performing concurrent assessment during an exercise, personalization and scalability, and evaluation.

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Physical Exercise Quality Assessment Using Wearable Sensors

Cited by 7 publications

References 10 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

Recognition of TaeKwonDo kicking techniques based on accelerometer sensors

Assessing Human Motion During Exercise Using Machine Learning: A Literature Review

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