Optimization of Sports Training Systems Based on Wireless Sensor Networks Algorithms

Yang, Jun; Lv, Wu

doi:10.1109/jsen.2020.3046290

Cited by 14 publications

(7 citation statements)

References 20 publications

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“…The next work addresses another conundrum—can clients use the technology to self-direct and optimise their training program? Jang and Lv [ 13 ] aimed to design a sports training system by using data from a wireless sensor network. The implemented arrangement of sensor nodes and motion database software collects, stores and analyses the user’s motion parameters.…”

Section: Cloud Computingmentioning

confidence: 99%

“…Different OpenPose-based algorithms have been proposed to estimate segment and joint kinematics from either standard digital cameras [ 17 ] or smartphone images [ 18 ], and its performance was compared against 3D marker-based motion capture data (MoCap). Results have shown differences of less than 1° in joint angle estimation for hip and knee [ 13 ]. Gait parameters such as speed, cadence, step length and step time showed mean absolute differences lower than 2% [ 18 ].…”

Section: Applications In Performance and Health In Sportsmentioning

confidence: 99%

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Ubiquitous Computing in Sports and Physical Activity—Recent Trends and Developments

Baca

Dabnichki

et al. 2022

Sensors

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The use of small, interconnected and intelligent tools within the broad framework of pervasive computing for analysis and assessments in sport and physical activity is not a trend in itself but defines a way for information to be handled, processed and utilised: everywhere, at any time. The demand for objective data to support decision making prompted the adoption of wearables that evolve to fulfil the aims of assessing athletes and practitioners as closely as possible with their performance environments. In the present paper, we mention and discuss the advancements in ubiquitous computing in sports and physical activity in the past 5 years. Thus, recent developments in wearable sensors, cloud computing and artificial intelligence tools have been the pillars for a major change in the ways sport-related analyses are performed. The focus of our analysis is wearable technology, computer vision solutions for markerless tracking and their major contribution to the process of acquiring more representative data from uninhibited actions in realistic ecological conditions. We selected relevant literature on the applications of such approaches in various areas of sports and physical activity while outlining some limitations of the present-day data acquisition and data processing practices and the resulting sensors’ functionalities, as well as the limitations to the data-driven informed decision making in the current technological and scientific framework. Finally, we hypothesise that a continuous merger of measurement, processing and analysis will lead to the development of more reliable models utilising the advantages of open computing and unrestricted data access and allow for the development of personalised-medicine-type approaches to sport training and performance.

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Section: Cloud Computingmentioning

confidence: 99%

Section: Applications In Performance and Health In Sportsmentioning

confidence: 99%

Ubiquitous Computing in Sports and Physical Activity—Recent Trends and Developments

Baca

Dabnichki

et al. 2022

Sensors

View full text Add to dashboard Cite

show abstract

“…Literature [17] established an auxiliary model for evaluating and recognizing human sports postures with a deep learning algorithm as the core logic, which provides an intelligent auxiliary platform for athletes' training and effectively promotes the progress of trainers' sports levels. Literature [18] proposes an auxiliary training system based on wireless sensing technology to help improve the balance ability of athletes. Literature [19] introduces a golf sports simulation training product that can recognize and correct the user's golf sports posture and movements and, to a certain extent, promotes the improvement of the user's golf sports ability.…”

Section: Introductionmentioning

confidence: 99%

Development trend of the application of image recognition technology in the process of sports training

Wang

2024

Applied Mathematics and Nonlinear Sciences

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In the realm of sports training, the role of accurate image recognition is increasingly crucial for the effective correction of athletic movements. This research paper delves into the application of image recognition technologies to analyze sports training actions. Initial steps include the enhancement of image quality by filtering and sharpening images captured at a sports academy. Advanced techniques such as target detection algorithms and critical frame extraction are then applied to these refined images. Evaluations conducted on the KTH and UCF Sports action datasets reveal an average recognition rate of 88%, with further breakdowns indicating lower performance in activities like walking, jogging, and fast running in the KTH dataset. In contrast, uniform recognition results are observed in the UCF dataset with an average rate of 89.2% across various actions. The findings underscore the effectiveness of image recognition in improving sports training methodologies.

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“…Monitoring the exact pace of a game not only allows for fast and efficient returns but also lowers the risk of injuries [19,20]. As such, badminton gait analysis can be used as a valuable tool for diagnosing motor skills and enhancing training program optimization [21][22][23]. Additionally, gait analysis has been employed in fields like medical rehabilitation and other fields [17,[24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Ecoflex Flexible Array of Triboelectric Nanogenerators for Gait Monitoring Alarm Warning Applications

et al. 2023

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The advent of self-powered arrays of tribological nanogenerators (TENGs) that harvest mechanical energy for data collection has ushered in a promising avenue for human motion monitoring. This emerging trend is poised to shape the future landscape of biomechanical study. However, when we try to monitor various regions of the foot across disparate environments simultaneously, it poses a number of problems, such as the lack of satisfactory waterproofing, suboptimal heat resistance, inaccurate monitoring capacity, and the inability to transmit data wirelessly. To overcome these issues, we have developed an array of sensors affixed to the insole’s surface to adeptly monitor movement gait patterns and alert users to falls using self-powered triboelectric nanogenerators (TENGs). Each sensor cell on this sensor works as an individual air gap TENG (FWF-TENG), namely flexible, waterproof, and fast response, composed of an Ecoflex single-electrode array. Each FWF-TENG boasts a fast response time of 28 ms, which is sufficient to quickly monitor pressure changes during various badminton activities. Importantly, these sensors can persistently generate electrical signals at 70%RH humidity. Data obtained from these sensors can be transmitted to an upper computer intelligent terminal wirelessly through multi-grouped FHW-ENG sensing terminals in real time to achieve human–computer interaction applications, including motion technical determinations, feedback, and fall alerts. As a result, the interconnected TENG arrays have broad potential applications, including gait rehabilitation monitoring, motion technique identification, and fall alarm applications.

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Optimization of Sports Training Systems Based on Wireless Sensor Networks Algorithms

Cited by 14 publications

References 20 publications

Ubiquitous Computing in Sports and Physical Activity—Recent Trends and Developments

Ubiquitous Computing in Sports and Physical Activity—Recent Trends and Developments

Development trend of the application of image recognition technology in the process of sports training

Ecoflex Flexible Array of Triboelectric Nanogenerators for Gait Monitoring Alarm Warning Applications

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