2022 IEEE International Workshop on Sport, Technology and Research (STAR)

Conference Information
Name: 2022 IEEE International Workshop on Sport, Technology and Research (STAR)
Location: Trento, Italy
Date: 2022-7-6 - 2022-7-8

Latest articles from this conference

Andrea Zignoli, Damiano Fruet
Abstract:
This manuscript deals with the development of a generative model trained to create realistic cardiopulmonary test data. The model consists in a conditional generative adversarial neural network. The model can be used to generate an infinite number of fake-but-realistic cardiopulmonary tests. The gener-ated samples can be used in a variety of different applications, such as: 1) the creation of a shared dataset of well-defined tests that can be used to develop new methods for diagnostics and interpretation or to train exercise physiologists, and 2) to fill data gaps where artifacts are dominating the cardiopulmonary variables or when real data points are missing. The algorithm is deployed on a server and a web app can be used to challenge users to differentiate between a fake and a real test.
Alessio Serrani, Andrea Aliverti
Abstract:
The application of wearable devices for monitoring purposes is an open research topic and the study of increasingly reliable platforms is becoming more and more treated and widespread in the research community due to the recent great development of the telemedicine field. A telemedicine platform based on wearable sensors could allow the reduction of the hospitalizations, the prevention of acute events in chronic patients, the monitoring of the drug therapys functioning or just an autonomous and periodic monitoring of the patients health status during daily life or sports practice. Nowadays plenty of monitoring platforms are present in the market, developed for different use cases and scenarios, but usually the design is uncomfortable for the daily usage during sport activities or the clinical relevance of the collected information is poor. In order to address these issues, in this paper we propose an innovative fully wireless embedded platform to collect multiple physiological parameters in a real-time scenario, designed to both maximise user comfort and ensure high synchronization performance between different sensor nodes. Examples of possible applications could be the assessment of the sport performance during a physical training session or the real time evaluation of athletes health status during long-term sport competitions.
Salvatore Tedesco, Sebastian Scheurer, Kenneth N. Brown, Liam Hennessy, Brendan O'Flynn
Abstract:
Artificial Intelligence (AI) could play a significant role in injury prediction in sports due to its capabilities to detect and identify hidden patterns across multi-modal heterogeneous data sources. This paper aims at providing an up-to-date survey of the state-of-the-art in machine learning for injury predictions in sports. Finally, a number of considerations have been also drawn to discuss about the future research challenges required to be tackled to move this field forward.
Dario Petri, Paolo Carbone, Luca Mari
Abstract:
Under the assumption that information provided by measurements may be usefully exploited to improve sport performances, this paper addresses the problem of defining and assessing the quality of measurement information in the context of sports applications. By using some criteria organized, according to semiotics, into syntactic, semantic, and pragmatic layers, a previously published framework is adapted to interpret measurement information acquired for sports applications. The framework is illustrated, and a case study is presented to introduce its application.
Ada Ferri, Marco Barla, Cristian Campagnaro, Francesca Dotti, Martina Dugoni, Guglielmo Marchesa, Daniele Mozzone, Alberto Vallan
Abstract:
A Cloth Face Covering (CFC) to prevent the spread of SARS-COVID 2 was designed and tested with the aim of minimising interference with athletic performance. A highly rigid 3D mesh fabric was chosen as the reusable frame and an electrospun non-woven fabric as the replaceable filter. A product with extremely high breathability was developed that complies with the Italian standard UNI/PdR 90.1:2020. Measurements of the pressure in the dead space during sports practise confirmed the low breathing resistance of CFC. In maximal tests, no differences were found in maximum heart rate and duration of exertion, while the rate of perceived exertion (RPE) was slightly higher when wearing CFC compared to not wearing the mask.
Anna-Maria Kogler, Elisabeth Happ, Martin Schnitzer
Abstract:
Physical activity (PA) is essential for kids health and well-being and therefore crucial for our society. There is a call from the academic community for a consistent conceptualization, hence the aim of this paper is to set up a base for future research. In order to frame a conceptualization in relation to the interplay between PA, individual characteristics and environment of kids, this paper in hand investigates in a first step (RQ1) how to develop a conceptual framework for children in terms of PA, individual characteristics and environment (settings and sources of influence) based on existing score cards and literature, (RQ2) how to enlarge existing knowledge by adding potential components caused by the epidemic to this framework and, moreover, (RQ3) tries to shed more light on the pillar resilience conducting a qualitative approach (world café). Findings of the research project may support the value of PA of youngsters in the extensive school context as well as during leisure time leading to a holistic approach towards supporting the well-being of children and their future health.
Binh Vu, Sebastian Bruchhaus, Anne Moorhead, Huiru Zheng, Luigi D'Arco, Louise Lynch, Luigia Simona Sica, Michela Ponticorvo, Federico Diano, Haithem Afli, et al.
Abstract:
Health and performance monitoring technologies are commonly used by athletes. Obese people on the other hand benefit less from empowering technologies that address their specific needs. It would arguably have a substantial positive impact if such could promote a more active lifestyle. The consequential costs of obesity are a matter of great concern for health professionals and European policy makers alike. The EU-funded STop Obesity Project (STOP) addresses these shortcomings. Its main work results are a platform and a gamified app supporting people with obesity under professional supervision. STOP employs smart sensors and artificial intelligence in the form of a chatbot that teaches healthy nutrition and physical activity. Users interact with it through digital avatars on their smartphones while supervising health care professionals are presented with the results through an analytics pipeline. The platform is based on the Knowledge Management Ecosystem Portal (KM-EP) for data management, and visualisation. It fuses data from the app with streams from various vendors wearable health trackers. All the while ethical concerns feature prominently in the design of STOP. A feasibility study with obese volunteers showed that STOP in fact can be used as intended. Moreover, participants in a separate usability study gave generally positive ratings for its user experience.
Alessandra Angelucci, Federica Camuncoli, Manuela Galli, Andrea Aliverti
Abstract:
Respiratory Rate (RR) can be detected with wearable devices, which can be used to monitor daily life activities continuously. Here we introduce a configuration that allows to filter the respiratory signal based on the activity level with the same sensor system. One healthy subject was recruited (age 55 yo., weight 80 kg, height 1.76 m, sex M). The protocol involved the assessment of RR in four conditions: standing, walking, running slow, and running fast. Data from a gold standard (K5; COSMED, Rome, Italy) and from the novel IMU-based sensor system developed by the research team were collected. The IMU-based sensor system consists of three units placed respectively on the thorax, on the abdomen, and on the lower back. The analysis of the IMU signals is based on Principal Component Analysis (PCA) to identify different movement patterns. Agreement was found between the K5 and the IMUs system. In a static posture, RR can be computed from the first PCA component. During dynamic activities, RR can generally be computed from the second PCA component. The first PCA component during dynamic activities is related to the stride. This finding suggests further research to develop an algorithm for respiratory signal filtering based on activity, thus improving accuracy.
Luca Santoro, Matteo Nardello, Daniele Fontanelli, Davide Brunelli, Dario Petri
Abstract:
Maintaining players performance during training or competition is fundamental in modern team sports. Parallel to the classical laboratory-based assessment, recent technological developments have made it possible to develop wearable sensors that can monitor real-time players performance without hindering them and avoid complex setup procedures. This paper presents the preliminary investigation of a flexible, lightweight, and easy to reconfigure tracking system for sports players that can be used both indoor and outdoor. The system is based on COTS components and exploits both UWB positioning and inertial sensors data fusion to real-time track players performances. Thanks to the R-TDOA link approach and Bluetooth data sharing, energy efficiency is ensured in a very compact form factor. Results highlight the feasibility of the solution by assessing battery autonomy and the accuracy of the tracking infrastructure.
Chantelle Jean Rigozzi, Jeremy Cox, Gareth A Vio, Philip Poronnik
Abstract:
Elbow tendinopathy injuries are very common in tennis players. One of the commonly accepted theories describing the development of elbow tendinopathy is based on stiffness of the forearm skeletal muscle units, their repetitive overuse and vibrational transfer from impact in tennis. The objective of this study was to design, develop and test a novel microcontroller based wearable device which could simultaneously measure a players grip strength, forearm electromyographic activity and vibrational transfer under realistic playing conditions. The device was tested on four tennis players of various playing levels (a previously WTA player, a qualified tennis coach and 2 recreational players) who were required to hit forehands cross-court with different spin levels (flat and topspin) into the back diagonal square following a specific height guideline. The results indicated that the device could record unique player technical profiles of vibrational transfer, racket orientation angle, grip strength and forearm muscle activity during the stroke. This study demonstrates the potential benefits of a wearable device to measure kinematic parameters associated with elbow injury development in tennis players, as well as provide coaching recommendations for potentially reducing the risk of developing elbow tendinopathy.
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