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Ubiquitous Computing in Sports and Physical Activity—Recent Trends and Developments
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 f...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9659168/ https://www.ncbi.nlm.nih.gov/pubmed/36366068 http://dx.doi.org/10.3390/s22218370 |
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author | Baca, Arnold Dabnichki, Peter Hu, Che-Wei Kornfeind, Philipp Exel, Juliana |
author_facet | Baca, Arnold Dabnichki, Peter Hu, Che-Wei Kornfeind, Philipp Exel, Juliana |
author_sort | Baca, Arnold |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-9659168 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-96591682022-11-15 Ubiquitous Computing in Sports and Physical Activity—Recent Trends and Developments Baca, Arnold Dabnichki, Peter Hu, Che-Wei Kornfeind, Philipp Exel, Juliana Sensors (Basel) Perspective 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. MDPI 2022-11-01 /pmc/articles/PMC9659168/ /pubmed/36366068 http://dx.doi.org/10.3390/s22218370 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Perspective Baca, Arnold Dabnichki, Peter Hu, Che-Wei Kornfeind, Philipp Exel, Juliana Ubiquitous Computing in Sports and Physical Activity—Recent Trends and Developments |
title | Ubiquitous Computing in Sports and Physical Activity—Recent Trends and Developments |
title_full | Ubiquitous Computing in Sports and Physical Activity—Recent Trends and Developments |
title_fullStr | Ubiquitous Computing in Sports and Physical Activity—Recent Trends and Developments |
title_full_unstemmed | Ubiquitous Computing in Sports and Physical Activity—Recent Trends and Developments |
title_short | Ubiquitous Computing in Sports and Physical Activity—Recent Trends and Developments |
title_sort | ubiquitous computing in sports and physical activity—recent trends and developments |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9659168/ https://www.ncbi.nlm.nih.gov/pubmed/36366068 http://dx.doi.org/10.3390/s22218370 |
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