Digital Twin Coaching for Physical Activities: A Survey
Digital Twin technology has been rising in popularity thanks to the popularity of machine learning in the last decade. As the life expectancy of people around the world is increasing, so is the focus on physical activity to remain healthy especially in the current times where people are staying sede...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-10-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/20/20/5936 |
| _version_ | 1797550298071302144 |
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| author | Rogelio Gámez Díaz Qingtian Yu Yezhe Ding Fedwa Laamarti Abdulmotaleb El Saddik |
| author_facet | Rogelio Gámez Díaz Qingtian Yu Yezhe Ding Fedwa Laamarti Abdulmotaleb El Saddik |
| author_sort | Rogelio Gámez Díaz |
| collection | DOAJ |
| description | Digital Twin technology has been rising in popularity thanks to the popularity of machine learning in the last decade. As the life expectancy of people around the world is increasing, so is the focus on physical activity to remain healthy especially in the current times where people are staying sedentary while in quarantine. This article aims to provide a survey on the field of Digital Twin technology focusing on machine learning and coaching techniques as they have not been explored yet. We also define what Digital Twin Coaching is and categorize the work done so far in terms of the objective of the physical activity. We also list common Digital Twin Coaching characteristics found in the articles reviewed in terms of concepts such as interactivity, privacy and security and also detail future perspectives in multimodal interaction and standardization, to name a few, that can guide researchers if they choose to work in this field. Finally, we provide a diagram for the Digital Twin Ecosystem showing the interaction between relevant entities and the information flow as well as an idealization of an ideal Digital Twin Ecosystem for team sports’ athlete tracking. |
| first_indexed | 2024-03-10T15:27:19Z |
| format | Article |
| id | doaj.art-2b328ff0ab2c4cafa6661745d2303dbc |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T15:27:19Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-2b328ff0ab2c4cafa6661745d2303dbc2023-11-20T17:52:48ZengMDPI AGSensors1424-82202020-10-012020593610.3390/s20205936Digital Twin Coaching for Physical Activities: A SurveyRogelio Gámez Díaz0Qingtian Yu1Yezhe Ding2Fedwa Laamarti3Abdulmotaleb El Saddik4Multimedia Communications Research Laboratory, University of Ottawa, Ottawa, ON K1N6N5, CanadaMultimedia Communications Research Laboratory, University of Ottawa, Ottawa, ON K1N6N5, CanadaMultimedia Communications Research Laboratory, University of Ottawa, Ottawa, ON K1N6N5, CanadaMultimedia Communications Research Laboratory, University of Ottawa, Ottawa, ON K1N6N5, CanadaMultimedia Communications Research Laboratory, University of Ottawa, Ottawa, ON K1N6N5, CanadaDigital Twin technology has been rising in popularity thanks to the popularity of machine learning in the last decade. As the life expectancy of people around the world is increasing, so is the focus on physical activity to remain healthy especially in the current times where people are staying sedentary while in quarantine. This article aims to provide a survey on the field of Digital Twin technology focusing on machine learning and coaching techniques as they have not been explored yet. We also define what Digital Twin Coaching is and categorize the work done so far in terms of the objective of the physical activity. We also list common Digital Twin Coaching characteristics found in the articles reviewed in terms of concepts such as interactivity, privacy and security and also detail future perspectives in multimodal interaction and standardization, to name a few, that can guide researchers if they choose to work in this field. Finally, we provide a diagram for the Digital Twin Ecosystem showing the interaction between relevant entities and the information flow as well as an idealization of an ideal Digital Twin Ecosystem for team sports’ athlete tracking.https://www.mdpi.com/1424-8220/20/20/5936digital twinsmart coachingartificial intelligencemachine learningdeep learningfitness |
| spellingShingle | Rogelio Gámez Díaz Qingtian Yu Yezhe Ding Fedwa Laamarti Abdulmotaleb El Saddik Digital Twin Coaching for Physical Activities: A Survey Sensors digital twin smart coaching artificial intelligence machine learning deep learning fitness |
| title | Digital Twin Coaching for Physical Activities: A Survey |
| title_full | Digital Twin Coaching for Physical Activities: A Survey |
| title_fullStr | Digital Twin Coaching for Physical Activities: A Survey |
| title_full_unstemmed | Digital Twin Coaching for Physical Activities: A Survey |
| title_short | Digital Twin Coaching for Physical Activities: A Survey |
| title_sort | digital twin coaching for physical activities a survey |
| topic | digital twin smart coaching artificial intelligence machine learning deep learning fitness |
| url | https://www.mdpi.com/1424-8220/20/20/5936 |
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