Publicação
Using Artificial Intelligence-Enhanced Smartwatches for Performance Optimization in Sports
| Resumo: | The integration of artificial intelligence (AI) in sports training, specifically through smartwatch generated insights, has seen a significant change in how athletes optimize performance. This research delves into how athletes perceive and trust the recommendations provided by AI technology while exploring factors such as demographics and smartwatch usage habits that can impact long term performance enhancement, in different sports modalities. Using a quantitative methodology, an online survey was conducted with 114 athletes from diverse backgrounds, collecting data on their interaction with AI technology and adjustments in training routines. The results revealed that the level of trust in AI recommendations is more reliable on factors such as education level, frequency of use, and personal profiles of individual athletes rather than how long the athletes use the smartwatch. Moreover, athletes who frequently adjust their training plans based on AI feedback reported experiencing performance improvements. These findings suggest that, although AI can be used to maximize athletic training, its acceptance depends on how well it aligns with athlete’s individual needs, highlighting the importance of developing more personalized AI tools solutions for sports performance optimization. |
|---|---|
| Autores principais: | Flôr, Rita Falcão |
| Assunto: | Sports Artificial Intelligence Smartwatches Performance SDG 3 - Good health and well-being |
| Ano: | 2025 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade Nova de Lisboa |
| Idioma: | inglês |
| Origem: | Repositório Institucional da UNL |
| _version_ | 1868983112177811456 |
|---|---|
| author | Flôr, Rita Falcão |
| author_facet | Flôr, Rita Falcão |
| author_role | author |
| contributor_name_str_mv | Santos, Vítor Manuel Pereira Duarte dos RUN |
| country_str | PT |
| creators_json_txt | [{\"Person.name\":\"Flôr, Rita Falcão\"}] |
| datacite.contributors.contributor.contributorName.fl_str_mv | Santos, Vítor Manuel Pereira Duarte dos RUN |
| datacite.creators.creator.creatorName.fl_str_mv | Flôr, Rita Falcão |
| datacite.date.Accepted.fl_str_mv | 2025-11-05T00:00:00Z |
| datacite.date.available.fl_str_mv | 2025-11-19T12:12:31Z |
| datacite.date.embargoed.fl_str_mv | 2025-11-19T12:12:31Z |
| datacite.rights.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| datacite.subjects.subject.fl_str_mv | Sports Artificial Intelligence Smartwatches Performance SDG 3 - Good health and well-being |
| datacite.titles.title.fl_str_mv | Using Artificial Intelligence-Enhanced Smartwatches for Performance Optimization in Sports |
| dc.contributor.none.fl_str_mv | Santos, Vítor Manuel Pereira Duarte dos RUN |
| dc.creator.none.fl_str_mv | Flôr, Rita Falcão |
| dc.date.Accepted.fl_str_mv | 2025-11-05T00:00:00Z |
| dc.date.available.fl_str_mv | 2025-11-19T12:12:31Z |
| dc.date.embargoed.fl_str_mv | 2025-11-19T12:12:31Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://hdl.handle.net/10362/191028 |
| dc.language.none.fl_str_mv | eng |
| dc.rights.cclincense.fl_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| dc.rights.none.fl_str_mv | http://purl.org/coar/access_right/c_abf2 |
| dc.subject.none.fl_str_mv | Sports Artificial Intelligence Smartwatches Performance SDG 3 - Good health and well-being |
| dc.title.fl_str_mv | Using Artificial Intelligence-Enhanced Smartwatches for Performance Optimization in Sports |
| dc.type.none.fl_str_mv | http://purl.org/coar/resource_type/c_bdcc |
| description | The integration of artificial intelligence (AI) in sports training, specifically through smartwatch generated insights, has seen a significant change in how athletes optimize performance. This research delves into how athletes perceive and trust the recommendations provided by AI technology while exploring factors such as demographics and smartwatch usage habits that can impact long term performance enhancement, in different sports modalities. Using a quantitative methodology, an online survey was conducted with 114 athletes from diverse backgrounds, collecting data on their interaction with AI technology and adjustments in training routines. The results revealed that the level of trust in AI recommendations is more reliable on factors such as education level, frequency of use, and personal profiles of individual athletes rather than how long the athletes use the smartwatch. Moreover, athletes who frequently adjust their training plans based on AI feedback reported experiencing performance improvements. These findings suggest that, although AI can be used to maximize athletic training, its acceptance depends on how well it aligns with athlete’s individual needs, highlighting the importance of developing more personalized AI tools solutions for sports performance optimization. |
| dirty | 0 |
| eu_rights_str_mv | openAccess |
| format | masterThesis |
| fulltext.url.fl_str_mv | https://run.unl.pt/bitstreams/ae8a2845-5997-489b-9c31-6744a92b5188/download |
| id | run_0d1c6d1a12e641a90e7e2f4edb73a42e |
| identifier.url.fl_str_mv | http://hdl.handle.net/10362/191028 |
| inst_facet_str | urn:organizationAcronym:unl{{{_:::_}}}Universidade Nova de Lisboa |
| instacron_str | unl |
| institution | Universidade Nova de Lisboa |
| instname_str | Universidade Nova de Lisboa |
| language | eng |
| network_acronym_str | run |
| network_name_str | Repositório Institucional da UNL |
| oai_identifier_str | oai:run.unl.pt:10362/191028 |
| organization_str_mv | urn:organizationAcronym:unl |
| person_str_mv | Flôr, Rita Falcão |
| publishDate | 2025 |
| repo_facet_str | urn:repositoryAcronym:run{{{_:::_}}}Repositório Institucional da UNL |
| reponame_str | Repositório Institucional da UNL |
| repository_id_str | urn:repositoryAcronym:run |
| service_str_mv | urn:repositoryAcronym:run |
| spelling | engpt_PTThe integration of artificial intelligence (AI) in sports training, specifically through smartwatch generated insights, has seen a significant change in how athletes optimize performance. This research delves into how athletes perceive and trust the recommendations provided by AI technology while exploring factors such as demographics and smartwatch usage habits that can impact long term performance enhancement, in different sports modalities. Using a quantitative methodology, an online survey was conducted with 114 athletes from diverse backgrounds, collecting data on their interaction with AI technology and adjustments in training routines. The results revealed that the level of trust in AI recommendations is more reliable on factors such as education level, frequency of use, and personal profiles of individual athletes rather than how long the athletes use the smartwatch. Moreover, athletes who frequently adjust their training plans based on AI feedback reported experiencing performance improvements. These findings suggest that, although AI can be used to maximize athletic training, its acceptance depends on how well it aligns with athlete’s individual needs, highlighting the importance of developing more personalized AI tools solutions for sports performance optimization.application/pdfpt_PTUsing Artificial Intelligence-Enhanced Smartwatches for Performance Optimization in SportsFlôr, Rita FalcãoSantos, Vítor Manuel Pereira Duarte dosHostingInstitutionOrganizationalRUNe-mailmailto:run@unl.ptrun@unl.ptURNurn:tid:2040743202025-11-19T12:12:31Z2025-11-052025-11-05T00:00:00ZHandlehttp://hdl.handle.net/10362/191028http://purl.org/coar/access_right/c_abf2open accessSportsArtificial IntelligenceSmartwatchesPerformanceSDG 3 - Good health and well-being1855045 bytesliteraturehttp://purl.org/coar/resource_type/c_bdccmaster thesis2025-11-05http://creativecommons.org/licenses/by/4.0/http://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://run.unl.pt/bitstreams/ae8a2845-5997-489b-9c31-6744a92b5188/download |
| spellingShingle | Using Artificial Intelligence-Enhanced Smartwatches for Performance Optimization in Sports Flôr, Rita Falcão Sports Artificial Intelligence Smartwatches Performance SDG 3 - Good health and well-being |
| status | SINGLETON |
| subject.fl_str_mv | Sports Artificial Intelligence Smartwatches Performance SDG 3 - Good health and well-being |
| title | Using Artificial Intelligence-Enhanced Smartwatches for Performance Optimization in Sports |
| title_full | Using Artificial Intelligence-Enhanced Smartwatches for Performance Optimization in Sports |
| title_fullStr | Using Artificial Intelligence-Enhanced Smartwatches for Performance Optimization in Sports |
| title_full_unstemmed | Using Artificial Intelligence-Enhanced Smartwatches for Performance Optimization in Sports |
| title_short | Using Artificial Intelligence-Enhanced Smartwatches for Performance Optimization in Sports |
| title_sort | Using Artificial Intelligence-Enhanced Smartwatches for Performance Optimization in Sports |
| topic | Sports Artificial Intelligence Smartwatches Performance SDG 3 - Good health and well-being |
| topic_facet | Sports Artificial Intelligence Smartwatches Performance SDG 3 - Good health and well-being |
| url | http://hdl.handle.net/10362/191028 |
| visible | 1 |