A Physical Activity Recommender System for Patients With Arterial Hypertension
Recommender systems have been applied in several areas, including e-Health systems, which refers to information and health services enhanced through technology. However, most studies aim at imposing rules to improve lifestyle, rather than recommending nutrition and physical activities. In this conte...
Gespeichert in:
| Veröffentlicht in: | IEEE access 2020, Vol.8, p.61656-61664 |
|---|---|
| Hauptverfasser: | , , , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 61664 |
|---|---|
| container_issue | |
| container_start_page | 61656 |
| container_title | IEEE access |
| container_volume | 8 |
| creator | Ferretto, Luciano Rodrigo Bellei, Ericles Andrei Biduski, Daiana Bin, Luiz Carlos Pereira Moro, Mirella Moura Cervi, Cristiano Roberto De Marchi, Ana Carolina Bertoletti |
| description | Recommender systems have been applied in several areas, including e-Health systems, which refers to information and health services enhanced through technology. However, most studies aim at imposing rules to improve lifestyle, rather than recommending nutrition and physical activities. In this context, this study aims to develop a system for recommending physical activities for hypertensive patients to create opportunities for the patients so they can search for and create a healthy lifestyle. To achieve this goal, we elaborated on a hypertensive user profile model, called HyperModel2PAR, and a physical activity recommender system for hypertensive patients, called HyperRecSysPA. The model resulting from this study is composed of 32 elements divided into three groups, which were used in the modeling of user profiles within the system for generating HyperRecSysPA recommendations. The developed system was validated by physicians who answered a specific questionnaire. As a result, ~75% of the recommendations generated were approved. Therefore, this study has prospective contributions to the literature, since both models obtained conclusive results in the assessments performed. |
| doi_str_mv | 10.1109/ACCESS.2020.2983564 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_ieee_</sourceid><recordid>TN_cdi_proquest_journals_2453689710</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>9047890</ieee_id><doaj_id>oai_doaj_org_article_2ebc11afb9f9481bb8c6aac0fa37876c</doaj_id><sourcerecordid>2453689710</sourcerecordid><originalsourceid>FETCH-LOGICAL-c408t-d5a90c77ba5f84be2a143502b8a6207c77a726f8ee0fe7f5553f52f5763aeb8e3</originalsourceid><addsrcrecordid>eNpNUU1rGzEQXUIDDWl-QS4LOdvVx2olHRfjJoHQhjihRzErj2IZe-VKcmD_fZSsCZ3LDG_mvRnmVdU1JXNKif7ZLRbL1WrOCCNzphUXbXNWXTDa6hkXvP32X_29ukppS0qoAgl5Uf3u6sfNmLyFXd3Z7N98HusntGG_x2GNsV6NKeO-diHWj5A9DjnVf33e1F3MGH2h3Y0HLPWQfBh-VOcOdgmvTvmyevm1fF7czR7-3N4vuoeZbYjKs7UATayUPQinmh4Z0IYLwnoFLSOydECy1ilE4lA6IQR3gjkhWw7YK-SX1f2kuw6wNYfo9xBHE8CbTyDEVwMxe7tDw7C3lILrtdONon2vbAtgiQMulWxt0bqZtA4x_DtiymYbjnEo5xvWlKcpLSkpU3yasjGkFNF9baXEfPhgJh_Mhw_m5ENhXU8sj4hfDE0aqTTh7--dhEs</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2453689710</pqid></control><display><type>article</type><title>A Physical Activity Recommender System for Patients With Arterial Hypertension</title><source>IEEE Open Access Journals</source><source>DOAJ Directory of Open Access Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Ferretto, Luciano Rodrigo ; Bellei, Ericles Andrei ; Biduski, Daiana ; Bin, Luiz Carlos Pereira ; Moro, Mirella Moura ; Cervi, Cristiano Roberto ; De Marchi, Ana Carolina Bertoletti</creator><creatorcontrib>Ferretto, Luciano Rodrigo ; Bellei, Ericles Andrei ; Biduski, Daiana ; Bin, Luiz Carlos Pereira ; Moro, Mirella Moura ; Cervi, Cristiano Roberto ; De Marchi, Ana Carolina Bertoletti</creatorcontrib><description>Recommender systems have been applied in several areas, including e-Health systems, which refers to information and health services enhanced through technology. However, most studies aim at imposing rules to improve lifestyle, rather than recommending nutrition and physical activities. In this context, this study aims to develop a system for recommending physical activities for hypertensive patients to create opportunities for the patients so they can search for and create a healthy lifestyle. To achieve this goal, we elaborated on a hypertensive user profile model, called HyperModel2PAR, and a physical activity recommender system for hypertensive patients, called HyperRecSysPA. The model resulting from this study is composed of 32 elements divided into three groups, which were used in the modeling of user profiles within the system for generating HyperRecSysPA recommendations. The developed system was validated by physicians who answered a specific questionnaire. As a result, ~75% of the recommendations generated were approved. Therefore, this study has prospective contributions to the literature, since both models obtained conclusive results in the assessments performed.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2020.2983564</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>Blood pressure ; eHealth ; Electronic healthcare ; Exercise ; Guidelines ; Hypertension ; Indexes ; Mathematical model ; Nutrition ; physical activity ; Physicians ; Recommender system ; Recommender systems ; user modeling</subject><ispartof>IEEE access, 2020, Vol.8, p.61656-61664</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c408t-d5a90c77ba5f84be2a143502b8a6207c77a726f8ee0fe7f5553f52f5763aeb8e3</citedby><cites>FETCH-LOGICAL-c408t-d5a90c77ba5f84be2a143502b8a6207c77a726f8ee0fe7f5553f52f5763aeb8e3</cites><orcidid>0000-0003-1443-1250 ; 0000-0002-2743-4111 ; 0000-0002-7704-3119 ; 0000-0002-0545-2001 ; 0000-0002-5839-8571 ; 0000-0002-6020-6356</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/9047890$$EHTML$$P50$$Gieee$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,860,2096,4010,27610,27900,27901,27902,54908</link.rule.ids></links><search><creatorcontrib>Ferretto, Luciano Rodrigo</creatorcontrib><creatorcontrib>Bellei, Ericles Andrei</creatorcontrib><creatorcontrib>Biduski, Daiana</creatorcontrib><creatorcontrib>Bin, Luiz Carlos Pereira</creatorcontrib><creatorcontrib>Moro, Mirella Moura</creatorcontrib><creatorcontrib>Cervi, Cristiano Roberto</creatorcontrib><creatorcontrib>De Marchi, Ana Carolina Bertoletti</creatorcontrib><title>A Physical Activity Recommender System for Patients With Arterial Hypertension</title><title>IEEE access</title><addtitle>Access</addtitle><description>Recommender systems have been applied in several areas, including e-Health systems, which refers to information and health services enhanced through technology. However, most studies aim at imposing rules to improve lifestyle, rather than recommending nutrition and physical activities. In this context, this study aims to develop a system for recommending physical activities for hypertensive patients to create opportunities for the patients so they can search for and create a healthy lifestyle. To achieve this goal, we elaborated on a hypertensive user profile model, called HyperModel2PAR, and a physical activity recommender system for hypertensive patients, called HyperRecSysPA. The model resulting from this study is composed of 32 elements divided into three groups, which were used in the modeling of user profiles within the system for generating HyperRecSysPA recommendations. The developed system was validated by physicians who answered a specific questionnaire. As a result, ~75% of the recommendations generated were approved. Therefore, this study has prospective contributions to the literature, since both models obtained conclusive results in the assessments performed.</description><subject>Blood pressure</subject><subject>eHealth</subject><subject>Electronic healthcare</subject><subject>Exercise</subject><subject>Guidelines</subject><subject>Hypertension</subject><subject>Indexes</subject><subject>Mathematical model</subject><subject>Nutrition</subject><subject>physical activity</subject><subject>Physicians</subject><subject>Recommender system</subject><subject>Recommender systems</subject><subject>user modeling</subject><issn>2169-3536</issn><issn>2169-3536</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ESBDL</sourceid><sourceid>RIE</sourceid><sourceid>DOA</sourceid><recordid>eNpNUU1rGzEQXUIDDWl-QS4LOdvVx2olHRfjJoHQhjihRzErj2IZe-VKcmD_fZSsCZ3LDG_mvRnmVdU1JXNKif7ZLRbL1WrOCCNzphUXbXNWXTDa6hkXvP32X_29ukppS0qoAgl5Uf3u6sfNmLyFXd3Z7N98HusntGG_x2GNsV6NKeO-diHWj5A9DjnVf33e1F3MGH2h3Y0HLPWQfBh-VOcOdgmvTvmyevm1fF7czR7-3N4vuoeZbYjKs7UATayUPQinmh4Z0IYLwnoFLSOydECy1ilE4lA6IQR3gjkhWw7YK-SX1f2kuw6wNYfo9xBHE8CbTyDEVwMxe7tDw7C3lILrtdONon2vbAtgiQMulWxt0bqZtA4x_DtiymYbjnEo5xvWlKcpLSkpU3yasjGkFNF9baXEfPhgJh_Mhw_m5ENhXU8sj4hfDE0aqTTh7--dhEs</recordid><startdate>2020</startdate><enddate>2020</enddate><creator>Ferretto, Luciano Rodrigo</creator><creator>Bellei, Ericles Andrei</creator><creator>Biduski, Daiana</creator><creator>Bin, Luiz Carlos Pereira</creator><creator>Moro, Mirella Moura</creator><creator>Cervi, Cristiano Roberto</creator><creator>De Marchi, Ana Carolina Bertoletti</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. (IEEE)</general><scope>97E</scope><scope>ESBDL</scope><scope>RIA</scope><scope>RIE</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7SR</scope><scope>8BQ</scope><scope>8FD</scope><scope>JG9</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-1443-1250</orcidid><orcidid>https://orcid.org/0000-0002-2743-4111</orcidid><orcidid>https://orcid.org/0000-0002-7704-3119</orcidid><orcidid>https://orcid.org/0000-0002-0545-2001</orcidid><orcidid>https://orcid.org/0000-0002-5839-8571</orcidid><orcidid>https://orcid.org/0000-0002-6020-6356</orcidid></search><sort><creationdate>2020</creationdate><title>A Physical Activity Recommender System for Patients With Arterial Hypertension</title><author>Ferretto, Luciano Rodrigo ; Bellei, Ericles Andrei ; Biduski, Daiana ; Bin, Luiz Carlos Pereira ; Moro, Mirella Moura ; Cervi, Cristiano Roberto ; De Marchi, Ana Carolina Bertoletti</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c408t-d5a90c77ba5f84be2a143502b8a6207c77a726f8ee0fe7f5553f52f5763aeb8e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Blood pressure</topic><topic>eHealth</topic><topic>Electronic healthcare</topic><topic>Exercise</topic><topic>Guidelines</topic><topic>Hypertension</topic><topic>Indexes</topic><topic>Mathematical model</topic><topic>Nutrition</topic><topic>physical activity</topic><topic>Physicians</topic><topic>Recommender system</topic><topic>Recommender systems</topic><topic>user modeling</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ferretto, Luciano Rodrigo</creatorcontrib><creatorcontrib>Bellei, Ericles Andrei</creatorcontrib><creatorcontrib>Biduski, Daiana</creatorcontrib><creatorcontrib>Bin, Luiz Carlos Pereira</creatorcontrib><creatorcontrib>Moro, Mirella Moura</creatorcontrib><creatorcontrib>Cervi, Cristiano Roberto</creatorcontrib><creatorcontrib>De Marchi, Ana Carolina Bertoletti</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 2005-present</collection><collection>IEEE Open Access Journals</collection><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE Electronic Library (IEL)</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>IEEE access</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ferretto, Luciano Rodrigo</au><au>Bellei, Ericles Andrei</au><au>Biduski, Daiana</au><au>Bin, Luiz Carlos Pereira</au><au>Moro, Mirella Moura</au><au>Cervi, Cristiano Roberto</au><au>De Marchi, Ana Carolina Bertoletti</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A Physical Activity Recommender System for Patients With Arterial Hypertension</atitle><jtitle>IEEE access</jtitle><stitle>Access</stitle><date>2020</date><risdate>2020</risdate><volume>8</volume><spage>61656</spage><epage>61664</epage><pages>61656-61664</pages><issn>2169-3536</issn><eissn>2169-3536</eissn><coden>IAECCG</coden><abstract>Recommender systems have been applied in several areas, including e-Health systems, which refers to information and health services enhanced through technology. However, most studies aim at imposing rules to improve lifestyle, rather than recommending nutrition and physical activities. In this context, this study aims to develop a system for recommending physical activities for hypertensive patients to create opportunities for the patients so they can search for and create a healthy lifestyle. To achieve this goal, we elaborated on a hypertensive user profile model, called HyperModel2PAR, and a physical activity recommender system for hypertensive patients, called HyperRecSysPA. The model resulting from this study is composed of 32 elements divided into three groups, which were used in the modeling of user profiles within the system for generating HyperRecSysPA recommendations. The developed system was validated by physicians who answered a specific questionnaire. As a result, ~75% of the recommendations generated were approved. Therefore, this study has prospective contributions to the literature, since both models obtained conclusive results in the assessments performed.</abstract><cop>Piscataway</cop><pub>IEEE</pub><doi>10.1109/ACCESS.2020.2983564</doi><tpages>9</tpages><orcidid>https://orcid.org/0000-0003-1443-1250</orcidid><orcidid>https://orcid.org/0000-0002-2743-4111</orcidid><orcidid>https://orcid.org/0000-0002-7704-3119</orcidid><orcidid>https://orcid.org/0000-0002-0545-2001</orcidid><orcidid>https://orcid.org/0000-0002-5839-8571</orcidid><orcidid>https://orcid.org/0000-0002-6020-6356</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 2169-3536 |
| ispartof | IEEE access, 2020, Vol.8, p.61656-61664 |
| issn | 2169-3536 2169-3536 |
| language | eng |
| recordid | cdi_proquest_journals_2453689710 |
| source | IEEE Open Access Journals; DOAJ Directory of Open Access Journals; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | Blood pressure eHealth Electronic healthcare Exercise Guidelines Hypertension Indexes Mathematical model Nutrition physical activity Physicians Recommender system Recommender systems user modeling |
| title | A Physical Activity Recommender System for Patients With Arterial Hypertension |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-21T00%3A32%3A43IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_ieee_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20Physical%20Activity%20Recommender%20System%20for%20Patients%20With%20Arterial%20Hypertension&rft.jtitle=IEEE%20access&rft.au=Ferretto,%20Luciano%20Rodrigo&rft.date=2020&rft.volume=8&rft.spage=61656&rft.epage=61664&rft.pages=61656-61664&rft.issn=2169-3536&rft.eissn=2169-3536&rft.coden=IAECCG&rft_id=info:doi/10.1109/ACCESS.2020.2983564&rft_dat=%3Cproquest_ieee_%3E2453689710%3C/proquest_ieee_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2453689710&rft_id=info:pmid/&rft_ieee_id=9047890&rft_doaj_id=oai_doaj_org_article_2ebc11afb9f9481bb8c6aac0fa37876c&rfr_iscdi=true |