Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic?
Goal: The aim of the study herein reported was to review mobile health (mHealth) technologies and explore their use to monitor and mitigate the effects of the COVID-19 pandemic. Methods: A Task Force was assembled by recruiting individuals with expertise in electronic Patient-Reported Outcomes (ePRO...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Catherine P. Adans-Dester [verfasserIn] Stacy Bamberg [verfasserIn] Francesco P. Bertacchi [verfasserIn] Brian Caulfield [verfasserIn] Kara Chappie [verfasserIn] Danilo Demarchi [verfasserIn] M. Kelley Erb [verfasserIn] Juan Estrada [verfasserIn] Eric E. Fabara [verfasserIn] Michael Freni [verfasserIn] Karl E. Friedl [verfasserIn] Roozbeh Ghaffari [verfasserIn] Geoffrey Gill [verfasserIn] Mark S. Greenberg [verfasserIn] Reed W. Hoyt [verfasserIn] Emil Jovanov [verfasserIn] Christoph M. Kanzler [verfasserIn] Dina Katabi [verfasserIn] Meredith Kernan [verfasserIn] Colleen Kigin [verfasserIn] Sunghoon I. Lee [verfasserIn] Steffen Leonhardt [verfasserIn] Nigel H. Lovell [verfasserIn] Jose Mantilla [verfasserIn] Thomas H. McCoy [verfasserIn] Nell Meosky Luo [verfasserIn] Glenn A. Miller [verfasserIn] John Moore [verfasserIn] Derek O'Keeffe [verfasserIn] Jeffrey Palmer [verfasserIn] Federico Parisi [verfasserIn] Shyamal Patel [verfasserIn] Jack Po [verfasserIn] Benito L. Pugliese [verfasserIn] Thomas Quatieri [verfasserIn] Tauhidur Rahman [verfasserIn] Nathan Ramasarma [verfasserIn] John A. Rogers [verfasserIn] Guillermo U. Ruiz-Esparza [verfasserIn] Stefano Sapienza [verfasserIn] Gregory Schiurring [verfasserIn] Lee Schwamm [verfasserIn] Hadi Shafiee [verfasserIn] Sara Kelly Silacci [verfasserIn] Nathaniel M Sims [verfasserIn] Tanya Talkar [verfasserIn] William J. Tharion [verfasserIn] James A. Toombs [verfasserIn] Christopher Uschnig [verfasserIn] Gloria P. Vergara-Diaz [verfasserIn] Paul Wacnik [verfasserIn] May D. Wang [verfasserIn] James Welch [verfasserIn] Lina Williamson [verfasserIn] Ross Zafonte [verfasserIn] Adrian Zai [verfasserIn] Yuan-Ting Zhang [verfasserIn] Guillermo J. Tearney [verfasserIn] Rushdy Ahmad [verfasserIn] David R. Walt [verfasserIn] Paolo Bonato [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2020 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
In: IEEE Open Journal of Engineering in Medicine and Biology - IEEE, 2020, 1(2020), Seite 243-248 |
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| Übergeordnetes Werk: |
volume:1 ; year:2020 ; pages:243-248 |
| Links: |
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| DOI / URN: |
10.1109/OJEMB.2020.3015141 |
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| Katalog-ID: |
DOAJ051402637 |
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| 520 | |a Goal: The aim of the study herein reported was to review mobile health (mHealth) technologies and explore their use to monitor and mitigate the effects of the COVID-19 pandemic. Methods: A Task Force was assembled by recruiting individuals with expertise in electronic Patient-Reported Outcomes (ePRO), wearable sensors, and digital contact tracing technologies. Its members collected and discussed available information and summarized it in a series of reports. Results: The Task Force identified technologies that could be deployed in response to the COVID-19 pandemic and would likely be suitable for future pandemics. Criteria for their evaluation were agreed upon and applied to these systems. Conclusions: mHealth technologies are viable options to monitor COVID-19 patients and be used to predict symptom escalation for earlier intervention. These technologies could also be utilized to monitor individuals who are presumed non-infected and enable prediction of exposure to SARS-CoV-2, thus facilitating the prioritization of diagnostic testing. | ||
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10.1109/OJEMB.2020.3015141 doi (DE-627)DOAJ051402637 (DE-599)DOAJ9f4d73ef1b354d7baa82ecc18ae00e74 DE-627 ger DE-627 rakwb eng R858-859.7 R855-855.5 Catherine P. Adans-Dester verfasserin aut Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic? 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Goal: The aim of the study herein reported was to review mobile health (mHealth) technologies and explore their use to monitor and mitigate the effects of the COVID-19 pandemic. Methods: A Task Force was assembled by recruiting individuals with expertise in electronic Patient-Reported Outcomes (ePRO), wearable sensors, and digital contact tracing technologies. Its members collected and discussed available information and summarized it in a series of reports. Results: The Task Force identified technologies that could be deployed in response to the COVID-19 pandemic and would likely be suitable for future pandemics. Criteria for their evaluation were agreed upon and applied to these systems. Conclusions: mHealth technologies are viable options to monitor COVID-19 patients and be used to predict symptom escalation for earlier intervention. These technologies could also be utilized to monitor individuals who are presumed non-infected and enable prediction of exposure to SARS-CoV-2, thus facilitating the prioritization of diagnostic testing. COVID-19 digital contact tracing electronic patient reported outcomes (ePRO) mHealth technology wearable sensors Computer applications to medicine. Medical informatics Medical technology Stacy Bamberg verfasserin aut Francesco P. Bertacchi verfasserin aut Brian Caulfield verfasserin aut Kara Chappie verfasserin aut Danilo Demarchi verfasserin aut M. Kelley Erb verfasserin aut Juan Estrada verfasserin aut Eric E. Fabara verfasserin aut Michael Freni verfasserin aut Karl E. Friedl verfasserin aut Roozbeh Ghaffari verfasserin aut Geoffrey Gill verfasserin aut Mark S. Greenberg verfasserin aut Reed W. Hoyt verfasserin aut Emil Jovanov verfasserin aut Christoph M. Kanzler verfasserin aut Dina Katabi verfasserin aut Meredith Kernan verfasserin aut Colleen Kigin verfasserin aut Sunghoon I. Lee verfasserin aut Steffen Leonhardt verfasserin aut Nigel H. Lovell verfasserin aut Jose Mantilla verfasserin aut Thomas H. McCoy verfasserin aut Nell Meosky Luo verfasserin aut Glenn A. Miller verfasserin aut John Moore verfasserin aut Derek O'Keeffe verfasserin aut Jeffrey Palmer verfasserin aut Federico Parisi verfasserin aut Shyamal Patel verfasserin aut Jack Po verfasserin aut Benito L. Pugliese verfasserin aut Thomas Quatieri verfasserin aut Tauhidur Rahman verfasserin aut Nathan Ramasarma verfasserin aut John A. Rogers verfasserin aut Guillermo U. Ruiz-Esparza verfasserin aut Stefano Sapienza verfasserin aut Gregory Schiurring verfasserin aut Lee Schwamm verfasserin aut Hadi Shafiee verfasserin aut Sara Kelly Silacci verfasserin aut Nathaniel M Sims verfasserin aut Tanya Talkar verfasserin aut William J. Tharion verfasserin aut James A. Toombs verfasserin aut Christopher Uschnig verfasserin aut Gloria P. Vergara-Diaz verfasserin aut Paul Wacnik verfasserin aut May D. Wang verfasserin aut James Welch verfasserin aut Lina Williamson verfasserin aut Ross Zafonte verfasserin aut Adrian Zai verfasserin aut Yuan-Ting Zhang verfasserin aut Guillermo J. Tearney verfasserin aut Rushdy Ahmad verfasserin aut David R. Walt verfasserin aut Paolo Bonato verfasserin aut In IEEE Open Journal of Engineering in Medicine and Biology IEEE, 2020 1(2020), Seite 243-248 (DE-627)1693157721 (DE-600)3012072-X 26441276 nnns volume:1 year:2020 pages:243-248 https://doi.org/10.1109/OJEMB.2020.3015141 kostenfrei https://doaj.org/article/9f4d73ef1b354d7baa82ecc18ae00e74 kostenfrei https://ieeexplore.ieee.org/document/9162431/ kostenfrei https://doaj.org/toc/2644-1276 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 1 2020 243-248 |
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10.1109/OJEMB.2020.3015141 doi (DE-627)DOAJ051402637 (DE-599)DOAJ9f4d73ef1b354d7baa82ecc18ae00e74 DE-627 ger DE-627 rakwb eng R858-859.7 R855-855.5 Catherine P. Adans-Dester verfasserin aut Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic? 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Goal: The aim of the study herein reported was to review mobile health (mHealth) technologies and explore their use to monitor and mitigate the effects of the COVID-19 pandemic. Methods: A Task Force was assembled by recruiting individuals with expertise in electronic Patient-Reported Outcomes (ePRO), wearable sensors, and digital contact tracing technologies. Its members collected and discussed available information and summarized it in a series of reports. Results: The Task Force identified technologies that could be deployed in response to the COVID-19 pandemic and would likely be suitable for future pandemics. Criteria for their evaluation were agreed upon and applied to these systems. Conclusions: mHealth technologies are viable options to monitor COVID-19 patients and be used to predict symptom escalation for earlier intervention. These technologies could also be utilized to monitor individuals who are presumed non-infected and enable prediction of exposure to SARS-CoV-2, thus facilitating the prioritization of diagnostic testing. COVID-19 digital contact tracing electronic patient reported outcomes (ePRO) mHealth technology wearable sensors Computer applications to medicine. Medical informatics Medical technology Stacy Bamberg verfasserin aut Francesco P. Bertacchi verfasserin aut Brian Caulfield verfasserin aut Kara Chappie verfasserin aut Danilo Demarchi verfasserin aut M. Kelley Erb verfasserin aut Juan Estrada verfasserin aut Eric E. Fabara verfasserin aut Michael Freni verfasserin aut Karl E. Friedl verfasserin aut Roozbeh Ghaffari verfasserin aut Geoffrey Gill verfasserin aut Mark S. Greenberg verfasserin aut Reed W. Hoyt verfasserin aut Emil Jovanov verfasserin aut Christoph M. Kanzler verfasserin aut Dina Katabi verfasserin aut Meredith Kernan verfasserin aut Colleen Kigin verfasserin aut Sunghoon I. Lee verfasserin aut Steffen Leonhardt verfasserin aut Nigel H. Lovell verfasserin aut Jose Mantilla verfasserin aut Thomas H. McCoy verfasserin aut Nell Meosky Luo verfasserin aut Glenn A. Miller verfasserin aut John Moore verfasserin aut Derek O'Keeffe verfasserin aut Jeffrey Palmer verfasserin aut Federico Parisi verfasserin aut Shyamal Patel verfasserin aut Jack Po verfasserin aut Benito L. Pugliese verfasserin aut Thomas Quatieri verfasserin aut Tauhidur Rahman verfasserin aut Nathan Ramasarma verfasserin aut John A. Rogers verfasserin aut Guillermo U. Ruiz-Esparza verfasserin aut Stefano Sapienza verfasserin aut Gregory Schiurring verfasserin aut Lee Schwamm verfasserin aut Hadi Shafiee verfasserin aut Sara Kelly Silacci verfasserin aut Nathaniel M Sims verfasserin aut Tanya Talkar verfasserin aut William J. Tharion verfasserin aut James A. Toombs verfasserin aut Christopher Uschnig verfasserin aut Gloria P. Vergara-Diaz verfasserin aut Paul Wacnik verfasserin aut May D. Wang verfasserin aut James Welch verfasserin aut Lina Williamson verfasserin aut Ross Zafonte verfasserin aut Adrian Zai verfasserin aut Yuan-Ting Zhang verfasserin aut Guillermo J. Tearney verfasserin aut Rushdy Ahmad verfasserin aut David R. Walt verfasserin aut Paolo Bonato verfasserin aut In IEEE Open Journal of Engineering in Medicine and Biology IEEE, 2020 1(2020), Seite 243-248 (DE-627)1693157721 (DE-600)3012072-X 26441276 nnns volume:1 year:2020 pages:243-248 https://doi.org/10.1109/OJEMB.2020.3015141 kostenfrei https://doaj.org/article/9f4d73ef1b354d7baa82ecc18ae00e74 kostenfrei https://ieeexplore.ieee.org/document/9162431/ kostenfrei https://doaj.org/toc/2644-1276 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 1 2020 243-248 |
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10.1109/OJEMB.2020.3015141 doi (DE-627)DOAJ051402637 (DE-599)DOAJ9f4d73ef1b354d7baa82ecc18ae00e74 DE-627 ger DE-627 rakwb eng R858-859.7 R855-855.5 Catherine P. Adans-Dester verfasserin aut Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic? 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Goal: The aim of the study herein reported was to review mobile health (mHealth) technologies and explore their use to monitor and mitigate the effects of the COVID-19 pandemic. Methods: A Task Force was assembled by recruiting individuals with expertise in electronic Patient-Reported Outcomes (ePRO), wearable sensors, and digital contact tracing technologies. Its members collected and discussed available information and summarized it in a series of reports. Results: The Task Force identified technologies that could be deployed in response to the COVID-19 pandemic and would likely be suitable for future pandemics. Criteria for their evaluation were agreed upon and applied to these systems. Conclusions: mHealth technologies are viable options to monitor COVID-19 patients and be used to predict symptom escalation for earlier intervention. These technologies could also be utilized to monitor individuals who are presumed non-infected and enable prediction of exposure to SARS-CoV-2, thus facilitating the prioritization of diagnostic testing. COVID-19 digital contact tracing electronic patient reported outcomes (ePRO) mHealth technology wearable sensors Computer applications to medicine. Medical informatics Medical technology Stacy Bamberg verfasserin aut Francesco P. Bertacchi verfasserin aut Brian Caulfield verfasserin aut Kara Chappie verfasserin aut Danilo Demarchi verfasserin aut M. Kelley Erb verfasserin aut Juan Estrada verfasserin aut Eric E. Fabara verfasserin aut Michael Freni verfasserin aut Karl E. Friedl verfasserin aut Roozbeh Ghaffari verfasserin aut Geoffrey Gill verfasserin aut Mark S. Greenberg verfasserin aut Reed W. Hoyt verfasserin aut Emil Jovanov verfasserin aut Christoph M. Kanzler verfasserin aut Dina Katabi verfasserin aut Meredith Kernan verfasserin aut Colleen Kigin verfasserin aut Sunghoon I. Lee verfasserin aut Steffen Leonhardt verfasserin aut Nigel H. Lovell verfasserin aut Jose Mantilla verfasserin aut Thomas H. McCoy verfasserin aut Nell Meosky Luo verfasserin aut Glenn A. Miller verfasserin aut John Moore verfasserin aut Derek O'Keeffe verfasserin aut Jeffrey Palmer verfasserin aut Federico Parisi verfasserin aut Shyamal Patel verfasserin aut Jack Po verfasserin aut Benito L. Pugliese verfasserin aut Thomas Quatieri verfasserin aut Tauhidur Rahman verfasserin aut Nathan Ramasarma verfasserin aut John A. Rogers verfasserin aut Guillermo U. Ruiz-Esparza verfasserin aut Stefano Sapienza verfasserin aut Gregory Schiurring verfasserin aut Lee Schwamm verfasserin aut Hadi Shafiee verfasserin aut Sara Kelly Silacci verfasserin aut Nathaniel M Sims verfasserin aut Tanya Talkar verfasserin aut William J. Tharion verfasserin aut James A. Toombs verfasserin aut Christopher Uschnig verfasserin aut Gloria P. Vergara-Diaz verfasserin aut Paul Wacnik verfasserin aut May D. Wang verfasserin aut James Welch verfasserin aut Lina Williamson verfasserin aut Ross Zafonte verfasserin aut Adrian Zai verfasserin aut Yuan-Ting Zhang verfasserin aut Guillermo J. Tearney verfasserin aut Rushdy Ahmad verfasserin aut David R. Walt verfasserin aut Paolo Bonato verfasserin aut In IEEE Open Journal of Engineering in Medicine and Biology IEEE, 2020 1(2020), Seite 243-248 (DE-627)1693157721 (DE-600)3012072-X 26441276 nnns volume:1 year:2020 pages:243-248 https://doi.org/10.1109/OJEMB.2020.3015141 kostenfrei https://doaj.org/article/9f4d73ef1b354d7baa82ecc18ae00e74 kostenfrei https://ieeexplore.ieee.org/document/9162431/ kostenfrei https://doaj.org/toc/2644-1276 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 1 2020 243-248 |
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10.1109/OJEMB.2020.3015141 doi (DE-627)DOAJ051402637 (DE-599)DOAJ9f4d73ef1b354d7baa82ecc18ae00e74 DE-627 ger DE-627 rakwb eng R858-859.7 R855-855.5 Catherine P. Adans-Dester verfasserin aut Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic? 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Goal: The aim of the study herein reported was to review mobile health (mHealth) technologies and explore their use to monitor and mitigate the effects of the COVID-19 pandemic. Methods: A Task Force was assembled by recruiting individuals with expertise in electronic Patient-Reported Outcomes (ePRO), wearable sensors, and digital contact tracing technologies. Its members collected and discussed available information and summarized it in a series of reports. Results: The Task Force identified technologies that could be deployed in response to the COVID-19 pandemic and would likely be suitable for future pandemics. Criteria for their evaluation were agreed upon and applied to these systems. Conclusions: mHealth technologies are viable options to monitor COVID-19 patients and be used to predict symptom escalation for earlier intervention. These technologies could also be utilized to monitor individuals who are presumed non-infected and enable prediction of exposure to SARS-CoV-2, thus facilitating the prioritization of diagnostic testing. COVID-19 digital contact tracing electronic patient reported outcomes (ePRO) mHealth technology wearable sensors Computer applications to medicine. Medical informatics Medical technology Stacy Bamberg verfasserin aut Francesco P. Bertacchi verfasserin aut Brian Caulfield verfasserin aut Kara Chappie verfasserin aut Danilo Demarchi verfasserin aut M. Kelley Erb verfasserin aut Juan Estrada verfasserin aut Eric E. Fabara verfasserin aut Michael Freni verfasserin aut Karl E. Friedl verfasserin aut Roozbeh Ghaffari verfasserin aut Geoffrey Gill verfasserin aut Mark S. Greenberg verfasserin aut Reed W. Hoyt verfasserin aut Emil Jovanov verfasserin aut Christoph M. Kanzler verfasserin aut Dina Katabi verfasserin aut Meredith Kernan verfasserin aut Colleen Kigin verfasserin aut Sunghoon I. Lee verfasserin aut Steffen Leonhardt verfasserin aut Nigel H. Lovell verfasserin aut Jose Mantilla verfasserin aut Thomas H. McCoy verfasserin aut Nell Meosky Luo verfasserin aut Glenn A. Miller verfasserin aut John Moore verfasserin aut Derek O'Keeffe verfasserin aut Jeffrey Palmer verfasserin aut Federico Parisi verfasserin aut Shyamal Patel verfasserin aut Jack Po verfasserin aut Benito L. Pugliese verfasserin aut Thomas Quatieri verfasserin aut Tauhidur Rahman verfasserin aut Nathan Ramasarma verfasserin aut John A. Rogers verfasserin aut Guillermo U. Ruiz-Esparza verfasserin aut Stefano Sapienza verfasserin aut Gregory Schiurring verfasserin aut Lee Schwamm verfasserin aut Hadi Shafiee verfasserin aut Sara Kelly Silacci verfasserin aut Nathaniel M Sims verfasserin aut Tanya Talkar verfasserin aut William J. Tharion verfasserin aut James A. Toombs verfasserin aut Christopher Uschnig verfasserin aut Gloria P. Vergara-Diaz verfasserin aut Paul Wacnik verfasserin aut May D. Wang verfasserin aut James Welch verfasserin aut Lina Williamson verfasserin aut Ross Zafonte verfasserin aut Adrian Zai verfasserin aut Yuan-Ting Zhang verfasserin aut Guillermo J. Tearney verfasserin aut Rushdy Ahmad verfasserin aut David R. Walt verfasserin aut Paolo Bonato verfasserin aut In IEEE Open Journal of Engineering in Medicine and Biology IEEE, 2020 1(2020), Seite 243-248 (DE-627)1693157721 (DE-600)3012072-X 26441276 nnns volume:1 year:2020 pages:243-248 https://doi.org/10.1109/OJEMB.2020.3015141 kostenfrei https://doaj.org/article/9f4d73ef1b354d7baa82ecc18ae00e74 kostenfrei https://ieeexplore.ieee.org/document/9162431/ kostenfrei https://doaj.org/toc/2644-1276 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 1 2020 243-248 |
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Catherine P. Adans-Dester @@aut@@ Stacy Bamberg @@aut@@ Francesco P. Bertacchi @@aut@@ Brian Caulfield @@aut@@ Kara Chappie @@aut@@ Danilo Demarchi @@aut@@ M. Kelley Erb @@aut@@ Juan Estrada @@aut@@ Eric E. Fabara @@aut@@ Michael Freni @@aut@@ Karl E. Friedl @@aut@@ Roozbeh Ghaffari @@aut@@ Geoffrey Gill @@aut@@ Mark S. Greenberg @@aut@@ Reed W. Hoyt @@aut@@ Emil Jovanov @@aut@@ Christoph M. Kanzler @@aut@@ Dina Katabi @@aut@@ Meredith Kernan @@aut@@ Colleen Kigin @@aut@@ Sunghoon I. Lee @@aut@@ Steffen Leonhardt @@aut@@ Nigel H. Lovell @@aut@@ Jose Mantilla @@aut@@ Thomas H. McCoy @@aut@@ Nell Meosky Luo @@aut@@ Glenn A. Miller @@aut@@ John Moore @@aut@@ Derek O'Keeffe @@aut@@ Jeffrey Palmer @@aut@@ Federico Parisi @@aut@@ Shyamal Patel @@aut@@ Jack Po @@aut@@ Benito L. Pugliese @@aut@@ Thomas Quatieri @@aut@@ Tauhidur Rahman @@aut@@ Nathan Ramasarma @@aut@@ John A. Rogers @@aut@@ Guillermo U. Ruiz-Esparza @@aut@@ Stefano Sapienza @@aut@@ Gregory Schiurring @@aut@@ Lee Schwamm @@aut@@ Hadi Shafiee @@aut@@ Sara Kelly Silacci @@aut@@ Nathaniel M Sims @@aut@@ Tanya Talkar @@aut@@ William J. Tharion @@aut@@ James A. Toombs @@aut@@ Christopher Uschnig @@aut@@ Gloria P. Vergara-Diaz @@aut@@ Paul Wacnik @@aut@@ May D. Wang @@aut@@ James Welch @@aut@@ Lina Williamson @@aut@@ Ross Zafonte @@aut@@ Adrian Zai @@aut@@ Yuan-Ting Zhang @@aut@@ Guillermo J. Tearney @@aut@@ Rushdy Ahmad @@aut@@ David R. Walt @@aut@@ Paolo Bonato @@aut@@ |
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Catherine P. Adans-Dester misc R858-859.7 misc R855-855.5 misc COVID-19 misc digital contact tracing misc electronic patient reported outcomes (ePRO) misc mHealth technology misc wearable sensors misc Computer applications to medicine. Medical informatics misc Medical technology Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic? |
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R858-859.7 R855-855.5 Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic? COVID-19 digital contact tracing electronic patient reported outcomes (ePRO) mHealth technology wearable sensors |
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Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic? |
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Catherine P. Adans-Dester |
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Catherine P. Adans-Dester Stacy Bamberg Francesco P. Bertacchi Brian Caulfield Kara Chappie Danilo Demarchi M. Kelley Erb Juan Estrada Eric E. Fabara Michael Freni Karl E. Friedl Roozbeh Ghaffari Geoffrey Gill Mark S. Greenberg Reed W. Hoyt Emil Jovanov Christoph M. Kanzler Dina Katabi Meredith Kernan Colleen Kigin Sunghoon I. Lee Steffen Leonhardt Nigel H. Lovell Jose Mantilla Thomas H. McCoy Nell Meosky Luo Glenn A. Miller John Moore Derek O'Keeffe Jeffrey Palmer Federico Parisi Shyamal Patel Jack Po Benito L. Pugliese Thomas Quatieri Tauhidur Rahman Nathan Ramasarma John A. Rogers Guillermo U. Ruiz-Esparza Stefano Sapienza Gregory Schiurring Lee Schwamm Hadi Shafiee Sara Kelly Silacci Nathaniel M Sims Tanya Talkar William J. Tharion James A. Toombs Christopher Uschnig Gloria P. Vergara-Diaz Paul Wacnik May D. Wang James Welch Lina Williamson Ross Zafonte Adrian Zai Yuan-Ting Zhang Guillermo J. Tearney Rushdy Ahmad David R. Walt Paolo Bonato |
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can mhealth technology help mitigate the effects of the covid-19 pandemic? |
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Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic? |
| abstract |
Goal: The aim of the study herein reported was to review mobile health (mHealth) technologies and explore their use to monitor and mitigate the effects of the COVID-19 pandemic. Methods: A Task Force was assembled by recruiting individuals with expertise in electronic Patient-Reported Outcomes (ePRO), wearable sensors, and digital contact tracing technologies. Its members collected and discussed available information and summarized it in a series of reports. Results: The Task Force identified technologies that could be deployed in response to the COVID-19 pandemic and would likely be suitable for future pandemics. Criteria for their evaluation were agreed upon and applied to these systems. Conclusions: mHealth technologies are viable options to monitor COVID-19 patients and be used to predict symptom escalation for earlier intervention. These technologies could also be utilized to monitor individuals who are presumed non-infected and enable prediction of exposure to SARS-CoV-2, thus facilitating the prioritization of diagnostic testing. |
| abstractGer |
Goal: The aim of the study herein reported was to review mobile health (mHealth) technologies and explore their use to monitor and mitigate the effects of the COVID-19 pandemic. Methods: A Task Force was assembled by recruiting individuals with expertise in electronic Patient-Reported Outcomes (ePRO), wearable sensors, and digital contact tracing technologies. Its members collected and discussed available information and summarized it in a series of reports. Results: The Task Force identified technologies that could be deployed in response to the COVID-19 pandemic and would likely be suitable for future pandemics. Criteria for their evaluation were agreed upon and applied to these systems. Conclusions: mHealth technologies are viable options to monitor COVID-19 patients and be used to predict symptom escalation for earlier intervention. These technologies could also be utilized to monitor individuals who are presumed non-infected and enable prediction of exposure to SARS-CoV-2, thus facilitating the prioritization of diagnostic testing. |
| abstract_unstemmed |
Goal: The aim of the study herein reported was to review mobile health (mHealth) technologies and explore their use to monitor and mitigate the effects of the COVID-19 pandemic. Methods: A Task Force was assembled by recruiting individuals with expertise in electronic Patient-Reported Outcomes (ePRO), wearable sensors, and digital contact tracing technologies. Its members collected and discussed available information and summarized it in a series of reports. Results: The Task Force identified technologies that could be deployed in response to the COVID-19 pandemic and would likely be suitable for future pandemics. Criteria for their evaluation were agreed upon and applied to these systems. Conclusions: mHealth technologies are viable options to monitor COVID-19 patients and be used to predict symptom escalation for earlier intervention. These technologies could also be utilized to monitor individuals who are presumed non-infected and enable prediction of exposure to SARS-CoV-2, thus facilitating the prioritization of diagnostic testing. |
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Can mHealth Technology Help Mitigate the Effects of the COVID-19 Pandemic? |
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https://doi.org/10.1109/OJEMB.2020.3015141 https://doaj.org/article/9f4d73ef1b354d7baa82ecc18ae00e74 https://ieeexplore.ieee.org/document/9162431/ https://doaj.org/toc/2644-1276 |
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Stacy Bamberg Francesco P. Bertacchi Brian Caulfield Kara Chappie Danilo Demarchi M. Kelley Erb Juan Estrada Eric E. Fabara Michael Freni Karl E. Friedl Roozbeh Ghaffari Geoffrey Gill Mark S. Greenberg Reed W. Hoyt Emil Jovanov Christoph M. Kanzler Dina Katabi Meredith Kernan Colleen Kigin Sunghoon I. Lee Steffen Leonhardt Nigel H. Lovell Jose Mantilla Thomas H. McCoy Nell Meosky Luo Glenn A. Miller John Moore Derek O'Keeffe Jeffrey Palmer Federico Parisi Shyamal Patel Jack Po Benito L. Pugliese Thomas Quatieri Tauhidur Rahman Nathan Ramasarma John A. Rogers Guillermo U. Ruiz-Esparza Stefano Sapienza Gregory Schiurring Lee Schwamm Hadi Shafiee Sara Kelly Silacci Nathaniel M Sims Tanya Talkar William J. Tharion James A. Toombs Christopher Uschnig Gloria P. Vergara-Diaz Paul Wacnik May D. Wang James Welch Lina Williamson Ross Zafonte Adrian Zai Yuan-Ting Zhang Guillermo J. Tearney Rushdy Ahmad David R. Walt Paolo Bonato |
| author2Str |
Stacy Bamberg Francesco P. Bertacchi Brian Caulfield Kara Chappie Danilo Demarchi M. Kelley Erb Juan Estrada Eric E. Fabara Michael Freni Karl E. Friedl Roozbeh Ghaffari Geoffrey Gill Mark S. Greenberg Reed W. Hoyt Emil Jovanov Christoph M. Kanzler Dina Katabi Meredith Kernan Colleen Kigin Sunghoon I. Lee Steffen Leonhardt Nigel H. Lovell Jose Mantilla Thomas H. McCoy Nell Meosky Luo Glenn A. Miller John Moore Derek O'Keeffe Jeffrey Palmer Federico Parisi Shyamal Patel Jack Po Benito L. Pugliese Thomas Quatieri Tauhidur Rahman Nathan Ramasarma John A. Rogers Guillermo U. Ruiz-Esparza Stefano Sapienza Gregory Schiurring Lee Schwamm Hadi Shafiee Sara Kelly Silacci Nathaniel M Sims Tanya Talkar William J. Tharion James A. Toombs Christopher Uschnig Gloria P. Vergara-Diaz Paul Wacnik May D. Wang James Welch Lina Williamson Ross Zafonte Adrian Zai Yuan-Ting Zhang Guillermo J. Tearney Rushdy Ahmad David R. Walt Paolo Bonato |
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R - General Medicine |
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| doi_str |
10.1109/OJEMB.2020.3015141 |
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R858-859.7 |
| up_date |
2024-07-03T20:09:14.257Z |
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1803589888781582336 |
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| score |
7.4007654 |