A reference architecture for personalized and self-adaptive e-health apps

Eoin Martino Grua; Martina De Sanctis; Patricia Lago

doi:10.1007/978-3-030-59155-7_15

A reference architecture for personalized and self-adaptive e-health apps

Eoin Martino Grua^*, Martina De Sanctis, Patricia Lago

^*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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Abstract

A wealth of e-Health mobile apps are available for many purposes, such as life style improvement, mental coaching, etc. The interventions, prompts, and encouragements of e-Health apps sometimes take context into account (e.g., previous interactions or geographical location of the user), but they still tend to be rigid, e.g., by using fixed rule sets or being not sufficiently tailored towards individuals. Personalization to the different users’ characteristics and run-time adaptation to their changing needs and context provide a great opportunity for getting users continuously engaged and active, eventually leading to better physical and mental conditions. This paper presents a reference architecture for enabling AI-based personalization and self-adaptation of mobile apps for e-Health. The reference architecture makes use of multiple MAPE loops operating at different levels of granularity and for different purposes.

Original language	English
Title of host publication	Software Architecture
Subtitle of host publication	14th European Conference, ECSA 2020 Tracks and Workshops, L'Aquila, Italy, September 14–18, 2020, Proceedings
Editors	Henry Muccini, Mirco Franzago, Paris Avgeriou, Barbora Buhnova, Javier Camara, Mauro Caporuscio, Anne Koziolek, Patrizia Scandurra, Catia Trubiani, Danny Weyns, Uwe Zdun
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	195-209
Number of pages	15
ISBN (Electronic)	9783030591557
ISBN (Print)	9783030591540
DOIs	https://doi.org/10.1007/978-3-030-59155-7_15
Publication status	Published - 2020
Event	14th European Conference on Software Architecture,ECSA 2020 - L'Aquila, Italy Duration: 14 Sept 2020 → 18 Sept 2020

Publication series

Name	Communications in Computer and Information Science
Volume	1269 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	14th European Conference on Software Architecture,ECSA 2020
Country/Territory	Italy
City	L'Aquila
Period	14/09/20 → 18/09/20

Keywords

e-Health
Mobile apps
Personalization
Reference architecture
Self-adaptive systems

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10.1007/978-3-030-59155-7_15

Grua2020_Chapter_AReferenceArchitectureForPersonalizedAndSelfAdaptiveEHealthAppsFinal published version, 486 KBLicence: Article 25fa Dutch Copyright Act

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Grua, E. M., De Sanctis, M., & Lago, P. (2020). A reference architecture for personalized and self-adaptive e-health apps. In H. Muccini, M. Franzago, P. Avgeriou, B. Buhnova, J. Camara, M. Caporuscio, A. Koziolek, P. Scandurra, C. Trubiani, D. Weyns, & U. Zdun (Eds.), Software Architecture: 14th European Conference, ECSA 2020 Tracks and Workshops, L'Aquila, Italy, September 14–18, 2020, Proceedings (pp. 195-209). (Communications in Computer and Information Science; Vol. 1269 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-59155-7_15

Grua, Eoin Martino ; De Sanctis, Martina ; Lago, Patricia. / A reference architecture for personalized and self-adaptive e-health apps. Software Architecture: 14th European Conference, ECSA 2020 Tracks and Workshops, L'Aquila, Italy, September 14–18, 2020, Proceedings. editor / Henry Muccini ; Mirco Franzago ; Paris Avgeriou ; Barbora Buhnova ; Javier Camara ; Mauro Caporuscio ; Anne Koziolek ; Patrizia Scandurra ; Catia Trubiani ; Danny Weyns ; Uwe Zdun. Springer Science and Business Media Deutschland GmbH, 2020. pp. 195-209 (Communications in Computer and Information Science).

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abstract = "A wealth of e-Health mobile apps are available for many purposes, such as life style improvement, mental coaching, etc. The interventions, prompts, and encouragements of e-Health apps sometimes take context into account (e.g., previous interactions or geographical location of the user), but they still tend to be rigid, e.g., by using fixed rule sets or being not sufficiently tailored towards individuals. Personalization to the different users{\textquoteright} characteristics and run-time adaptation to their changing needs and context provide a great opportunity for getting users continuously engaged and active, eventually leading to better physical and mental conditions. This paper presents a reference architecture for enabling AI-based personalization and self-adaptation of mobile apps for e-Health. The reference architecture makes use of multiple MAPE loops operating at different levels of granularity and for different purposes.",

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doi = "10.1007/978-3-030-59155-7_15",

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editor = "Henry Muccini and Mirco Franzago and Paris Avgeriou and Barbora Buhnova and Javier Camara and Mauro Caporuscio and Anne Koziolek and Patrizia Scandurra and Catia Trubiani and Danny Weyns and Uwe Zdun",

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Grua, EM, De Sanctis, M & Lago, P 2020, A reference architecture for personalized and self-adaptive e-health apps. in H Muccini, M Franzago, P Avgeriou, B Buhnova, J Camara, M Caporuscio, A Koziolek, P Scandurra, C Trubiani, D Weyns & U Zdun (eds), Software Architecture: 14th European Conference, ECSA 2020 Tracks and Workshops, L'Aquila, Italy, September 14–18, 2020, Proceedings. Communications in Computer and Information Science, vol. 1269 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 195-209, 14th European Conference on Software Architecture,ECSA 2020, L'Aquila, Italy, 14/09/20. https://doi.org/10.1007/978-3-030-59155-7_15

A reference architecture for personalized and self-adaptive e-health apps. / Grua, Eoin Martino; De Sanctis, Martina; Lago, Patricia.
Software Architecture: 14th European Conference, ECSA 2020 Tracks and Workshops, L'Aquila, Italy, September 14–18, 2020, Proceedings. ed. / Henry Muccini; Mirco Franzago; Paris Avgeriou; Barbora Buhnova; Javier Camara; Mauro Caporuscio; Anne Koziolek; Patrizia Scandurra; Catia Trubiani; Danny Weyns; Uwe Zdun. Springer Science and Business Media Deutschland GmbH, 2020. p. 195-209 (Communications in Computer and Information Science; Vol. 1269 CCIS).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

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AU - De Sanctis, Martina

AU - Lago, Patricia

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N2 - A wealth of e-Health mobile apps are available for many purposes, such as life style improvement, mental coaching, etc. The interventions, prompts, and encouragements of e-Health apps sometimes take context into account (e.g., previous interactions or geographical location of the user), but they still tend to be rigid, e.g., by using fixed rule sets or being not sufficiently tailored towards individuals. Personalization to the different users’ characteristics and run-time adaptation to their changing needs and context provide a great opportunity for getting users continuously engaged and active, eventually leading to better physical and mental conditions. This paper presents a reference architecture for enabling AI-based personalization and self-adaptation of mobile apps for e-Health. The reference architecture makes use of multiple MAPE loops operating at different levels of granularity and for different purposes.

AB - A wealth of e-Health mobile apps are available for many purposes, such as life style improvement, mental coaching, etc. The interventions, prompts, and encouragements of e-Health apps sometimes take context into account (e.g., previous interactions or geographical location of the user), but they still tend to be rigid, e.g., by using fixed rule sets or being not sufficiently tailored towards individuals. Personalization to the different users’ characteristics and run-time adaptation to their changing needs and context provide a great opportunity for getting users continuously engaged and active, eventually leading to better physical and mental conditions. This paper presents a reference architecture for enabling AI-based personalization and self-adaptation of mobile apps for e-Health. The reference architecture makes use of multiple MAPE loops operating at different levels of granularity and for different purposes.

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Grua EM, De Sanctis M, Lago P. A reference architecture for personalized and self-adaptive e-health apps. In Muccini H, Franzago M, Avgeriou P, Buhnova B, Camara J, Caporuscio M, Koziolek A, Scandurra P, Trubiani C, Weyns D, Zdun U, editors, Software Architecture: 14th European Conference, ECSA 2020 Tracks and Workshops, L'Aquila, Italy, September 14–18, 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. p. 195-209. (Communications in Computer and Information Science). Epub 2020 Sept 7. doi: 10.1007/978-3-030-59155-7_15

A reference architecture for personalized and self-adaptive e-health apps

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