A recommender system for behavioral change in 60-70-year-old adults

Pierpaolo Palumbo; Luca Cattelani; Federica Fusco; Mirjam Pijnappels; Lorenzo Chiari; Federico Chesani; Sabato Mellone

A recommender system for behavioral change in 60-70-year-old adults

Pierpaolo Palumbo, Luca Cattelani, Federica Fusco, Mirjam Pijnappels, Lorenzo Chiari, Federico Chesani, Sabato Mellone

Research output: Contribution to journal › Conference article › Scientific › peer-review

11 Downloads (Pure)

Abstract

Early old age (60-70 years old) is a particular period of life when possible habit modifications may occur, often related to job retirement. While taking up a more sedentary lifestyle may be pernicious for health, changing behavior by introducing simple exercises within daily life routines can effectively prevent age-related functional decline. This article presents the Profiling Tool, a system that provides 60-70-year-old adults with personalized recommendations to integrate simple activities, promoting balance, strength, and physical activity into their daily life. Its first implementation has been designed on information from literature, data from previously available longitudinal datasets, and experts' opinions. It has been deployed within a randomized controlled trial. Strategies for its update are based on model-based reinforcement learning approaches.

Original language	English
Pages (from-to)	69-80
Number of pages	12
Journal	CEUR Workshop Proceedings
Volume	2804
Publication status	Published - 2020
Publication type	A1 Journal article-refereed
Event	2020 Italian Workshop on Artificial Intelligence for an Ageing Society, AIxAS 2020 - Virtual, Online Duration: 25 Nov 2020 → 27 Nov 2020

Keywords

Ageing
Behavioral change
Functional decline
Prevention
Recommender system

Publication forum classification

Publication forum level 1

ASJC Scopus subject areas

General Computer Science

Access to Document

paper5Final published version, 808 KBLicence: CC BY

http://ceur-ws.org/Vol-2804/paper5.pdfLicence: CC BY
https://urn.fi/URN:NBN:fi:tuni-202201171362Licence: CC BY

Cite this

@article{afab9ff90d4e4e6e9e579fbc2911dd04,

title = "A recommender system for behavioral change in 60-70-year-old adults",

abstract = "Early old age (60-70 years old) is a particular period of life when possible habit modifications may occur, often related to job retirement. While taking up a more sedentary lifestyle may be pernicious for health, changing behavior by introducing simple exercises within daily life routines can effectively prevent age-related functional decline. This article presents the Profiling Tool, a system that provides 60-70-year-old adults with personalized recommendations to integrate simple activities, promoting balance, strength, and physical activity into their daily life. Its first implementation has been designed on information from literature, data from previously available longitudinal datasets, and experts' opinions. It has been deployed within a randomized controlled trial. Strategies for its update are based on model-based reinforcement learning approaches.",

keywords = "Ageing, Behavioral change, Functional decline, Prevention, Recommender system",

author = "Pierpaolo Palumbo and Luca Cattelani and Federica Fusco and Mirjam Pijnappels and Lorenzo Chiari and Federico Chesani and Sabato Mellone",

note = "Funding Information: This study has been partly funded by the European Commission under the project 'PreventIT' (2016?2018, grant number 689238) responding to the Horizon 2020, Personalised Health and Care call PHC-21: Advancing active and healthy aging with ICT: Early risk detection and intervention. Publisher Copyright: {\textcopyright} 2020 Copyright for this paper by its authors.; 2020 Italian Workshop on Artificial Intelligence for an Ageing Society, AIxAS 2020 ; Conference date: 25-11-2020 Through 27-11-2020",

year = "2020",

language = "English",

volume = "2804",

pages = "69--80",

}

TY - JOUR

T1 - A recommender system for behavioral change in 60-70-year-old adults

AU - Palumbo, Pierpaolo

AU - Cattelani, Luca

AU - Fusco, Federica

AU - Pijnappels, Mirjam

AU - Chiari, Lorenzo

AU - Chesani, Federico

AU - Mellone, Sabato

N1 - Funding Information: This study has been partly funded by the European Commission under the project 'PreventIT' (2016?2018, grant number 689238) responding to the Horizon 2020, Personalised Health and Care call PHC-21: Advancing active and healthy aging with ICT: Early risk detection and intervention. Publisher Copyright: © 2020 Copyright for this paper by its authors.

PY - 2020

Y1 - 2020

N2 - Early old age (60-70 years old) is a particular period of life when possible habit modifications may occur, often related to job retirement. While taking up a more sedentary lifestyle may be pernicious for health, changing behavior by introducing simple exercises within daily life routines can effectively prevent age-related functional decline. This article presents the Profiling Tool, a system that provides 60-70-year-old adults with personalized recommendations to integrate simple activities, promoting balance, strength, and physical activity into their daily life. Its first implementation has been designed on information from literature, data from previously available longitudinal datasets, and experts' opinions. It has been deployed within a randomized controlled trial. Strategies for its update are based on model-based reinforcement learning approaches.

AB - Early old age (60-70 years old) is a particular period of life when possible habit modifications may occur, often related to job retirement. While taking up a more sedentary lifestyle may be pernicious for health, changing behavior by introducing simple exercises within daily life routines can effectively prevent age-related functional decline. This article presents the Profiling Tool, a system that provides 60-70-year-old adults with personalized recommendations to integrate simple activities, promoting balance, strength, and physical activity into their daily life. Its first implementation has been designed on information from literature, data from previously available longitudinal datasets, and experts' opinions. It has been deployed within a randomized controlled trial. Strategies for its update are based on model-based reinforcement learning approaches.

KW - Ageing

KW - Behavioral change

KW - Functional decline

KW - Prevention

KW - Recommender system

M3 - Conference article

AN - SCOPUS:85100875037

SN - 1613-0073

VL - 2804

SP - 69

EP - 80

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

T2 - 2020 Italian Workshop on Artificial Intelligence for an Ageing Society, AIxAS 2020

Y2 - 25 November 2020 through 27 November 2020

ER -

A recommender system for behavioral change in 60-70-year-old adults

Abstract

Keywords

Publication forum classification

ASJC Scopus subject areas

Access to Document

Fingerprint

Cite this