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research-article

Conceptualization of a personalized ecoach for wellness promotion

Authors:

Santiago Martinez,

Dian TjondronegoroAuthors Info & Claims

PervasiveHealth '17: Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare

Pages 365 - 374

https://doi.org/10.1145/3154862.3154930

Published: 23 May 2017 Publication History

Abstract

Evidence-based health promotion programs implement clinical practice guidelines built upon results of clinical trials with a definite number of participants, collected during a specific period of time. Wearable technologies allow for continuous observation of wellness parameters of multiple citizens, combined with monitoring of activities and context parameters involved in citizens' wellness. A statistical inference model can describe the relation between multidimensional activities and context parameters, the wellness of an individual and a comparable reference group, utilizing machine learning techniques and knowledge from continuous observations of multiple citizens.

This paper presents a holistic concept of a coach system, namely eCoach, that combines specialized medical evidence available from randomized control trials, with individual and reference knowledge to create and reinforce wellness-based recommendations. The eCoach adapts these recommendations in a continuous personalized coaching dialog addressing citizen's needs and preferences.

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Published In

cover image ACM Other conferences

PervasiveHealth '17: Proceedings of the 11th EAI International Conference on Pervasive Computing Technologies for Healthcare

May 2017

503 pages

ISBN:9781450363631

DOI:10.1145/3154862

General Chairs:
Nuria Oliver
Vodafone, Data-Pop Alliance
,
Mary Czerwinski
Visualization and Interaction (VIBE) Research Group

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 23 May 2017

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PervasiveHealth '17

PervasiveHealth '17: 11th EAI International Conference on Pervasive Computing Technologies for Healthcare

May 23 - 26, 2017

Barcelona, Spain

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Overall Acceptance Rate 55 of 116 submissions, 47%

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Cited By

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https://doi.org/10.1109/ICCSAI59793.2023.10421130
Chatterjee APrinz A(2022)Personalized Recommendations for Physical Activity e-Coaching (OntoRecoModel): Ontological ModelingJMIR Medical Informatics10.2196/3384710:6(e33847)Online publication date: 23-Jun-2022
https://doi.org/10.2196/33847
Singh NDube SVarshney UBourgeois A(2022)A comprehensive mobile health intervention to prevent and manage the complexities of opioid useInternational Journal of Medical Informatics10.1016/j.ijmedinf.2022.104792164(104792)Online publication date: Aug-2022
https://doi.org/10.1016/j.ijmedinf.2022.104792
Sarriegi JIraola AÁlvarez Sánchez RGraña MRebescher KEpelde GHopper LCarroll JIanes PGasperini BPilla FMattei WTessarolo FPetsani DBamidis PKonstantinidis E(2021)COLAEVA: Visual Analytics and Data Mining Web-Based Tool for Virtual Coaching of Older Adult PopulationsSensors10.3390/s2123799121:23(7991)Online publication date: 30-Nov-2021
https://doi.org/10.3390/s21237991
Chatterjee APrinz AGerdes MMartinez S(2021)Digital Interventions on Healthy Lifestyle Management: Systematic Review (Preprint)Journal of Medical Internet Research10.2196/26931Online publication date: 4-Jan-2021
https://doi.org/10.2196/26931
Chatterjee AGerdes MPrinz AMartinez S(2021)Comparing Performance of Ensemble-Based Machine Learning Algorithms to Identify Potential Obesity Risk Factors from Public Health DatasetsEmerging Technologies in Data Mining and Information Security10.1007/978-981-15-9927-9_26(253-269)Online publication date: 29-Jun-2021
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Chatterjee AGerdes MMartinez S(2020)Identification of Risk Factors Associated with Obesity and Overweight—A Machine Learning OverviewSensors10.3390/s2009273420:9(2734)Online publication date: 11-May-2020
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Santamaria-Granados LMendoza-Moreno JRamirez-Gonzalez G(2020)Tourist Recommender Systems Based on Emotion Recognition—A Scientometric ReviewFuture Internet10.3390/fi1301000213:1(2)Online publication date: 24-Dec-2020
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Chatterjee APrinz AGerdes MMartinez S(2020)An Automatic Ontology-based Approach to Support Logical Representation of Observable and Measurable Data for Healthy Lifestyle Management Targeting Obesity as a Case Study: From Theory to Implementation (Preprint)Journal of Medical Internet Research10.2196/24656Online publication date: 29-Sep-2020
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Chatterjee AGerdes MPrinz AMartinez S(2020)Human Coaching Methodologies for Automatic Coaching (eCoaching) as Behavior Intervention with Information and Communication Technologies: Systematic Review (Preprint)Journal of Medical Internet Research10.2196/23533Online publication date: 14-Aug-2020
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