A context-aware platform for comprehensive care of elderly people: Proposed architecture

Bravo‐Torres, Jack F.; Ordoñez-Ordoñez, Jorge O.; Gallegos-Segovia, Pablo L.; Vintimilla-Tapia, Paul E.; López‐Nores, Martín; Blanco‐Fernández, Yolanda

doi:10.1109/chilecon.2017.8229507

Cited by 5 publications

(5 citation statements)

References 19 publications

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“…Recommendations with a lower DOC are more efficient for the user’s health, but recommendations with a high DOC could convince users to believe that the recommended action is worth doing. Other approaches used are structured interviews [ 58 ], ranking [ 86 , 89 ], asking for unstructured feedback [ 40 , 88 ], and focus group discussions [ 87 ]. Finally, 3 studies [ 15 , 75 , 90 ] evaluated their system through a heuristic evaluation with expert users.…”

Section: Resultsmentioning

confidence: 99%

“…When health conditions are known, the system knows which measurements need to be monitored. A total of 7 studies used a content-based technique to recommend educational content [15,72,87], activities [32,86], reading materials [54], or nutritional advice [63].…”

Section: Recommender Techniques In Practicementioning

confidence: 99%

“…Distribution of the interfaces used among the different health recommender systems (n=34). ,34,35,40,44,48,56,58,66,69,77,78,[82][83][84]86,88,97] …”

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confidence: 99%

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Health Recommender Systems: Systematic Review

Croon¹,

Houdt²,

Htun³

et al. 2021

J Med Internet Res

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Background Health recommender systems (HRSs) offer the potential to motivate and engage users to change their behavior by sharing better choices and actionable knowledge based on observed user behavior. Objective We aim to review HRSs targeting nonmedical professionals (laypersons) to better understand the current state of the art and identify both the main trends and the gaps with respect to current implementations. Methods We conducted a systematic literature review according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and synthesized the results. A total of 73 published studies that reported both an implementation and evaluation of an HRS targeted to laypersons were included and analyzed in this review. Results Recommended items were classified into four major categories: lifestyle, nutrition, general health care information, and specific health conditions. The majority of HRSs use hybrid recommendation algorithms. Evaluations of HRSs vary greatly; half of the studies only evaluated the algorithm with various metrics, whereas others performed full-scale randomized controlled trials or conducted in-the-wild studies to evaluate the impact of HRSs, thereby showing that the field is slowly maturing. On the basis of our review, we derived five reporting guidelines that can serve as a reference frame for future HRS studies. HRS studies should clarify who the target user is and to whom the recommendations apply, what is recommended and how the recommendations are presented to the user, where the data set can be found, what algorithms were used to calculate the recommendations, and what evaluation protocol was used. Conclusions There is significant opportunity for an HRS to inform and guide health actions. Through this review, we promote the discussion of ways to augment HRS research by recommending a reference frame with five design guidelines.

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Section: Resultsmentioning

confidence: 99%

Section: Recommender Techniques In Practicementioning

confidence: 99%

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Health Recommender Systems: Systematic Review

Croon¹,

Houdt²,

Htun³

et al. 2021

J Med Internet Res

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“…In our review, we found that only 10 studies recruited users and asked them to be involved in HRS development. For example, in the study conducted by Bravo-Torres [16], the design was developed following recommendations given by 25 end users. Moreover, to verify the operation and use of the application, several tests were carried out on a total of 25 older adults.…”

Section: Principal Findingsmentioning

confidence: 99%

Development and Evaluation of Health Recommender Systems: Systematic Scoping Review and Evidence Mapping

Sun¹,

Ji²,

Zhou³

et al. 2023

J Med Internet Res

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Background Health recommender systems (HRSs) are information retrieval systems that provide users with relevant items according to the users’ needs, which can motivate and engage users to change their behavior. Objective This study aimed to identify the development and evaluation of HRSs and create an evidence map. Methods A total of 6 databases were searched to identify HRSs reported in studies from inception up to June 30, 2022, followed by forward citation and grey literature searches. Titles, abstracts, and full texts were screened independently by 2 reviewers, with discrepancies resolved by a third reviewer, when necessary. Data extraction was performed by one reviewer and checked by a second reviewer. This review was conducted in accordance with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) statement. Results A total of 51 studies were included for data extraction. Recommender systems were used across different health domains, such as general health promotion, lifestyle, and generic health service. A total of 23 studies had reported the use of a combination of recommender techniques, classified as hybrid recommender systems, which are the most commonly used recommender techniques in HRSs. In the HRS design stage, only 10 of 51 (19.6%) recommender systems considered personal preferences of end users in the design or development of the system; a total of 29 studies reported the user interface of HRSs, and most HRSs worked on users’ mobile interfaces, usually a mobile app. Two categories of HRS evaluations were used, and evaluations of HRSs varied greatly; 62.7% (32/51) of the studies used the offline evaluations using computational methods (no user), and 33.3% (17/51) of the studies included end users in their HRS evaluation. Conclusions Through this scoping review, nonmedical professionals and policy makers can visualize and better understand HRSs for future studies. The health care professionals and the end users should be encouraged to participate in the future design and development of HRSs to optimize their utility and successful implementation. Detailed evaluations of HRSs in a user-centered approach are needed in future studies.

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“…SAFER-LIM is an upgrade of the SAFER platform, which provides tools to ensure the integral care of older adults. Its main difference from the original version is justified by the evolution of its features (see [1]), three key points are covered to avoid any type of alteration in the well-being of the elderly: linkage with society, interaction with people of the same age and monitoring of health status. As can be seen in Fig.…”

Section: Safer-lim: Description Of the Proposalmentioning

confidence: 99%

SAFER-LIM: A Platform for Assistance, Care and Social Integration for the Elderly

Lema-Sarmiento

Calle-Romero

Gallegos-Segovia

et al. 2020

Communications in Computer and Information Science

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The steady increase in the world's older adult population is about to become one of the most critical social transformations of the 21st century, demanding significant adaptations of each nation's health and social systems. Consequently, from the various needs reflected by this demographic change, SAFER-LIM emerges, a Web platform based on three axes that guarantee the correct development of each individual during his/her aging: linkage with society, interaction with his/her peers and monitoring of the state of health. From there, a virtual space is created centralized in the elderly that is shared with doctors, caregivers and family members. On the one hand, the social requirements are satisfied thanks to the addition of friends, creation of events and recommendation of places, promoting the enhancement of spaces and places destined for the senescent. On the other hand, with respect to the state of health, has designed a network of e-Health sensors for doctors that process and record measurements on biological variables of each elderly, following a model based on user profiles. Finally, in general, caregivers or relatives can see in real time the geographic location of the older adult and receive alerts about the change of routes or the abandonment of safe areas (geofences). The results obtained on the deployment of SAFER-LIM in an elderly community show positive impressions about its use.

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A context-aware platform for comprehensive care of elderly people: Proposed architecture

Cited by 5 publications

References 19 publications

Health Recommender Systems: Systematic Review

Health Recommender Systems: Systematic Review

Development and Evaluation of Health Recommender Systems: Systematic Scoping Review and Evidence Mapping

SAFER-LIM: A Platform for Assistance, Care and Social Integration for the Elderly

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