scholarly journals Context-aware mobile app for the multidimensional assessment of the elderly

2018 ◽  
Author(s):  
Javier Berrocal ◽  
Jose Garcia-Alonso ◽  
Juan M. Murillo ◽  
David Mendes ◽  
Cesar Fonseca ◽  
...  
Keyword(s):  
The Elderly ◽  
Mobile App ◽  
Context Aware ◽  
Multidimensional Assessment

A context-aware decision-support system in clinical pharmacy: Drug monitoring in the elderly

2017 ◽  
Vol 52 (1) ◽  
pp. 100-110
Author(s):  
F. Lagrange ◽  
J. Lagrange ◽  
C. Bennaga ◽  
F. Taloub ◽  
M. Keddi ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Clinical Pharmacy ◽  
Drug Monitoring ◽  
The Elderly ◽  
Context Aware

Design and development of a mobile app to support the care of the elderly

2021 ◽  
Author(s):  
William R. Rodriguez-Duenas ◽  
Karen Aguia-Rojas ◽  
Valeria Valencia-Daza
Keyword(s):  
The Elderly ◽  
Mobile App ◽  
Design And Development

scholarly journals A Context-Aware Accurate Wellness Determination (CAAWD) Model for Elderly People Using Lazy Associative Classification

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1613 ◽  
Author(s):  
Farhan Sabir Ujager ◽  
Azhar Mahmood
Keyword(s):  
Elderly People ◽  
Data Extraction ◽  
Contextual Information ◽  
Elderly Person ◽  
The Elderly ◽  
Sensor Nodes ◽  
Behavior Patterns ◽  
Context Aware ◽  
Classification Rules ◽  
Training Time

Wireless Sensor Network (WSN) based smart homes are proving to be an ideal candidate to provide better healthcare facilities to elderly people in their living areas. Several currently proposed techniques have implementation and usage complexities (such as wearable devices and the charging of these devices) which make these proposed techniques less acceptable for elderly people, while the behavioral analysis based on visual techniques lacks privacy. In this paper, a context-aware accurate wellness determination (CAAWD) model for elderly people is presented, where behavior monitoring information is extracted by using simple sensor nodes attached to household objects and appliances for the analysis of daily, frequent behavior patterns of elderly people in a simple and non-obtrusive manner. A contextual data extraction algorithm (CDEA) is proposed for the generation of contextually comprehensive behavior-training instances for accurate wellness classification. The CDEA presents an activity’s spatial–temporal information along with behavioral contextual correlation aspects (such as the object/appliance of usage and sub-activities of an activity) which are vital for accurate wellness analysis and determination. As a result, the classifier is trained in a more logical manner in the context of behavior parameters which are more relevant for wellness determination. The frequent behavioral patterns are classified using the lazy associative classifier (LAC) for wellness determination. The associative nature of LAC helps to integrate spatial–temporal and related contextual attributes (provided by CDEA) of elderly behavior to generate behavior-focused classification rules. Similarly, LAC provides high accuracy with less training time of the classifier, includes minimum-support behavior patterns, and selects highly accurate classification rules for the classification of a test instance. CAAWD further introduces the ability to contextually validate the authenticity of the already classified instance by taking behavioral contextual information (of the elderly person) from the caregiver. Due to the consideration of spatial–temporal behavior contextual attributes, the use of an efficient classifier, and the ability to contextually validate the classified instances, it has been observed that the CAAWD model out-performs currently proposed techniques in terms of accuracy, precision, and f-measure.

scholarly journals BPcontrol

2016 ◽  
Vol 07 (04) ◽  
pp. 1120-1134 ◽  
Author(s):  
Adrián Carrera ◽  
Marc Pifarré ◽  
Jordi Vilaplana ◽  
Josep Cuadrado ◽  
Sara Solsona ◽  
...  
Keyword(s):  
Operating Systems ◽  
The Elderly ◽  
Mobile App ◽  
Hypertensive Patients ◽  
Monitoring And Diagnosis ◽  
Start Up ◽  
Communication Efficiency ◽  
Efficiency Factors ◽  
User Friendly ◽  
Health Care Centers

SummaryBackground Hypertension or high blood pressure is on the rise. Not only does it affect the elderly but is also increasingly spreading to younger sectors of the population. Treating this condition involves exhaustive monitoring of patients. The current mobile health services can be improved to perform this task more effectively.Objective To develop a useful, user-friendly, robust and efficient app, to monitor hypertensive patients and adapted to the particular requirements of hypertension.Methods This work presents BPcontrol, an Android and iOS app that allows hypertensive patients to communicate with their health-care centers, thus facilitating monitoring and diagnosis. Usability, robustness and efficiency factors for BPcontrol were evaluated for different devices and operating systems (Android, iOS and system-aware). Furthermore, its features were compared with other similar apps in the literature.Results BPcontrol is robust and user-friendly. The respective start-up efficiency of the Android and iOS versions of BPcontrol were 2.4 and 8.8 times faster than a system-aware app. Similar values were obtained for the communication efficiency (7.25 and 11.75 times faster for the Android and iOS respectively). When comparing plotting performance, BPcontrol was on average 2.25 times faster in the Android case. Most of the apps in the literature have no communication with a server, thus making it impossible to compare their performance with BPcontrol.Conclusions Its optimal design and the good behavior of its facilities make BPcontrol a very promising mobile app for monitoring hypertensive patients.Citation: Carrera A, Pifarré M, Vilaplana J, Cuadrado J, Solsona S, Mateo J, Solsona F. BPcontrol: a mobile app to monitor hypertensive patients

Fall Prevention and Management App Prototype for the Elderly and Their Caregivers

2020 ◽  
Vol 2 (1) ◽  
pp. 48-67
Author(s):  
Eseohen Imoukhome ◽  
Lori E. Weeks ◽  
Samina Abidi
Keyword(s):  
Management Practices ◽  
Point Of Care ◽  
Frailty Index ◽  
The Elderly ◽  
Mobile App ◽  
Management Approach ◽  
End User ◽  
Educational Materials ◽  
Patient Health ◽  
Potential Improvement

The objective of this article is to develop a validated mobile app prototype to empower the elderly and caregivers to manage falls that provides personalized and actionable educational materials at the point of care and improves the engagement of the elderly and caregiver in adopting validated fall management practices; To determine the usefulness and suitability of a fall management mobile app to the elderly and caregivers. The method used is a knowledge management approach is used to implement the app based on 2 validated models: Patient Health Engagement Model and Rockwood frailty index. A mixed method evaluation including a cognitive walk through is used to collect end-user feedback from the elderly and caregivers, on the usability, usefulness, and suitability of the app. The app was deemed easy to use, informative and understandable. Potential improvement areas include: larger print; less wordy interfaces; better navigation features; data sharing functionalities; and voice readers. These suggestions will be incorporated in the future. The conclusion of this article is that smartphones have vast potential in providing relevant and creditable fall management information to elderly and caregivers.

Multidimensional assessment and risk factors for prolonged hospitalization in the elderly

2003 ◽  
Vol 15 (4) ◽  
pp. 305-309 ◽  
Author(s):  
Mauro Zanocchi ◽  
Barbara Maero ◽  
Federica Francisetti ◽  
Erica Giona ◽  
Elena Nicola ◽  
...  
Keyword(s):  
Risk Factors ◽  
The Elderly ◽  
Multidimensional Assessment ◽  
Prolonged Hospitalization

scholarly journals Assessment of mHealth Solutions Applied to Fall Detection for the Elderly

2021 ◽  
Author(s):  
Fellipe Soares de Oliveira ◽  
Camila Carvalho da Silva ◽  
Talita Santos Pinheiro ◽  
Larissa Mayumi Yokoi ◽  
Pablo Deoclecia dos Santos ◽  
...  
Keyword(s):  
Clinical Practice ◽  
Mobile Health ◽  
Rating Scale ◽  
Fall Detection ◽  
The Elderly ◽  
Mobile App ◽  
Assessment Methods ◽  
Rigorous Evaluation ◽  
Wide Availability

Mobile Health has been increasingly present in healthcare due to the wide availability of applications for smartphones, however, robust assessment methods must be considered, seeking to provide evidence for clinical practice and mHealth solutions. This research presents the assessment of applications aimed at detecting and preventing falls for the elderly, available for Android and IOS, through the Mobile App Rating Scale. Based on the results presented, it can be concluded that the fall detection and prevention applications for the elderly available for Android and IOS showed good quality after rigorous evaluation.

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