Transforming usage data into a sustainable mobile health solution

Sultan, Salys; Mohan, Permanand

doi:10.1007/s12525-012-0090-6

Cited by 11 publications

(7 citation statements)

References 7 publications

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“…It is mainly because of the added value and benefit of mobile phones' ability to adapt day-to-day interactions based on previous usage patterns [4]. Moreover, mobile service benefits include extensive data capturing throughout the day to enable more participant empowerment, improved data quality for the health management process, improved feedback options based on improved data in different types of visualizations suited for the type of data, stimulating the ownership of their health by the users, more health data integration at the level of the person involved, etc.…”

Section: Related Research In Persuasive Healthcarementioning

confidence: 99%

Using Persuasive Recommendations in Wellness Applications based upon User Activities

Mukhtar¹

2016

ijacsa

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Abstract-Recently, a large number of mobile wellness applications have emerged for assisting users in self-monitoring of daily food intake and physical activities. While such applications are in abundance, many research surveys have found that the users soon give them up after giving some initial try. This article presents our application for healthcare self-management that monitors users' activities but -unlike the existing applicationsit focuses on keeping the users engaged for self-management. The distinguishing feature of our application is that it uses persuasive mechanisms to help users adopt healthy behavior. For this purpose, users' various activities are monitored and then they are persuaded using different persuasion strategies that are adaptive and are according to their behavior.For each user, a behavior model is created that is based on Fogg's behavior model but, in addition, it also holds within it user preferences, and user health profile. The behavior model is then used to create a persuasion profile of the user that allows us to propose personalized suggestions targeted to overcome his lacking behavior. We also describe a case study that describes the actual application.

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Section: Related Research In Persuasive Healthcarementioning

confidence: 99%

Using Persuasive Recommendations in Wellness Applications based upon User Activities

Mukhtar¹

2016

ijacsa

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“…10 In the proposed framework, these are represented in the form of parameters with default values that can be modified by the user. The feature values can be altered for adaptation.…”

Section: Adaptable Mobile User Interface Featuresmentioning

confidence: 99%

“…Alternatively, in the least popular usage day, the system may send more reminders to the user to use the application and in case there is a popular sequence of events, this sequence should be made easier to perform by adjusting the user interface layout. 10 …”

Section: System Generated Rulesmentioning

confidence: 99%

A Cloud-Based Framework for Context-Aware Intelligent Mobile User Interfaces in Healthcare Applications

Elazhary¹

2015

j med imaging hlth inform

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Developing context-aware intelligent mobile user interfaces is one of the ambitious goals of pervasive computing. One of the most promising candidate domains for using such interfaces is the healthcare domain. Healthcare personnel normally work all day long in many different contexts and thus, they need intelligent mobile user interfaces that can adapt to different contexts to help them perform their tasks efficiently and effectively without errors. Current research studies in the literature address aspects of this problem with no clear plan of how the different components may be integrated and specifically how adaptation rules and preferences can be developed, updated and managed. Thus, this paper presents a comprehensive framework that integrates several different functionalities to guide the development of intelligent mobile user interfaces with varying levels of complexity as required. The framework provides a definition of context that separates the system view and the complexity of context acquisition from the user view. It represents both context and adaptable mobile features in the form of a set of parameters and objects to facilitate the task of defining and modifying preferences for interface adaptation based on context. The framework considers both user-defined preferences and system generated ones based on usage analysis. Preferences are represented in different ways to help in handling inconsistencies and incompleteness. Storing user profiles and preferences on the cloud makes it possible for users to select stereotype preferences or to search for preferences of users with similar profiles. It also enables sharing preferences among applications and mobile devices and the automated update of stereotype preferences. Though this framework is general-purpose, it has been developed with an eye towards healthcare applications. Thus, its salient features have been tested empirically among healthcare personnel to assess their effectiveness and acceptability in this domain.

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“…Most experts are capable of expressing their knowledge in the form of rules for problem solving [9]. Our IMUI adaptation approach is based on a knowledge representation technique which is easy to use, and easy to modify and extend [8].…”

Section: New Direction In Adaptive Muismentioning

confidence: 99%

“…Sultan and Mohan (2012) [8] present an approach to adapting the user interface of a mobile health system with the goal of promoting the patient behaviors necessary for long-term use of the system. They focus on patients rather than doctors, and their type of adaptation can influence the sustainability of a mobile health initiative in the target patient market.…”

Section: Introductionmentioning

confidence: 99%

Empirical Evaluation of Intelligent Mobile User Interfaces in Healthcare

Alnanih

Ormandjieva

Radhakrishnan

2014

Advances in Artificial Intelligence

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Abstract.The users of mobile healthcare applications are not all the same, and there may be considerable variation in their requirements. In order for the application to be attractive to potential adopters, the interface should be very convenient and straightforward to use, and easy to learn. One way to accomplish this is with an intelligent mobile user interface (IMUI), so that the application can be readily adapted to suit user preferences. This paper presents the results of adapting the IMUI for the various user stereotypes and contexts in the healthcare environment. We begin with a context model of the healthcare domain and an analysis of user needs, and then proceed to solution analysis, followed by product design, development, and user testing in a real environment. In terms of IMUI design, we focus on adapting the MUI features for users in the healthcare context, either at design time or at runtime.

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Transforming usage data into a sustainable mobile health solution

Cited by 11 publications

References 7 publications

Using Persuasive Recommendations in Wellness Applications based upon User Activities

Using Persuasive Recommendations in Wellness Applications based upon User Activities

A Cloud-Based Framework for Context-Aware Intelligent Mobile User Interfaces in Healthcare Applications

Empirical Evaluation of Intelligent Mobile User Interfaces in Healthcare

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