mMamee: A mHealth Platform for Monitoring and Assessing Maternal Environmental Exposure

Karagiannaki, Katerina; Chonianakis, Stavros; Patelarou, Evridiki; Panousopoulou, Athanasia; Papadopouli, Maria

doi:10.1109/cbms.2015.56

Cited by 6 publications

(3 citation statements)

References 15 publications

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“…These solutions aim to provide services like personal health record management [7], providing electronic medical and health records [8], providing in-home medical nursing services [9], and provides convenient method of monitoring and safe life from kidnapping or lost [10]. The use of the m-health platform was discussed by Karagiannaki et al [11], in which the assessment of the women who are under maternity was done against the exposure to the environment. Kirtava et al [12] discussed the use of the m-health platform in the region of Georgia to monitor the outpatients for cardiac arrhythmia.…”

Section: Related Workmentioning

confidence: 99%

Nineveh Blood: Android Based Blood Donation Application for Nineveh Governorate in Iraq

Mostfa¹,

Alabass²,

Sharkawy³

2020

AL-Rafidain Journal of Computer Sciences and Mathematics

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Blood donation (BD) is one of the most significant contributions that a person can make towards the society. The growing android technology has made the process of BD easier and hassle-free. The Nineveh blood bank is an android application made for such great and noble cause. The application connects the givers and the requesters of blood who live in the Nineveh province, Iraq. The blood requester can serach from a list of all donors who have the same blood group and directly contact them without any thirdparty involvement. The Nineveh Blood application creates giver's/requester's profile through the Google Firebase Real-time database. In which, a one WebSocket two-way channel can constantly send the data back-and-forth between the server and the clients, and store the data as a JavaScript Object Notation (JSON) file.

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Section: Related Workmentioning

confidence: 99%

Nineveh Blood: Android Based Blood Donation Application for Nineveh Governorate in Iraq

Mostfa¹,

Alabass²,

Sharkawy³

2020

AL-Rafidain Journal of Computer Sciences and Mathematics

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“…They reported feasible methodology to monitor cardiac arrhythmia in outpatients in Georgia, promoting earlier discharge of nonlifethreatening cases, improving patients' comfort of life and increasing their mobility with enhanced safety. Similarly, Karagiannaki et al [7] presented the conceptual design and prototype development of mMamee, a mHealth platform for monitoring and analyzing the environmental exposures of women in maternity. The core objective is to produce a way to the physicians for monitoring and alert services for the benefits of the patient.…”

Section: IImentioning

confidence: 99%

Blood4U: A Novel Approach for Blood Collection

Haripriya¹

2018

IJRASET

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Blood4U is new perspective for health that provides healthcare services by using the mobile devices and communication technologies. We developed android based blood donation application as Blood4U solutions to build a connection between the acceptor and donor at anytime and anywhere. The main aim of developing this application is to reduce the time to a great extent that is spent in searching for the right donor and the availability of blood required by specifying urgency of acceptor in the application. Thus this application provides the required information and updating in time and also helps in quicker decision making by broadcasting message from acceptor to all donors that are registered in the application. To assess our application, we build acceptor-donor profiles and examine that it will assist to upgrade the timely access of the details and quick acknowledgement in urgent condition.

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“…Several studies have examined the use of mHealth for environmental health impact assessments—assessment of health-related problems deriving from the environment, such as chemical hazards, environmental contaminants, and other aspects of the ambient and living environment [ 5 ]. For example, Karagiannaki et al [ 6 ] deployed mHealth to monitor environmental factors affecting maternal health remotely. Honkoop et al [ 7 ] predicted the onset of asthma according to physiological, behavioral, and environmental data obtained by mHealth and home-monitoring sensors.…”

Section: Introductionmentioning

confidence: 99%

Factors Predicting Older People’s Acceptance of a Personalized Health Care Service App and the Effect of Chronic Disease: Cross-Sectional Questionnaire Study

Koo¹,

Park²,

Kang³

2023

JMIR Aging

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Background Mobile health (mHealth) services enable real-time measurement of information on individuals’ biosignals and environmental risk factors; accordingly, research on health management using mHealth is being actively conducted. Objective The study aims to identify the predictors of older people’s intention to use mHealth in South Korea and verify whether chronic disease moderates the effect of the identified predictors on behavioral intentions. Methods A cross-sectional questionnaire study was conducted among 500 participants aged 60 to 75 years. The research hypotheses were tested using structural equation modeling, and indirect effects were verified through bootstrapping. Bootstrapping was performed 10,000 times, and the significance of the indirect effects was confirmed through the bias-corrected percentile method. Results Of 477 participants, 278 (58.3%) had at least 1 chronic disease. Performance expectancy (β=.453; P=.003) and social influence (β=.693; P<.001) were significant predictors of behavioral intention. Bootstrapping results showed that facilitating conditions (β=.325; P=.006; 95% CI 0.115-0.759) were found to have a significant indirect effect on behavioral intention. Multigroup structural equation modeling testing the presence or absence of chronic disease revealed a significant difference in the path of device trust to performance expectancy (critical ratio=–2.165). Bootstrapping also confirmed that device trust (β=.122; P=.039; 95% CI 0.007-0.346) had a significant indirect effect on behavioral intention in people with chronic disease. Conclusions This study, which explored the predictors of the intention to use mHealth through a web-based survey of older people, suggests similar results to those of other studies that applied the unified theory of acceptance and use of technology model to the acceptance of mHealth. Performance expectancy, social influence, and facilitating conditions were revealed as predictors of accepting mHealth. In addition, trust in a wearable device for measuring biosignals was investigated as an additional predictor in people with chronic disease. This suggests that different strategies are needed, depending on the characteristics of users.

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mMamee: A mHealth Platform for Monitoring and Assessing Maternal Environmental Exposure

Cited by 6 publications

References 15 publications

Nineveh Blood: Android Based Blood Donation Application for Nineveh Governorate in Iraq

Nineveh Blood: Android Based Blood Donation Application for Nineveh Governorate in Iraq

Blood4U: A Novel Approach for Blood Collection

Factors Predicting Older People’s Acceptance of a Personalized Health Care Service App and the Effect of Chronic Disease: Cross-Sectional Questionnaire Study

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