scholarly journals Methods for Breathing Rate Measurement through Mobile Platform: a Review

2019 ◽  
Author(s):  
Diego O. Lemos ◽  
Clauirton A. Siebra

Breathing rate is a vital sign that can indicate someone’s health status and even detect early diseases. Mobile health applications might become the main tool for estimating breathing rate out of the clinical environment. In this research, a review of the literature is conducted, aiming at finding out the most recent researches that have been proposed as solutions for respiratory measurement or monitoring using mobile devices. We discuss and compare their methods, highlighting pros and cons regarding ubiquity and feasibility. The results indicate that the combination of methods is a key aspect to improve measurements.

2015 ◽  
Author(s):  
Roberto Moro Visconti ◽  
Alberto Larocca ◽  
Michele Marconi

2020 ◽  
Author(s):  
Claudia Eberle ◽  
Maxine Löhnert

BACKGROUND Gestational diabetes mellitus (GDM) emerges worldwide and is closely associated with short- and long-term health issues in women and their offspring, such as pregnancy and birth complications respectively comorbidities, Type 2 Diabetes (T2D), Metabolic Syndrome (MetS) as well as cardiovascular disease (CD). Against this background mobile health applications (mHealth-Apps) do open up new possibilities to improve the management of GDM clearly. OBJECTIVE Since there is – to our knowledge – no systematic literature review published, which focusses on the effectiveness of specific mHealth-Apps on clinical health-related short and long-term outcomes of mother and child, we conducted these much-needed analyses. METHODS Data sources: A systematic literature search in Medline (Pubmed), Cochrane Library, Embase, CINAHL and Web of Science was performed including full text publications since 2008 up to date. An additional manual search in references and Google Scholar was conducted subsequently. Study Eligibility Criteria: Women diagnosed with GDM using specific mHealth-Apps during pregnancy compared to control groups, which met main clinical parameters and outcomes in GDM management as well as maternity and offspring care. Study appraisal and synthesis methods: Study quality was assessed and rated “strong”, “moderate” or “weak” by using the Effective Public Health Practice Project (EPHPP) tool. Study results were strongly categorized by outcomes; an additional qualitative summary was assessed. Study selection: Overall, n= 114 studies were analyzed, n= 46 duplicates were removed, n=5 studies met the eligible criteria and n=1 study was assessed by manual search subsequently. In total, n=6 publications, analyzing n=408 GDM patients in the interventional and n=405 women diagnosed with GDM in the control groups, were included. These studies were divided into n=5 two-arm randomized controlled trials (RCT) and n=1 controlled clinical trial (CCT). RESULTS Distinct improvements in clinical parameters and outcomes, such as fasting blood glucoses (FBG), 2-hour postprandial blood glucoses (PBG), off target blood glucose measurements (OTBG), delivery modes and patient compliance were analyzed in GDM patients using specific mHealth-Apps compared to matched control groups. CONCLUSIONS mHealth-Apps clearly improve clinical outcomes in management of GDM effectively. More studies need to be done more in detail.


Author(s):  
Snežana Jovičić ◽  
Joanna Siodmiak ◽  
Marta Duque Alcorta ◽  
Maximillian Kittel ◽  
Wytze Oosterhuis ◽  
...  

AbstractObjectivesThere are many mobile health applications (apps) now available and some that use in some way laboratory medicine data. Among them, patient-oriented are of the lowest content quality. The aim of this study was to compare the opinions of non-laboratory medicine professionals (NLMP) with those of laboratory medicine specialists (LMS) and define the benchmarks for quality assessment of laboratory medicine apps.MethodsTwenty-five volunteers from six European countries evaluated 16 selected patient-oriented apps. Participants were 20–60 years old, 44% were females, with different educational degrees, and no professional involvement in laboratory medicine. Each participant completed a questionnaire based on the Mobile Application Rating Scale (MARS) and the System Usability Scale, as previously used for rating the app quality by LMS. The responses from the two groups were compared using the Mann-Whitney U test and Spearman correlation.ResultsThe median total score of NLMP app evaluation was 2.73 out of 5 (IQR 0.95) compared to 3.78 (IQR 1.05) by the LMS. All scores were statistically significantly lower in the NLMP group (p<0.05), except for the item Information quality (p=0.1631). The suggested benchmarks for a useful appear: increasing awareness of the importance and delivering an understanding of persons’ own laboratory test results; understandable terminology; easy to use; appropriate graphic design, and trustworthy information.ConclusionsNLMP’ evaluation confirmed the low utility of currently available laboratory medicine apps. A reliable app should contain trustworthy and understandable information. The appearance of an app should be fit for purpose and easy to use.


Author(s):  
Sahar Khenarinezhad ◽  
Ehsan Ghazanfari Savadkoohi ◽  
Leila Shahmoradi

Aim: During the epidemic and with an increase in coronavirus (COVID-19) disease prevalence, emergency care is essential to help people stay informed and undertake self-management measures to protect their health. One of these self-management procedures is the use of mobile apps in health. Mobile health (mHealth) applications include mobile devices in collecting clinical health data, sharing healthcare information for practitioners and patients, real-time monitoring of patient vital signs, and the direct provision of care (via mobile telemedicine). Mobile apps are increasing to improve health, but before healthcare providers can recommend these applications to patients, they need to be sure the apps will help change patients' lifestyles. Method: A search was conducted systematically using the keywords "Covid-19," "Coronavirus," "Covid-19, and Self-management" at the "Apple App Store". Then we evaluated the apps according to MARS criteria in May 2020. Results: A total of 145 apps for COVID-19 self-management were identified, but only 32 apps met our inclusion criteria after being assessed. The overall mean MARS score was 2.9 out of 5, and more than half of the apps had a minimum acceptability score (range 2.5-3.9). The "who academy" app received the highest functionality score. Who Academy, Corona-Care and First Responder COVID-19 Guide had the highest scores for behavior change. Conclusion: Our findings showed that few apps meet the quality, content, and functionality criteria for Covid-19 self-management. Therefore, developers should use evidence-based medical guidelines in creating mobile health applications so that, they can provide comprehensive and complete information to both patients and healthcare provider.


2017 ◽  
Vol 33 (9) ◽  
pp. 1-6
Author(s):  
Adam Rosenfeld ◽  
Sachin Pendse ◽  
Nicole R. Nugent

2018 ◽  
Vol 35 (4) ◽  
pp. 815-825 ◽  
Author(s):  
Hao-Yun Kao ◽  
Chun-Wang Wei ◽  
Min-Chun Yu ◽  
Tyng-Yeu Liang ◽  
Wen-Hsiung Wu ◽  
...  

2020 ◽  
Author(s):  
Mubarak Albarka Umar

<p><i>Software Testing is the process of evaluating a software program to ensure that it performs its intended purpose. Software testing verifies the safety, reliability, and correct working of software. The growing need for quality software makes software testing a crucial stage in Software Development Lifecycle. There are many methods of testing software, however, the choice of method to test a given software remains a major problem in software testing. Although, it is often impossible to find all errors in software, employing the right combination of methods will make software testing efficient and successful. Knowing these software testing methods is the key to making the right selection. This paper presents a comprehensive study of software testing methods. An explanation of Testing Categories was presented first, followed by Testing Levels (and their comparison), then Testing Techniques (and their comparison). For each Testing Levels and Testing Techniques, examples of some testing types and their pros and cons were given with a brief explanation of some of the important testing types. Furthermore, a clear and distinguishable explanation of two confused and contradictory terms (Verification and Validation) and how they relate to Software Quality was provided.</i></p>


IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 9390-9403 ◽  
Author(s):  
Achilleas Papageorgiou ◽  
Michael Strigkos ◽  
Eugenia Politou ◽  
Efthimios Alepis ◽  
Agusti Solanas ◽  
...  

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