ABSTRACT
Health is the centre of human enlightenment. Due to the recent Covid outbreak and several environmental pollutions, checking one's vitals regularly has become a necessity. Ours is an IoT-based device that measures a user's heart rate, blood oxygen level and body temperature. The device is compact and portable, making it easy for users to wear. The readings are measured and shown on an OLED display with the help of sensors. The data is also available on the cloud. A webpage and a mobile application were developed to view the data from the cloud. Individual graphs of the vitals with time are available on the mobile application. This can be used for progress measurement and statistical analyses. Authorized personnel can access the patient's vitals. This creates a scope for Tele-medication in rural and underdeveloped regions. Besides, one can also view his/her vitals for personal health routine. © 2022 IEEE.
ABSTRACT
Mobile application developers rely largely on user reviews for identifying issues in mobile applications and meeting the users' expectations. User reviews are unstructured, unorganized and very informal. Identifying and classifying issues by extracting required information from reviews is difficult due to a large number of reviews. To automate the process of classifying reviews many researchers have adopted machine learning approaches. Keeping in view, the rising demand for educational applications, especially during COVID-19, this research aims to automate Android application education reviews' classification and sentiment analysis using natural language processing and machine learning techniques. A baseline corpus comprising 13,000 records has been built by collecting reviews of more than 20 educational applications. The reviews were then manually labelled with respect to sentiment and issue types mentioned in each review. User reviews are classified into eight categories and various machine learning algorithms are applied to classify users' sentiments and issues of applications. The results demonstrate that our proposed framework achieved an accuracy of 97% for sentiment identification and an accuracy of 94% in classifying the most significant issues. Moreover, the interpretability of the model is verified by using the explainable artificial intelligence technique of local interpretable model-agnostic explanations. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
ABSTRACT
The COVID-19 pandemic has given people much free time. With this, the researchers want to encourage these people to read instead of scrolling through social media. A barrier to reading for many people is not knowing what to read and disinterest in popular books that they would find when they search online. The existing websites that encourage book reading rely on social networking for their recommendations, while the collaborative filtering algorithms applied to books do not exist in the mobile application form. Readwell is a book recommender Android app with a Point-of-Sales System created using Java, Python, and SQLite databases. The information regarding the books was web scraped from the Goodreads website. It aims to apply the more efficient collaborative filtering algorithm to an accessible mobile application that allows users to directly buy the books they are interested in, thus encouraging the reading and buying of books. The researchers created unit test cases to validate the different functionalities of the application. © 2022 IEEE.
ABSTRACT
By the beginning of 2020, the illness had been named as COVID-19, which had spread due to its extreme severity affecting multiple industries and sectors throughout the world. To protect the public's health and safety, the Philippine government has established a number of quarantine regulations and travel restrictions in reaction to the current COVID-19 outbreak. Nonetheless, the ILO predicted that the pandemic would initially disrupt the economy and labor markets, affecting 11 million employees, or around 25% of the workforce in the Philippines. Therefore, the government continues to urge employers of local companies and enterprises to use alternative work plans, such as a WFH - work-from-home operation in accordance with the established policies. In line with the concept of telework, several studies have already been carried out, though some were declared inconclusive and require additional study. Hence, in this research, a mobile application was created to evaluate the employee's telework capability assessment using a Fuzzy-based model which utilizes Google AppSheet, Apps Script, and Sheets. The developed mobile application is able to provide capacity evaluation utilizing the four key input variables, which are also reasonably characterized for potential telecommuting cost evaluation. © 2022 IEEE.
ABSTRACT
Background: The coronavirus disease 2019 (COVID-19) pandemic has had an immense impact on psychic health. Children and adolescents are considered especially vulnerable which is why health promotion and prevention programs are important and should be designed in a motivating way to be attractive to this age group. The aim of this work is to investigate whether young people can be reached with the help of innovative digital formats for health promotion. Methods: An app-based training to promote self-regulation was offered to adolescents in lower secondary education in autumn 2020. Data were collected using an app. The types of motivation to participate in the training were analyzed. In addition, the students were able to rate the attractiveness of the training with the help of a self-designed evaluation sheet. Results: Of the 91 registered participants, 39.56% completed the study. In all, 40.91% of the students stated that the training was "very" helpful and 36.36% rated it as "quite" helpful. Although 50% of the respondents found the app-based training "modern and motivating", the other half would have preferred more personal support. Conclusion: The results confirm previous study results with health apps in children and adolescents. This age group is interested in digital formats, but health apps are not used continuously in this age group unless obligatory.
ABSTRACT
Some problems of Filipino farmers in Nueva Ecija are irrigation systems and labor shortage. Most of them are unable to work due to old age while others chose to stop because of the COVID-19 pandemic. Meanwhile, irrigation systems have been an issue due to the lack of resources such as continuous water supply and control. Fortunately, there is a progression of smart farming in the country which could assist in optimizing farming processes. This study presents a systematic literature survey on rice farming technologies and challenges. This study also aims to help address these problems by creating a rice irrigation system that introduces a water level control system. The system was comprised of a mobile application, Arduino ESP32 module, and a tank with water level sensors. The mobile application was used to set the desired water level while the proportional- integral-derivative (PID) controller adjusted the water level automatically. When current water level is lower than the setpoint, the valves to the tank will open. Tank specifications were used to come up with a transfer function for the system. The proposed design was simulated in MATLAB Simulink and PID parameters were tuned to enhance system performance. The tuned control system obtained an output response with less overshoot and faster settling time. © 2022 IEEE.
ABSTRACT
MNLTour is a virtual tour system for selected tourist spots situated within the city of Manila. It utilizes 360-degree images, 2D images, voice recordings, and virtual reality technology to offer an immersive user experience of the virtual environment. The virtual tour system was developed using the Unity3D software and was then integrated into web and mobile applications accessible through web browsers and android smartphones, respectively. MNLTour aims to promote the wonders of Manila city by showcasing some of its historical tourist spots that have been severely affected by the outbreak of the COVID-19 pandemic. The developed web and mobile applications were tested and later evaluated to assess the overall quality of the software in accordance with ISO 9126 standard. The evaluation statements primarily focus on the aspects of functionality, efficiency, usability, effectiveness, and user satisfaction in using the application. Descriptive statistics was used to analyze and summarize the data gathered from the evaluation respondents. The evaluation of the application in both platforms turned out to have admirable evaluation results;hence, it's safe to say that the developed software has an acceptable overall quality. © 2022 IEEE.
ABSTRACT
Smartphone use provides a significant amount of screen-time for youth, and there have been growing concerns regarding its impact on their mental health. While time spent in a passive manner on the device is frequently considered deleterious, more active engagement with the phone might be protective for mental health. Recent developments in mobile sensing technology provide a unique opportunity to examine behaviour in a naturalistic manner. The present study sought to investigate, in a sample of 451 individuals (mean age 20.97 years old, 83% female), whether the amount of time spent on the device, an indicator of passive smartphone use, would be associated with worse mental health in youth and whether an active form of smartphone use, namely frequent checking of the device, would be associated with better outcomes. The findings highlight that overall time spent on the smartphone was associated with more pronounced internalizing and externalizing symptoms in youth, while the number of unlocks was associated with fewer internalizing symptoms. For externalizing symptoms, there was also a significant interaction between the two types of smartphone use observed. Using objective measures, our results suggest interventions targeting passive smartphone use may contribute to improving the mental health of youth.
ABSTRACT
Context: Nowadays, mobile applications (or apps) have become vital in our daily life, particularly within education. Many institutions increasingly rely on mobile apps to provide access to all their students. However, many education mobile apps remain inaccessible to users with disabilities who need to utilize accessibility features like talkback or screen reader features. Accessibility features have to be considered in mobile apps to foster equity and inclusion in the educational environment allowing to use of such apps without limitations. Gaps in the accessibility to educational systems persist. Objective: In this paper, we focus on the accessibility of the Blackboard mobile app, which is one of the most common Learning Management Systems (LMS) used by many universities, especially during the current COVID-19 pandemic. Method: This study is divided into two-fold. First, we conduct a survey using questionnaires and interviews to explore the extent to which students consider the Blackboard mobile app usability. A Total of 1,308 hearing students and 65 deaf and hard-of-hearing students participated in the study. Second, we collected 15,478 user reviews from the Google Play Store and analyzed the reviews to extract accessibility issues. Result: We observed that most deaf and hard-of-hearing students found difficulty in the Blackboard mobile app, compared to hearing students. Also, our app store analysis showed that only 31% of the reviews reported violations of accessibility principles that apps like Blackboard must comply with. This study highlights these violations and their corresponding implications to support LMS frameworks in becoming more inclusive for all users. © 2023 ACM.
ABSTRACT
Objective: Develop an application to guide health professionals during home care in coping with the COVID-19 pandemic. Method: The structure of the application was developed in four stages: Analysis - an integrative literature review was carried out with the Health Sciences databases, such as MEDLINE, SciELO, and LILACS. Design - this step involved planning and producing didactic content, defining topics and writing subjects, selecting media, and designing the interface (layout). Development - definition of the navigation structure and planning of the configuration of environments. Implementation - construction of an environment for downloading the application on the Internet. Results: The ORIENTA COVID-19 application has 40 screens and 130 images describing gowning, and undressing of PPE, including using a homemade mask, guidelines for care to prevent COVID-19, and social etiquette. After registration at the National Institute of Industrial Property, it will be available on the Google Play Store under ORIENTA COVID-19. Conclusion: After an integrative review of the literature obtained from the main databases, the ORIENTA COVID-19 application was developed to support health professionals during home care related to COVID-19.
Objetivo: Desenvolver um aplicativo para orientar os profissionais de saúde durante o atendimento domiciliar, no enfrentamento da pandemia da COVID-19. Método: A estrutura do aplicativo foi desenvolvida em quatro etapas: Análise - foi realizada uma revisão integrativa da literatura junto às bases de dados das Ciências da Saúde, como: MEDLINE, SciELO e LILACS. Design - esta etapa envolveu o planejamento e a produção do conteúdo didático, a definição dos tópicos e a redação dos assuntos, a seleção das mídias e o desenho da interface (layout). Desenvolvimento - definição da estrutura de navegação e o planejamento da configuração de ambientes. Implementação - construção de um ambiente para download da aplicação na Internet. Resultados: O aplicativo ORIENTA COVID-19 tem 40 telas e 130 imagens descrevendo a paramentação, desparamentação dos EPIs incluindo a técnica do uso da máscara caseira, orientações dos cuidados para prevenir a COVID-19 e a etiqueta social. Após seu registro no Instituto Nacional da Propriedade Industrial, estará disponível no Google Play Store sob o nome ORIENTA COVID-19. Conclusão: Após revisão integrativa da literatura obtida nas principais bases de dados, desenvolveu-se o aplicativo ORIENTA COVID-19, para apoio aos profissionais da saúde durante o atendimento domiciliar relacionado à COVID-19.
ABSTRACT
Mobile health applications (mHealth apps) may be able to support people living with chronic obstructive pulmonary disease (COPD) to develop the appropriate skills and routines for adequate self-management. Given the wide variety of publicly available mHealth apps, it is important to be aware of their characteristics to optimize their use and mitigate potential harms. Objective: To report the characteristics and features of publicly available apps for COPD self-management. Methods: MHealth apps designed for patients' COPD self-management were searched in the Google Play and Apple app stores. Two reviewers trialed and assessed the eligible apps using the MHealth Index and Navigation Database framework to describe the characteristics, qualities, and features of mHealth apps across five domains. Results: From the Google Play and Apple stores, thirteen apps were identified and eligible for further evaluation. All thirteen apps were available for Android devices, but only seven were available for Apple devices. Most apps were developed by for-profit organizations (8/13), non-profit organizations (2/13), and unknown developers (3/13). Many apps had privacy policies (9/13), but only three apps described their security systems and two mentioned compliance with local health information and data usage laws. Education was the common app feature; additional features were medication reminders, symptom tracking, journaling, and action planning. None provided clinical evidence to support their use. Conclusions: Publicly available COPD apps vary in their designs, features, and overall quality. These apps lack evidence to support their clinical use and cannot be recommended at this time.
ABSTRACT
Healthcare monitoring frameworks emerged as one of the most essential frameworks and innovations established over the last decade. As a result of failing to provide adequate clinical attention to patients at the appropriate time, many people are facing the possibility of an untimely death. Ultimately, the goal was to develop an IoT-based integrated healthcare monitoring framework that could be relied upon by healthcare professionals to screen their patients, whether they were in the hospital or at home, to ensure that they were being well-cared for. A mobile phone-based remote healthcare monitoring framework has been constructed with the help of sensors, an information acquisition unit, a microcontroller (such as Arduino), and a product modification. This framework has the potential to provide continuous web-based data regarding a patient's physiological states (i.e., JAVA). Before transmitting it to the specialist's portable device along with the application, the framework examines the patient's temperature, heart rate, and EEG data. It then displays and saves this information. An Internet of Things-based patient monitoring framework may monitor a patient's health condition in an efficient manner and save the patient's life at the appropriate moment. © 2023 IEEE.
ABSTRACT
Fitness centres have been among the first businesses affected by the COVID-19 pandemic. It is clear that with the pandemic, users' choices for sports services and selection criteria for them have changed. During the pandemic, there has been a transition from traditional gym classes to virtual fitness classes. People have started to rapidly adopt these technology-based alternatives worldwide, and there has been an increase in the download and use of these mobile fitness applications. However, there are many alternatives to fitness applications for users. In this study, making the most effective selection among the alternatives in mobile applications where there are conflicting user criteria and identifying customer-oriented platform development proposals in terms of service providers are aimed to contribute to the relevant literature. The study has proposed an Analytic Hierarchy Process (AHP) model, one of the Multi-criteria Decision-Making approaches, for selecting the best choice among mobile fitness application alternatives where there is more than one alternative with more than one criterion and these criteria conflict with each other. The proposed AHP solution has a modular structure that can be easily adapted in case user preferences (criteria) changes and can flexibly be updated when the alternatives change.
ABSTRACT
Service providers from the informal sectors in the Philippines are left unemployed or want to look for part-time jobs due to the sudden COVID-19 pandemic. With the country on lockdown and as strict restrictions are implemented, people started adopting the e-commerce and m-commerce market. The rise in the Filipino masses using smartphones and participating in mobile commerce to purchase products and services over the Internet has given researchers a potential solution for the arising problem. Thus, the primary objective of the research is to design and develop a user-friendly mobile application that will give a platform where potential home service providers can offer their services to potential clients. HanAPP Buhay, a mobile application that is created in Android Studio with Java as a programming language, is a platform where service providers can offer a variety of home services including laundry, plumbing, cleaning, and electrical works to potential clients. As for the Application Programming Interface (API), Stripe and Firebase are the tools utilized for databases and transaction purposes. The researchers conducted a series of surveys and experiments and have determined that in the 38 trials, the HanAPP Buhay mobile application is functioning 100% accurately as expected, 99.995382330563% and 99.994941213182% working at real-time booking of appointments in the 16 trials for clients and 22 trials for workers respectively, have a reliable user's interface and secured data of both users through the Scrypt algorithm, and effective in its overall specifications in terms of customer's satisfaction. © 2022 IEEE.
ABSTRACT
BACKGROUND: Physical inactivity is a serious public health problem for people of all ages and is currently the fourth highest global risk factor for mortality. The transition period from adolescence to adulthood coincides with a marked reduction in participation in physical activity, with more than 50% (and up to 80%) of young adults stopping physical activity. This decrease in physical activity is more evident in women than in men. Despite efforts, existing programs face challenges in effectively initiating and maintaining physical activity among individuals, particularly women, for extended durations. To address these limitations, the Women's Involvement in Steady Exercise (WISE) randomized controlled trial (RCT) seeks to assess the efficacy of a digital high-intensity training intervention complemented by nutritional plans and other health-related advice. METHODS: The study will be a three-center, randomized (1:1), controlled, parallel-group trial with a six-month intervention period. A total of 300 participants will be recruited at three study sites in Spain, Serbia and Italy. The participants will be randomized to one of the two groups and will follow a six-month program. The primary outcome of the study is the daily step count. Self-reported physical activity, the adherence to the exercise program, body composition, physical activity enjoyment, quality of sleep and physical capacities will also be evaluated.
ABSTRACT
The world population is projected to rapidly age over the next 30 years. Given the increasing digital technology adoption amongst older adults, researchers have investigated how technology can support aging populations. However, little work has examined how technology can support older adults during crises, despite increasingly common natural disasters, public health emergencies, and other crisis scenarios in which older adults are especially vulnerable. Addressing this gap, we conducted focus groups with older adults residing in coastal locations to examine to what extent they felt technology could support them during emergencies. Our fndings characterize participants' desire for tools that enhance community resilience-local knowledge, preparedness, community relationships, and communication, that help communities withstand disasters. Further, older adults' crisis technology preferences were linked to their sense of control, social relationships, and digital readiness. We discuss how a focus on community resilience can yield crisis technologies that more efectively support older adults.
ABSTRACT
To help prevent the spread of COVID-19, countries around the world have implemented a range of measures and virus containment strategies, including digital contact-tracing (DCT) in the form of smartphone apps. While early studies showed a high level of acceptability of such technologies, the adoption rates varied greatly between countries after contact-tracing apps became available to download. This cross-national user survey (n=871) aims to explore public attitudes and factors that affect user acceptability and adoption of contact-tracing apps in the USA, UK, and the Republic of Ireland, which employ similar underlying technology, but have uneven adoption rates. The results indicate interactions between installation decisions and public trust in actors and institutions communicating COVID-related information, and releasing such technologies. Beyond the immediate case of contact tracing, our findings hold implications for the deployment and communicative framing of technology for public health and the public good, and inform the design of crisis response public health information systems.
ABSTRACT
Sentiment analysis has a critical role to reveal an opinion in a text-based form. Therefore, we exploit this analysis to discover the sentiment polarity of Taiwan Social Distancing mobile application. This paper proposes a semi-supervised scheme for annotating this mobile application's reviews. The semi-supervised scheme utilized a combination of numeric rating and lexicon-based sentiment. In addition, we also perform the sentiment analysis on an aspect-based level. Based on the experiment, we decide to select three aspects to be analyzed. This paper also evaluates the proposed scheme by implementing bidirectional encoder representations from transformers (BERT) and multilayer perceptron (MLP) as the classification model using the sentiment label of the proposed scheme. The result shows that the annotation of the proposed scheme outperforms the data annotation using counterpart models. © 2023 IEEE.
ABSTRACT
This dissertation presents findings from three longitudinal studies examining indicators of positive undergraduate mental health primarily during COVID-19 pandemic conditions at a large, residential, urban university in Canada (Western University) using apps with personal sensing data collection capabilities (e.g. GPS, step counts) over March 2019-August 2021. The apps featured mental health-related questionnaires - responses were representative of psychosocial outcomes for participants. Personal sensing data were representative of participant behavior/lifestyle. Questionnaires and personal sensing data were collected at the same time;personal sensing data was also collected hourly in the background for the final two studies. Associations between psychosocial outcomes and behavior/lifestyle found via mixed linear modelling revealed indicators of positive mental health. The first study, Smart Healthy Campus 1.0, began March 2019, concluding with limited data when COVID-19 was declared a pandemic;possible associations were identified. Initial plans were to improve SHC 1.0 with an upgraded SHC 2.0 study, but the Student Pandemic Experience (SPE) study was launched first, with questionnaires more fixated on pandemic conditions. Following this, SHC 2.0 was also launched shortly after, still relevant, although using shorter generic questionnaires. SPE completed with 315 participants who were primarily female (76%) iOS users (85.3%). Data collected for 40 weeks (11/2020 - 09/2021) included 4851 questionnaire responses and 25985 sensor samples with up to 68 individual values per sample. Mixed linear models were fit relating 15 mobile device (phone or tablet) sensors (e.g. step count) to 12 mental health-related questionnaire scores. SHC 2.0 ran with 94 participants were who primarily male (76.6%) iOS users (86%). Data collected for 30 weeks (01/2021 - 08/2021) included 1722 questionnaire responses and 6518 sensor samples with up to 68 individual values per sample. Mixed linear models were fit relating 12 mobile device (phone or tablet) sensors (e.g. step count) to the SHC 2.0 questionnaires. From these studies, it was found that device sensors had statistically significant associations with the selected mental health-related questionnaires for undergraduates during a major pandemic. These findings suggest directions for mental health-related programs (e.g. apps or physical activity) and interventions during a pandemic for a comparable group and setting. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
ABSTRACT
Currently, people’s highly busy lifestyles and sedentary behavior contribute negatively to multiple health factors. During the COVID-19 pandemic, the different sanitary measures, such as limited mobility and the closing of gyms and sports centers, have contributed to limited physical activity. In this context, there are several apps to enhance physical activity across all mobile stores with an emphasis on mobile sensing. However, the use of a formal theory incorporated into the app development and interventions is less evident. A theory-based approach contributes to understanding the reasons and situations in which an intervention strategy can have an impact. The present work considers the Elaboration Likelihood Model (ELM), which addresses persuasion and attitude change. Can we develop a persuasive app that promotes physical activity based on contemporary attitudes and behavioral change theories? We developed a mobile application for Android OS. Then, 63 participants tested it, and were encouraged to think of ideas or arguments in favor of doing physical activity in a high elaboration task. A mediation analysis was done, with results showing that attitudes partially mediate the association between thought and physical activity. Participants’thoughts were seen to be positively correlated with their attitudes;and, in turn, participants’attitudes were correlated with their behavioral intention (to do physical activity). This suggests that a theory-based approach for the active production of biased beliefs is effective when designing an app that encourages positive attitudes toward physical activity. Author