Abstract

Healthcare is one of the basic human rights, but providing proper healthcare in rural remote areas of developing countries has always been a challenging task. Telemonitoring has brought some relief with limitations due to accessing patient's health information by healthcare workers and specialists, but merging it with cloud services can be an optimal solution. This proposed framework, CMED (Cloud based MEDical system), is a setup consisting of both healthcare center and a portable healthcare service with a Community Health Worker(CHW), which will sort the patients into three different categories—healthy, alarming and emergency. Upon failing to diagnose a unique problem, it will suggest and contact a specialist doctor and provide suggestions. The privacy and confidentiality of patient's health information will be secured by Identity Based Encryption. In this paper, a framework has been presented for smart and secure healthcare monitoring system for rural under privileged people in developing countries.

Abstract:

Bangladesh’s health care system, particularly in rural areas, experiences enormous obstacles in
providing complete preventive and primary healthcare services due to the lack of adequate healthcare facilities,
resource constraints, and a non-functional referral system. To alleviate these problems, in this study, we introduce
the digital general practitioner (GP) model for rural Bangladesh, digital platforms and present a statistical
analysis of the data that was gathered from the pilot project.
Methods: A total of 12,746 people were provided regular health services during the pilot project, from all genders
and age groups, and provided their socio-demographic and healthcare-related data. We analyzed healthcarerelated
data by carrying out both descriptive and inferential statistics.
Results: By utilizing this digital GP model, rural residents can receive routine health screenings at their homes,
identify health risks early, receive consultation and health education, and be referred to GP and upper-level
health facilities as needed. We found that hypertension was more prevalent (4.84% of the served population),
and cancer was the least prevalent of all the NCDs in the studied population (0.05% of the served population).
The population for stroke, hypertension, diabetes increased until the 50–59 age range as age increased, following
which the population proportion declined as age increased. Additionally, 3.96% of young females were severely
malnourished, comparably higher proportion than young males (2.34%).
Conclusion: NCDs such as hypertension, diabetes was prevalent among rural people. Necessary steps should be
taken to raise preventive and primary healthcare awareness among rural people.
Public interest summary: The absence of proper healthcare facilities, resource constraints, and a non-functional
referral system hamper Bangladesh’s health care system’s ability to provide comprehensive preventive and
primary healthcare services in rural area. As a result, patients develop advanced ailments, including noncommunicable
diseases (NCDs), and must seek treatment at an expensive specialty hospital. To resolve this
issue, we introduce a digital GP model for rural Bangladesh, then show digital platforms that use the concept, and
lastly summarize significant findings from the piloted digital GP model. By utilizing this digital GP model, rural
residents can receive routine health screenings at their homes, identify health risks early, receive consultation
and health education, and be referred to GP and upper-level health facilities as need. From our data analysis, we
discovered high burden of NCDs such as hypertension and diabetes in the piloted area. Necessary steps should be
taken to raise preventive and primary healthcare awareness among rural people.

Abstract:

Over the past 10 years, the use of augmented reality (AR) applications to assist individuals with special needs such as intellectual disabilities, autism spectrum disorder (ASD), and physical disabilities has become more widespread. The beneficial features of AR for individuals with autism have driven a large amount of research into using this technology in assisting against autism-related impairments. This study aims to evaluate the effectiveness of AR in rehabilitating and training individuals with ASD through a systematic review using the PRISMA methodology. A comprehensive search of relevant databases was conducted, and 25 articles were selected for further investigation after being filtered based on inclusion criteria. The studies focused on areas such as social interaction, emotion recognition, cooperation, learning, cognitive skills, and living skills. The results showed that AR intervention was most effective in improving individuals’ social skills, followed by learning, behavioral, and living skills. This systematic review provides guidance for future research by highlighting the limitations in current research designs, control groups, sample sizes, and assessment and feedback methods. The findings indicate that augmented reality could be a useful and practical tool for supporting individuals with ASD in daily life activities and promoting their social interactions.

Abstract

There are different kinds of technologies being used to improve the communication opportunity of children with verbal challenges. Portable communication devices provide the facility to the users for customizing applications according to their needs. Besides, the usability and costing range of these portable communication devices make them less condemning for the users. On the other hand, communication devices efficiently help the users with less motor skills. After considering these points, a communication device named “Bolte Chai”, has been developed and experimented in a special school’s students and teachers based on five criteria to evaluate usability and effectiveness. Those criteria are, the ability to customize the program to fit the needs of the users, motor skills for operating the applications, reasonable time and resources involved in the teaching and utilization procedure, update the system based on current research and proper costing, considering the user’s affordability. Based on the evaluation, it has been seen that this communication device is usable and effective to improve communication skills of nonverbal children.

Abstract

Depression is the most common mental illness, which has become the major cause of fear and suicidal mortality or tendencies. Currently, about 10% of the world population has been suffering from depression. The classical approach for detecting depression relies on the clinical questionnaire, which depends on the patients’ responses as well as observing their behavioral activities. However, there is no established method to detect depression from EEG biomarkers. Therefore, exploration of EEG biomarkers for depression assessments is vital and has a great potential to improve our understanding and clinical interventions. In this study, we have conducted a systematic review of 52 research articles using the PRISMA-P systematic review protocol, where we analyzed their research methodologies and outcomes. We categorized the experimentations in these articles according to their physical and psychological aspects scaled by the commonly used clinical questionnaire-based assessments. This study finds that the negative stimuli are the better identification strategies for evaluating depression through EEG signals. From this exploration, researchers observed that the Neural Connectivity Analysis and Brain Topological Mapping have huge potentials for finding depression biomarkers, and it is evident that the right-side hemisphere and frontal and parietal-occipital cortex are distinct regions to detect depression using EEG signals. For this mechanism, researchers are using many signal processing and machine learning approaches. In the case of filtering, Independent Component Analysis (ICA) is commonly used to eliminate physiological and non-physiological artifacts. Among machine learning approaches, Convolutional Neural Network (CNN) and Support Vector Machine (SVM) showed better performance for classifying healthy and depressed brains. The authors hope this study will create an opportunity to explore more in the future for EEG as a diagnostic tool by analyzing brain functional connectivity for focusing on clinical interventions. 

Abstract

This study aimed to investigate the estimated 10-year predicted risk of developing cardiovascular diseases (CVD) among participants with and without diabetes in Bangladesh.

Methods

We performed post hoc analysis from a matched case-control study conducted among 1262 participants. A total of 631 participants with diabetes (case) were recruited from a tertiary hospital, and 631 age, sex and residence matched participants (control) were recruited from the community in Dhaka, Bangladesh. Socioeconomic anthropometric, clinical and CVD risk factor data were collected from the participants. The 10-year estimated CVD risk was calculated using the Framingham Risk Score, which has reasonable validity in South Asians.

Results

The mean (SD) age of the participants were 51 (10) years. Total 52.3% of cases and 17.2% of controls were at high risk for CVD. The 10-year risk of CVD increased by age and was higher among males in both groups. Among the control group, high CVD risk was more prevalent among higher education and income groups. More than 85% of the tobacco smokers and 70% of chewing tobacco users in the case group were at high risk of CVD. Prevalence of high CVD risk among non-smokers was 8.6%. About 35% of hypertensive participants in the control group were at high risk of CVD.

Conclusion

Bangladeshi patients with diabetes showed a significant burden of CVD risk at a relatively younger age. Strategies for reducing tobacco use and improving BP control in people with diabetes is needed for lowering future CVD risks.

Abstract

Bangladesh is one of the most densely populated countries in the world, where a significant number of populations are suffering eye health and visionary problems. Over the last decade, a rapid growth of ICT uses has shown in Bangladesh. Thus ICT based health services would be an effective solution for providing the better health services to the citizens of Bangladesh. In this research work, an android based mobile application (Virtual Eye Doc) is developed in Bengali language to support the citizens of Bangladesh for their eye health monitoring and vision examination. The paper highlights our experiences of designing and developing the Virtual Eye Doc application. This paper also presents a qualitative and quantitative exploration of the effectiveness and the perceived benefits of this app, and suggestions for improvement of this app.