International Journal of Telemedicine and Applications
 Journal metrics
Acceptance rate25%
Submission to final decision89 days
Acceptance to publication89 days
CiteScore3.100
Journal Citation Indicator0.540
Impact Factor-

Feedback Artificial Shuffled Shepherd Optimization-Based Deep Maxout Network for Human Emotion Recognition Using EEG Signals

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 Journal profile

International Journal of Telemedicine and Applications focuses on the applications of medical practice and care at a distance and their supporting technologies such as, computing, communications, and networking technologies.

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International Journal of Telemedicine and Applications maintains an Editorial Board of practicing researchers from around the world, to ensure manuscripts are handled by editors who are experts in the field of study.

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Research Article

Setting Up a Teleneurology Clinic during COVID-19 Pandemic: Experience from an Academic Practice

The declaration of the COVID-19 pandemic necessitated rapid implementation of telehealth across all neurological subspecialties. Transitioning to telehealth technology can be challenging for physicians and health care facilities with no prior experience. Here, we describe our experience at the Neurology and Sleep Disorders Clinic at the University of Missouri-Columbia of successful transition of all in-person clinic visits to telehealth visits within a span of 2 weeks with a collaborative effort of clinic staff and the leadership. Within a month of launch, 18 clinic providers with no prior telehealth experience conducted 1451 telehealth visits, which was the 2nd highest number of telehealth visits conducted by any department at the University of Missouri-Columbia Health Care system. Lack of connectivity, poor video/audio quality, and unavailability of smart devices among rural populations were the important shortcomings identified during our telehealth experience. Our study highlighted the need for expansion of high-speed internet access across rural Missouri. We hope our experience will help other health care facilities to learn and incorporate telehealth technology at their facilities, overcome the associated challenges, and serve patient needs while limiting the spread of the COVID-19.

Research Article

Impact of COVID-19 on the 937 Telephone Medical Consultation Service in Saudi Arabia

The impact of COVID-19 on healthcare services has been profound. One major impact has been underutilization of traditional healthcare services by patients. In 2020, the Saudi Ministry of Health (MoH) started offering general COVID-19 enquiries, education, and medical and psychological consultations around the clock via their 937-Call Center. Given this major change, there was a need to understand the impact of the COVID-19 pandemic on Call Center services, specifically medical consultations, to suggest future recommendations for patient care optimization. This descriptive study analyzed routinely collected data on the 937-Call Center service between March 2020 and September 2020. Data were reviewed, coded, verified, and analyzed using SPSS v22. There was a 296% increase in the number of calls received by the 937-Call Center in 2020 compared to the same period in 2019. The majority of calls received in 2020 were general medical enquiries (98.41%), but about three million COVID-19-specific enquiries were also received in 2020. The increased number of calls was managed by accepting volunteers to handle calls: an average of 236 volunteers per month, handling about 20% of the total call volume. The majority of volunteers were physicians but with the presence of pharmacists, psychologists, and specialized healthcare workers such as nutritionists. Utilization of the 937-Call Center increased during the COVID-19 pandemic, suggesting that it has been an effective strategy for combatting the COVID-19 pandemic in Saudi Arabia. Further research is recommended to investigate the impact of COVID-19 on public awareness of the 937-Call Center and other health-related mobile apps.

Review Article

The Design Blueprint for a Large-Scale Telehealth Platform

Technological innovation plays a crucial role in digital healthcare services. A growing number of telehealth platforms are concentrating on using digital tools to improve the quality and availability of care. Virtual care solutions employ not only advanced telehealth technology but also a comprehensive range of healthcare services. As a result, these can reduce patient healthcare costs as well as increase accessibility and convenience. At the same time, the healthcare service provider can leverage healthcare professionals to get a better perspective into the needs of their patients. The objective of this research is to provide a comprehensive design blueprint for a large-scale telehealth platform. Telehealth is the digital healthcare service combining online services and offline access for healthcare facilities to offer various healthcare services directly to patients. This design blueprint covers the digital healthcare ecosystem, new patient journey design for digital health services, telehealth functionality design, and an outline of the platform infrastructure and security design. Ultimately, telehealth platforms establish a completed digital healthcare service and new ecosystem that provides better care for every patient worldwide.

Research Article

Evaluation of Tele-rheumatology during the COVID-19 Pandemic in Asian Population: A Pilot Study

Objective. Rheumatoid arthritis (RA) is a chronic autoimmune condition associated with a potential for deformities. It is one of the common conditions to seek health care. Hence, the present study was conducted to assess the telemedicine services for patients suffering from rheumatoid arthritis during the COVID-19 pandemic in an Asian Indian population. Methods. A prospective study was conducted (March 2020–June 2020) in the telemedicine department of a premier northern Indian tertiary care institution. Out of the total patients enrolled () in telemedicine services, 122 rheumatoid arthritis patients (1.6%) were followed for 1 month to assess change in functional status by modified Health Assessment Questionnaire (mHAQ). Telephonic interviews of the enrolled patients were conducted to determine the level of understanding of advice given by consultants, barriers during the consultation, and satisfaction with teleconsultations for rheumatology clinics. Results. For the native people, language of the clinicians was the main barrier (20%) in telerheumatology. Saving of time and money was observed as beneficial factors for patients. More than three-quarters of all rheumatoid arthritis patients were ready to use teleconsultation in the near future. A similar proportion of patients were in support for the recommendation of these services to other persons. Conclusion. We report the successful use of telemedicine services in the evaluation and management of rheumatic diseases in the current COVID-19 pandemic situation.

Research Article

Experimental Study of a Deep-Learning RGB-D Tracker for Virtual Remote Human Model Reconstruction

Tracking movements of the body in a natural living environment of a person is a challenging undertaking. Such tracking information can be used as a part of detecting any onsets of anomalies in movement patterns or as a part of a remote monitoring environment. The tracking information can be mapped and visualized using a virtual avatar model of the tracked person. This paper presents an initial novel experimental study of using a commercially available deep-learning body tracking system based on an RGB-D sensor for virtual human model reconstruction. We carried out our study in an indoor environment under natural conditions. To study the performance of the tracker, we experimentally study the output of the tracker which is in the form of a skeleton (stick-figure) data structure under several conditions in order to observe its robustness and identify its drawbacks. In addition, we show and study how the generic model can be mapped for virtual human model reconstruction. It was found that the deep-learning tracking approach using an RGB-D sensor is susceptible to various environmental factors which result in the absence and presence of noise in estimating the resulting locations of skeleton joints. This as a result introduces challenges for further virtual model reconstruction. We present an initial approach for compensating for such noise resulting in a better temporal variation of the joint coordinates in the captured skeleton data. We explored how the extracted joint position information of the skeleton data can be used as a part of the virtual human model reconstruction.

Research Article

Development of a Mobile Application Platform for Self-Management of Obesity Using Artificial Intelligence Techniques

Obesity is a major global health challenge and a risk factor for the leading causes of death, including heart disease, stroke, diabetes, and several types of cancer. Attempts to manage and regulate obesity have led to the implementation of various dietary regulatory initiatives to provide information on the calorie contents of meals. Although knowledge of the calorie content is useful for meal planning, it is not sufficient as other factors, including health status (diabetes, hypertension, etc.) and level of physical activity, are essential in the decision process for obesity management. In this work, we present an artificial intelligence- (AI-) based application that is driven by a genetic algorithm (GA) as a potential tool for tracking a user’s energy balance and predicting possible calorie intake required to meet daily calorie needs for obesity management. The algorithm takes the users’ input information on desired foods which are selected from a database and extracted records of users on cholesterol level, diabetes status, and level of physical activity, to predict possible meals required to meet the users need. The micro- and macronutrients of food content are used for the computation and prediction of the potential foods required to meet the daily calorie needs. The functionality and performance of the model were tested using a sample of 30 volunteers from the University of Ghana. Results revealed that the model was able to predict both glycemic and non-glycemic foods based on the condition of the user as well as the macro- and micronutrients requirements. Moreover, the system is able to adequately track the progress of the user’s weight loss over time, daily nutritional needs, daily calorie intake, and predictions of meals that must be taken to avoid compromising their health. The proposed system can serve as a useful resource for individuals, dieticians, and other health management personnel for managing obesity, patients, and for training students in fields of dietetics and consumer science.

International Journal of Telemedicine and Applications
 Journal metrics
Acceptance rate25%
Submission to final decision89 days
Acceptance to publication89 days
CiteScore3.100
Journal Citation Indicator0.540
Impact Factor-
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