Background. The implementation of medical digital technologies can provide better accessibility and flexibility of healthcare for the public. It encompasses the availability of open information on the health, treatment, complications, and recent progress on biomedical research. At present, even in low-income countries, diagnostic and medical services are becoming more accessible and available. However, many issues related to digital health technologies remain unmet, including the reliability, safety, testing, and ethical aspects. Purpose. The aim of the review is to discuss and analyze the recent progress on the application of big data, artificial intelligence, telemedicine, block-chain platforms, smart devices in healthcare, and medical education. Basic Design. The publication search was carried out using Google Scholar, PubMed, Web of Sciences, Medline, Wiley Online Library, and CrossRef databases. The review highlights the applications of artificial intelligence, &#x201C;big data,&#x201D; telemedicine and block-chain technologies, and smart devices (internet of things) for solving the real problems in healthcare and medical education. Major Findings. We identified 252 papers related to the digital health area. However, the number of papers discussed in the review was limited to 152 due to the exclusion criteria. The literature search demonstrated that digital health technologies became highly sought due to recent pandemics, including COVID-19. The disastrous dissemination of COVID-19 through all continents triggered the need for fast and effective solutions to localize, manage, and treat the viral infection. In this regard, the use of telemedicine and other e-health technologies might help to lessen the pressure on healthcare systems. Summary. Digital platforms can help optimize diagnosis, consulting, and treatment of patients. However, due to the lack of official regulations and recommendations, the stakeholders, including private and governmental organizations, are facing the problem with adequate validation and approbation of novel digital health technologies. In this regard, proper scientific research is required before a digital product is deployed for the healthcare sector.

Maksut Senbekov

Timur Saliev

Zhanar Bukeyeva

Aigul Almabayeva

Marina Zhanaliyeva

Nazym Aitenova

Yerzhan Toishibekov

Ildar Fakhradiyev

The Recent Progress and Applications of Digital Technologies in Healthcare: A Review

Ming Li

Wei Xiong

Yongjian Li

Corrigendum to &#x201C;Wearable Measurement of ECG Signals Based on Smart Clothing&#x201D;

Aging in place is a notion which supports the independent living of older adults at their own place of residence for as long as possible. To support this alternative living which can be in contrast to various other types of assisted living options, modes of monitoring technology need to be explored and studied in order to determine a balance between the preservation of privacy and adequacy of sensed information for better estimation and visualization of movements and activities. In this paper, we explore such monitoring paradigm on how a network of RGB-D sensors can be utilized for this purpose. This type of sensor offers both visual and depth sensing modalities from the scene where the information can be fused and coded for better protection of privacy. For this purpose, we introduce the novel notion of passive observer. This observer is only triggered by detecting the absence of movements of older adults in the scene. This is accomplished by classifying and localizing objects in the monitoring scene from both before and after the detection of movements. A deep learning tool is utilized for visual classification of known objects in the physical scene followed by virtual reality reconstructing of the scene where the shape and location of objects are recreated. Such reconstruction can be used as a visual summary in order to identify objects which were handled by an older adult in-between observation. The simplified virtual scene can be used, for example, by caregivers or monitoring personnel in order to assist in detecting any anomalies. This virtual visualization can offer a high level of privacy protection without having any direct visual access to the monitoring scene. In addition, using the scene graph representation, an automatic decision-making tool is proposed where spatial relationships between the objects can be used to estimate the expected activities. The results of this paper are demonstrated through two case studies.

Shahram Payandeh

Jim Park

Passive Observer of Activities for Aging in Place Using a Network of RGB-D Sensors

This paper describes the design and implementation of a software system to improve the management of diabetes using a machine learning approach and to demonstrate and evaluate its effectiveness in controlling diabetes. The proposed approach for this management system handles the various factors that affect the health of people with diabetes by combining multiple artificial intelligence algorithms. The proposed framework factors the diabetes management problem into subgoals: building a Tensorflow neural network model for food classification; thus, it allows users to upload an image to determine if a meal is recommended for consumption; implementing K-Nearest Neighbour (KNN) algorithm to recommend meals; using cognitive sciences to build a diabetes question and answer chatbot; tracking user activity, user geolocation, and generating pdfs of logged blood sugar readings. The food recognition model was evaluated with cross-entropy metrics that support validation using Neural networks with a backpropagation algorithm. The model learned features of the images fed from local Ghanaian dishes with specific nutritional value and essence in managing diabetics and provided accurate image classification with given labels and corresponding accuracy. The model achieved specified goals by predicting with high accuracy, labels of new images. The food recognition and classification model achieved over 95% accuracy levels for specific calorie intakes. The performance of the meal recommender model and question and answer chatbot was tested with a designed cross-platform user-friendly interface using Cordova and Ionic Frameworks for software development for both mobile and web applications. The system recommended meals to meet the calorific needs of users successfully using KNN (with <svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="17.802pt" style="vertical-align:-0.2063999pt" id="M1" height="9.49473pt" version="1.1" viewBox="-0.0498162 -9.28833 17.802 9.49473"><g transform="matrix(.013,0,0,-0.013,0,0)"><path id="g113-108" d="M480 416C480 431 465 448 438 448C388 448 312 383 252 330C217 299 188 273 155 237H153L257 680C262 700 263 712 253 712C240 712 183 684 97 674L92 648L126 647C166 646 172 645 163 606L23 -6L29 -12C51 -5 77 2 107 8C115 62 130 128 142 180C153 193 179 220 204 241C231 170 259 106 288 54C317 0 336 -12 358 -12C381 -12 423 2 477 80L460 100C434 74 408 54 398 54C385 54 374 65 351 107C326 154 282 241 263 299C296 332 351 377 403 377C424 377 436 372 445 368C449 366 456 368 462 375C472 386 480 402 480 416Z"/></g><g transform="matrix(.013,0,0,-0.013,10.171,0)"><path id="g117-34" d="M535 323V373H52V323H535ZM535 138V188H52V138H535Z"/></g></svg><svg xmlns:xlink="http://www.w3.org/1999/xlink" xmlns="http://www.w3.org/2000/svg" width="6.416pt" style="vertical-align:-0.2063999pt" height="9.49473pt" version="1.1" viewBox="21.384183800000002 -9.28833 6.416 9.49473"><g transform="matrix(.013,0,0,-0.013,21.434,0)"><path id="g113-54" d="M153 550H386L412 615L406 623H120L82 318C104 327 142 338 184 338C294 338 347 275 347 187C347 112 305 39 221 39C160 39 119 71 97 89C88 97 80 96 71 90C59 80 50 67 49 57C48 45 52 36 66 23C80 9 123 -12 169 -12C221 -11 288 15 342 59C403 109 431 165 431 225C431 308 366 395 238 395C212 395 165 379 127 364L153 550Z"/></g></svg>) and answered questions asked in a human-like way. The implemented system would solve the problem of managing activity, dieting recommendations, and medication notification of diabetics.

Robert A. Sowah

Adelaide A. Bampoe-Addo

Stephen K. Armoo

Firibu K. Saalia

Francis Gatsi

Baffour Sarkodie-Mensah

Design and Development of Diabetes Management System Using Machine Learning

Introduction. False alarm reduction is an important challenge in self-care, whereas one of the most important false alarm causes in the cardiology domain is electrodes misplacements in ECG recordings, the main investigations to perform for early and pervasive detection of cardiovascular diseases. In this context, we present and assess a new method for electrode reversals identification for Mason-Likar based 3D ECG recording systems which are especially convenient to use in self-care and allow to achieve, as previously reported, high computerized ischemia detection accuracy. Methods. We mathematically simulate the effect of the six pairwise reversals of the LA, RA, LL, and C2 electrodes on the three ECG leads I, II, and V2. Our approach then consists in performing serial comparisons of the newly recorded 3D ECG and of the six derived ECGs simulating an electrode reversal with a standard, 12-lead reference ECG by means of the CAVIAR software. We further use a scoring method to compare these analysis results and then apply a decision tree model to extract the most relevant measurements in a learning set of 121 patients recorded in ICU. Results. The comparison of the seven sets of serial analysis results from the learning set resulted in the determination of a composite criteria involving four measurements of spatial orientation changes of QRS and T and providing a reversal identification accuracy of 100&#x0025;. Almost the same results, with 99.99&#x0025; of sensitivity and 100&#x0025; of specificity, were obtained in two test sets from 90 patients, composed of 2098 and 2036 representative ECG beats respectively recorded during PTCA balloon inflation, a procedure which mimics ischemia, and before PTCA for control. Conclusion. Personalized automatic detection of ECG electrode cable interchanges can reach almost the maximal accuracy of 100&#x0025; in self-care, and can be performed in almost real time.

Jocelyne Fayn

Paul Rubel

False Alarm Reduction in Self-Care by Personalized Automatic Detection of ECG Electrode Cable Interchanges

Background. Advances in information and communication technologies (ICTs) represent a growing platform for the expansion of healthcare related services, but there is little information on how generational differences might account for distinct patterns of use and interest for ICTs. Our study aims to achieve a better understanding on how generational cohorts might influence the use and preferences for ICTs among patients with obstructive lung diseases in Latin America. Materials and Methods. We conducted an anonymous cross-sectional survey-based study, involving 968 patients with obstructive lung diseases (OLD) in Latin America. Patients rated their frequency of use and preferences of ICTs through a modified version of the Michigan Questionnaire. Chi-square test for association and adjusted regression analyses were performed. Results. Of all, 63.6&#x0025; of participants had Internet access. Younger generations, in particular Generation Z and Millennials, had the highest rate of Internet access and smartphone ownership, as well as of overall frequency of ICT use. Web-based Internet was found to be the main source to seek information about the disease (36.9&#x0025;) across all generational cohorts. Generation Z and Millennials presented the highest odds to be interested in using Twitter (OR 31.79 and 8.86) for receiving health-related information, and email (OR 4.87 and 4.86) as the preferred way to ask physicians information related to their disease through ICTs. Conclusion. Generational cohorts influence the use and preferences for ICTs among patients with obstructive lung diseases. Younger generational cohorts were associated with higher access to the Internet and smartphone ownership, as well as higher interest for using ICTs to receive and ask for health-related information.

Ivan Cherrez-Ojeda

Valeria L. Mata

Emanuel Vanegas

Miguel Felix

Jonathan A. Bernstein

Fanny M. Jim&#x00E9;nez

Juan Carlos Calderon

Peter Chedraui

Antonio WD Gavilanes

Influence of Generational Cohorts on the Preferences for Information and Communication Technologies in Latin American Patients with Obstructive Lung Diseases

Smart clothing that can measure electrocardiogram (ECG) signals and monitor the health status of people meets the needs of our increasingly aging society. However, the conventional measurement of ECG signals is complicated and its electrodes can cause irritation to the skin, which makes the conventional measurement method unsuitable for applications in smart clothing. In this paper, a novel wearable measurement of ECG signals is proposed. There are only three ECG textile electrodes knitted into the fabric of smart clothing. The acquired ECG signals can be transmitted to a smartphone via Bluetooth, and they can also be sent out to a PC terminal by a smartphone via WiFi or Internet. To get more significant ECG signals, the ECG differential signal between two electrodes is calculated based on a spherical volume conductor model, and the best positions on the surface of a human body for two textile electrodes to measure ECG signals are simulated by using the body-surface potential mapping (BSPM) data. The results show that position 12 in the lower right and position 11 in the upper left of the human body are the best for the two electrodes to measure ECG signals, and the presented wearable measurement can obtain good performance when one person is under the conditions of sleeping and jogging.

Wearable Measurement of ECG Signals Based on Smart Clothing

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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 - Table of contents 2020

International Journal of Telemedicine and Applications | Hindawi

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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

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International Journal of Telemedicine and Applications