International Journal of Telemedicine and Applications最新文献

{"title":"An Enhanced Posture Prediction-Bayesian Network Algorithm for Sleep Posture Recognition in Wireless Body Area Networks","authors":"A. Roshini, K. Kiran","doi":"10.1155/2022/3102545","DOIUrl":"https://doi.org/10.1155/2022/3102545","url":null,"abstract":"Wireless body area networks have taken their unique recognition in providing consistent facilities in health monitoring. Several studies influence physiological signal monitoring through a centralized approach using star topology in regular activities like standing, walking, sitting, and running which are considered active postures. Unlike regular activities like walking, standing, sitting, and running, the in-bed sleep posture monitoring of a subject is highly necessary for those who have undergone surgery, victims of breathing problems, and victims of COVID-19 for whom oxygen imbalance is a major issue as the mortality rate in sleep is high due to unattended patients. Suggestions from the medical field state that the patients with the above-mentioned issues are highly suggested to follow the prone sleep posture that enables them to maintain the oxygen level in the human body. A distributed model of communication is used where mesh topology is used for the data packets to be carried in a relay fashion to the sink. Heartbeat rate (HBR) and image monitoring of the subject during sleep are closely monitored and taken as input to the proposed posture prediction-Bayesian network (PP-BN) to predict the consecutive postures to increase the accuracy rate of posture recognition. The accuracy rate of the model outperforms the existing classification and prediction algorithms which take the cleaned dataset as input for better prediction results.","PeriodicalId":45630,"journal":{"name":"International Journal of Telemedicine and Applications","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2022-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49615983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficacy of Telemedicine Utilization for Cardiac Outpatients' Care during the Pandemic of COVID-19: A Large Center Experience in the Wave of the Pandemic.","authors":"Wesam A Alhejily","doi":"10.1155/2022/4156436","DOIUrl":"10.1155/2022/4156436","url":null,"abstract":"<p><strong>Introduction: </strong>Synchronous telemedicine using teleconferencing may play a role in clinical care. In a tertiary care center, video conferencing-enhanced virtual clinics were established via a new application platform. They were introduced during COVID-19 pandemic to connect patients to trained health-care providers via a secured line. While maintaining patients' privacy, they were theorized to offer effective communications and continuous clinical care. In this cross-sectional cohort study, we ought to examine the impact of service and the assistance they may offer to cardiac patients in the outpatient setup.</p><p><strong>Methods: </strong>A prospective cohort study looking at all video-conferencing virtual clinics' visits during the pandemic with primary focus on cardiac outpatient clinic, addressing primary endpoints of need for admission or emergency visits from cardiac demises during the pandemic and secondary endpoint of patient satisfaction based on patients' experiences.</p><p><strong>Results: </strong>A total of 6000 live care video-based chats were made over 10 months period from March 10^th, 2020, to January 30^th, 2021, among which 277 patients were evaluated in the virtual cardiac clinic, of these 193 (69.7%) were males, with mean age of 48 ± 15.60 (22.3%), patients were requested to present to clinic for further evaluation and testing, 20 (7.2%) patients were asked to visit the emergency room, of whom 8 (2.8%) patients were hospitalized. All 8 were admitted for high-risk findings that require immediate medical attention, 4/8 underwent cardiac catheterization, mean duration of admission was 2 ± 1 days. When compared to regular walk-in care, there was a statistical difference in admission rate and emergency visits <i>p</i> = 0.001 and <i>p</i> = 0.0001, respectively, both were statistically higher in the virtual clinic. The satisfaction rate in a 5-scale grading system was 97% of 4 and above recommending the continuation of the service beyond pandemic time.</p><p><strong>Conclusions: </strong>Video-enhanced virtual cardiology clinic works safely and efficiently during COVID-19 pandemic with a difference in admission rate and ER visits when compared to walk-in clinic. It can be used during nonpandemic time to reduce load on hospital and clinic crowdedness. It also decreases the chances of COVID-19 transmission indirectly by reenforcing physical distance.</p>","PeriodicalId":45630,"journal":{"name":"International Journal of Telemedicine and Applications","volume":"2022 1","pages":"4156436"},"PeriodicalIF":3.1,"publicationDate":"2022-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9115730/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43580260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Smart Chatbot for Interactive Management in Beta Thalassemia Patients","authors":"Alma Mohammed Alturaiki, H. Banjar, A. Barefah, Salwa A. Alnajjar, S. Hindawi","doi":"10.1155/2022/9734518","DOIUrl":"https://doi.org/10.1155/2022/9734518","url":null,"abstract":"Background β-thalassemia is an inherited blood disorder that affects the production of hemoglobin molecules owing to the reduction or absence of beta chains. Transfusion therapy has had a key role in extending the lifespan of β-thalassemia patients. This life-saving therapy is linked to numerous assessments and complications that now comprise most thalassemia management considerations. Consequently, many patients do not receive adequate information about the required assessments, as indicated by evidence-based medical guidelines. Patients with β-thalassemia may benefit from chatbots that follow up on their condition and that provide the required assessment information. Self-management will hopefully have a positive impact on health outcomes. Objectives This study aims to develop a chatbot that can assist in the management of β-thalassemia by providing the assessment information required to monitor patients' statuses. Methods The chatbot operated as a messaging system. A question/answer system was created based on knowledge pertaining to β-thalassemia assembled from experts, medical guidelines, and articles. Recommendations regarding the patient's follow-up assessment are made based on the answers. Results A prototype was implemented to demonstrate how the chatbots could dynamically and flexibly provide the assessment information required to follow up on and monitor patients. A small sample of adults with β-thalassemia used the chatbot to examine the system's usability and perceived utility. A system usability scale and utility scale were implemented to complete a post-test survey. The chatbots were considered by 34 patients, of whom the majority (72%) found them easy to use, while more than 90% of patients considered their use beneficial. Most of the participants agreed that the chatbots could improve their knowledge about their β-thalassemia assessments. Conclusion Our findings suggest that chatbots can be beneficial to the development of recommended tests and management related to the assessment of β-thalassemia.","PeriodicalId":45630,"journal":{"name":"International Journal of Telemedicine and Applications","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2022-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48238043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Malaria Diagnosis Using a Lightweight Deep Convolutional Neural Network","authors":"Varun Magotra, Mukesh Kumar Rohil","doi":"10.1155/2022/4176982","DOIUrl":"https://doi.org/10.1155/2022/4176982","url":null,"abstract":"The applications of AI in the healthcare sector are increasing day by day. The application of convolutional neural network (CNN) and mask-region-based CNN (Mask-RCCN) to the medical domain has really revolutionized medical image analysis. CNNs have been prominently used for identification, classification, and feature extraction tasks, and they have delivered a great performance at these tasks. In our study, we propose a lightweight CNN, which requires less time to train, for identifying malaria parasitic red blood cells and distinguishing them from healthy red blood cells. To compare the accuracy of our model, we used transfer learning on two models, namely, the VGG-19 and the Inception v3. We train our model in three different configurations depending on the proportion of data being fed to the model for training. For all three configurations, our proposed model is able to achieve an accuracy of around 96%, which is higher than both the other models that we trained for the same three configurations. It shows that our model is able to perform better along with low computational requirements. Therefore, it can be used more efficiently and can be easily deployed for detecting malaria cells.","PeriodicalId":45630,"journal":{"name":"International Journal of Telemedicine and Applications","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2022-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44299229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Telepresence Robots at the Urology and Emergency Department: A Pilot Study Assessing Patients' and Healthcare Workers' Satisfaction","authors":"J. Laigaard, T. Fredskild, G. Fojecki","doi":"10.1155/2022/8787882","DOIUrl":"https://doi.org/10.1155/2022/8787882","url":null,"abstract":"COVID-19 intensified interest in telemedicine, yet no study has evaluated the use of a telepresence robot on unselected urological patients. Therefore, we performed a survey study of patients, bedside caregivers and urologists, investigating the satisfaction and applicability of a telepresence robot (Beam Pro, Suitable Technologies, USA) at the urology ward and emergency department. The primary outcome was the number of patient encounters solved without the urologist's physical presence. Between March 2021 and May 2021, patients, caregivers, and urologists filled in 42, 35, and 54 questionnaires, respectively. Most patients were male (79%), with a mean age of 64 (SD ± 17). Two of the department's ten urologists participated. The urologists responded that physical examination was required in 7 (13%) encounters. The caregivers would have preferred the urologist physically present in 11 (31%) cases. Most patients (71%) “agreed” or “strongly agreed” that they were willing to be attended by a telepresence robot at future evaluations and generally, patients gave high satisfaction scores. Though implementation among the department's urologists was a major challenge, participating urologists reported that physical presence could be avoided in 87% of the patient encounters. Studies of patient-reported outcome measures comparing telemedical and physical patient encounters are needed.","PeriodicalId":45630,"journal":{"name":"International Journal of Telemedicine and Applications","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2022-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48855134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Remote ECG Monitoring by ECG247 Smart Heart Sensor.","authors":"Jarle Jortveit,&nbsp;Rune Fensli","doi":"10.1155/2022/6812889","DOIUrl":"https://doi.org/10.1155/2022/6812889","url":null,"abstract":"<p><strong>Background: </strong>Heart rhythm disorders are common and may be associated with serious complications. The quality of the ECG signal is crucial to detect and classify arrhythmias. Most available devices for assessment arrhythmias do not allow for remote monitoring. The Norwegian ECG247 Smart Heart Sensor is a new remote patch monitor developed to simplify the assessment of arrhythmias. This study was aimed at evaluating the quality of the ECG signal from the ECG247 Smart Heart Sensor compared to standard 12-lead ECG.</p><p><strong>Methods: </strong>ECG recordings with ECG247 Smart Heart Sensor and a standard 12-lead ECG recorder were performed in 97 volunteers at Sorlandet Hospital, Arendal, Norway, in 2019. All ECGs were analysed by two independent cardiologists.</p><p><strong>Results: </strong>A total of 97 participants (53% men, age 48 (±14) years) were included in the study. The ability for both systems to use recorded ECG data for arrhythmia detection was good (100%). The quality of the P-wave (mean score 1.1 vs. 1.5) and the QRS complex (mean score 1.0 vs. 1.0) from the ECG247 Smart Heart Sensor and that from the 12-lead ECG were comparable (scale: 1: extremely good, 9: not accepted). Noise artefacts were a minor issue in all recordings.</p><p><strong>Conclusions: </strong>The ECG quality from the ECG247 Smart Heart Sensor was comparable to the ECG quality from the standard 12-lead ECG. The ECG247 Smart Heart Sensor may enable easy and remote diagnostics of heart rhythm disorders. This trial is registered with NCT04700865.</p>","PeriodicalId":45630,"journal":{"name":"International Journal of Telemedicine and Applications","volume":"2022 ","pages":"6812889"},"PeriodicalIF":4.4,"publicationDate":"2022-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8856830/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39939949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of Implementing Teleophthalmology Referral Guidelines Using the eyeSmart EMR App in 63,703 Patients from India.","authors":"Anthony Vipin Das,&nbsp;Rohit C Khanna,&nbsp;Niranjan Kumar,&nbsp;Padmaja Kumari Rani","doi":"10.1155/2022/8523131","DOIUrl":"https://doi.org/10.1155/2022/8523131","url":null,"abstract":"<p><strong>Objective: </strong>To describe the clinical indications and the impact of implementation of specific teleophthalmology referral guidelines in a large rural village vision centre network in India.</p><p><strong>Methods: </strong>This cross-sectional vision centre-based study included 1,016,284 patients presenting between January 2017 and March 2020. Patients who were referred for a teleophthalmology opinion were included as cases. The data were collected using the eyeSmart EMR app on a smart tablet. A training intervention was done to reinforce the implementation of targeted teleophthalmology referral guidelines.</p><p><strong>Results: </strong>Overall, 63,703 (6.3%) patients were referred for a teleophthalmology opinion and were included for analysis. The median age was 41 (IQR: 26-59) years, and adults (88.4%) were commonly referred for a consult. The two most common age groups were between 31-40 years (17.4%) and 21-30 years (16.3%), and the majority of patients were male (59.1%). The most common clinical indication was cornea and anterior segment disorders (71.05%). The most common queries for teleophthalmology referral before versus after the reinforcement of implementation of guidelines were red eye (33.4% vs. 45.6%) followed by cataract (21.2% vs. 8.1%). There was an increase in the red eye (<0.001) and a decrease in cataract (<0.001) which was statistically significant. The proportion of patients for whom a teleophthalmology consult could have been requested but not sent was minimal (2.3%).</p><p><strong>Conclusion: </strong>Implementation of targeted teleophthalmology referral guidelines enables an effective triage to seek opinion for more pertinent ocular diseases that require care. Adult male patients with cornea and anterior segment disorders are most commonly referred for a teleophthalmology opinion.</p>","PeriodicalId":45630,"journal":{"name":"International Journal of Telemedicine and Applications","volume":"2022 ","pages":"8523131"},"PeriodicalIF":4.4,"publicationDate":"2022-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8813305/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39893892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Feedback Artificial Shuffled Shepherd Optimization-Based Deep Maxout Network for Human Emotion Recognition Using EEG Signals","authors":"K. S. Bhanumathi, D. Jayadevappa, Satish Tunga","doi":"10.1155/2022/3749413","DOIUrl":"https://doi.org/10.1155/2022/3749413","url":null,"abstract":"Emotion recognition is very important for the humans in order to enhance the self-awareness and react correctly to the actions around them. Based on the complication and series of emotions, EEG-enabled emotion recognition is still a difficult issue. Hence, an effective human recognition approach is designed using the proposed feedback artificial shuffled shepherd optimization- (FASSO-) based deep maxout network (DMN) for recognizing emotions using EEG signals. The proposed technique incorporates feedback artificial tree (FAT) algorithm and shuffled shepherd optimization algorithm (SSOA). Here, median filter is used for preprocessing to remove the noise present in the EEG signals. The features, like DWT, spectral flatness, logarithmic band power, fluctuation index, spectral decrease, spectral roll-off, and relative energy, are extracted to perform further processing. Based on the data augmented results, emotion recognition can be accomplished using the DMN, where the training process of the DMN is performed using the proposed FASSO method. Furthermore, the experimental results and performance analysis of the proposed algorithm provide efficient performance with respect to accuracy, specificity, and sensitivity with the maximal values of 0.889, 0.89, and 0.886, respectively.","PeriodicalId":45630,"journal":{"name":"International Journal of Telemedicine and Applications","volume":" ","pages":""},"PeriodicalIF":4.4,"publicationDate":"2022-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47257820","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of COVID-19 on the 937 Telephone Medical Consultation Service in Saudi Arabia.","authors":"Najla J Alhraiwil,&nbsp;Sinaa Al-Aqeel,&nbsp;Amjad F AlFaleh,&nbsp;Alaa A AlAgeel,&nbsp;Mostafa A AlAbed,&nbsp;Walid A Al-Shroby","doi":"10.1155/2022/4181322","DOIUrl":"https://doi.org/10.1155/2022/4181322","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":45630,"journal":{"name":"International Journal of Telemedicine and Applications","volume":"2022 ","pages":"4181322"},"PeriodicalIF":4.4,"publicationDate":"2022-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8764273/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39957474","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Setting Up a Teleneurology Clinic during COVID-19 Pandemic: Experience from an Academic Practice.","authors":"Nakul Katyal,&nbsp;Naureen Narula,&nbsp;Raghav Govindarajan,&nbsp;Pradeep Sahota","doi":"10.1155/2022/4776328","DOIUrl":"https://doi.org/10.1155/2022/4776328","url":null,"abstract":"<p><p>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.</p>","PeriodicalId":45630,"journal":{"name":"International Journal of Telemedicine and Applications","volume":"2022 ","pages":"4776328"},"PeriodicalIF":4.4,"publicationDate":"2022-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8764272/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39957475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}