Super-Resolution-Empowered Adaptive Medical Video Streaming in Telemedicine Systems

Due to influence of COVID-19, telemedicine is becoming more and more important. High-quality medical videos can provide a physician with a better visual experience and increase the accuracy of disease diagnosis, but this requires a dramatic increase in bandwidth compared to that required by regular videos. Existing adaptive video-streaming approaches cannot successfully provide high-resolution video-streaming services under poor or fluctuating network conditions with limited bandwidth. In this paper, we propose a super-resolution-empowered adaptive medical video streaming in telemedicine system (named SR-Telemedicine) to provide high quality of experience (QoE) videos for the physician while saving the network bandwidth. In SR-Telemedicine, very low-resolution video chunks are first transmitted from the patient to an edge computing node near the physician. Then, a video super-resolution (VSR) model is employed at the edge to reconstruct the low-resolution video chunks into high-resolution ones with an appropriate high-resolution level (such as 720p or 1080p). Furthermore, the neural network of VSR model is designed to be scalable and can be determined dynamically. Based on the time-varying computational capability of the edge computing node and the network condition, a double deep Q-Network (DDQN)-based algorithm is proposed to jointly select the optimal reconstructed high-resolution level and the scale of the VSR model. Finally, extensive experiments based on real-world traces are carried out, and the experimental results illustrate that the proposed SR-Telemedicine system can improve the QoE of medical videos by 17–79% compared to three baseline algorithms. © 2022 by the authors.

Telemedicine use during COVID-19 pandemics and associated factors among health professionals working in health facilities at resource-limited setting 2021.

Background: Digitizing healthcare has been a potential solution for transforming healthcare service delivery in the era of COVID-19 pandemics. To limit and minimize the virus spread, telemedicine helps control and prevent the pandemic by delivering healthcare services over long distances using Information communication technology. The objective of the study was to determine the level of telemedicine utilization among health professionals in the era of the COVID-19 Pandemic and the factors associated with it. Methods: An institutional-based cross-sectional study design was used to collect data from 845 healthcare professionals. A pilot study was conducted on 5% of the study participants before the actual data collection process. After completion, changes were made based on the pilot study results, and a Cronbach alpha value of 0.76 was obtained. Descriptive and binary logistic regression models were used. Variables with a P-Value of less than or equal to 0.2 from the bivariable analysis were entered into the multivariable analysis. The odds ratio, 95% confidence interval, and p-value less than 0.05 were used to interpret a significant association, Hosmer-Lemeshow goodness-of-fit test, and the multicollinearity test were used to assess the assumptions. Result: 64.2% of the respondents had good use of telemedicine during COVID-19 with a response rate of 87.2%. 507 (62.8%) were male, and 525(71.2%) reported by nearly threefold (AOR = 2.96, % CI: [1.54-5.76]), IT support staff in the health facility (AOR = 8.32, 95 %CI: [4.77-14.52]), ICT training (AOR = 4.15, % CI: [2.13-8.02]), the frequency of searching health information (AOR = 6.19, % CI: [2.12-18.07]), and social media used (AOR = 3.46, % CI: [1.43-8.32]) were found significantly associated with health professionals' use of telemedicine. Conclusion: The majority of healthcare providers practice telemedicine to control and prevent the spread of the COVID-19 virus. However, the availability of the internet, the presence of IT support staff, ICT training, the frequency of searching for health information, and the use of social media were significantly associated with the level of telemedicine utilization. Initiatives for full implementation of telemedicine in the health facility and motivating the health professionals are needed to carry out their medical practice by providing training and improving internet access in health facilities.

Evidence of the Sequential Changes of Lung Sounds in COVID-19 Pneumonia Using a Novel Wireless Stethoscope with the Telemedicine System.

A 60-year-old woman was admitted to our hospital due to coronavirus disease 2019 (COVID-19) pneumonia with a chief complaint of persistent low-grade fever and dry cough for two weeks. Thoracic computed tomography demonstrated a crazy paving pattern in the bilateral lower lobes. In a COVID-19 ward, we used a novel wireless stethoscope with a telemedicine system and successfully recorded and shared the lung sounds in real-time between the red and green zones. The fine crackles at the posterior right lower lung fields changed from mid-to-late (day 1) to late inspiratory crackles (day 3), which disappeared at day 5 along with an improvement in both the clinical symptoms and thoracic CT findings.

Monitoring and Management of Home-Quarantined Patients With COVID-19 Using a WeChat-Based Telemedicine System: Retrospective Cohort Study.

BACKGROUND: Most patients with coronavirus disease (COVID-19) who show mild symptoms are sent home by physicians to recover. However, the condition of some of these patients becomes severe or critical as the disease progresses. OBJECTIVE: The aim of this study was to evaluate a telemedicine model that was developed to address the challenges of treating patients with progressive COVID-19 who are home-quarantined and shortages in the medical workforce. METHODS: A telemedicine system was developed to continuously monitor the progression of home-quarantined patients with COVID-19. The system was built based on a popular social media smartphone app called WeChat; the app was used to establish two-way communication between a multidisciplinary team consisting of 7 medical workers and 188 home-quarantined individuals (including 74 confirmed patients with COVID-19). The system helped patients self-assess their conditions and update the multidisciplinary team through a telemedicine form stored on a cloud service, based on which the multidisciplinary team made treatment decisions. We evaluated this telemedicine system via a single-center retrospective study conducted at Tongji Hospital in Wuhan, China, in January 2020. RESULTS: Among 188 individuals using the telemedicine system, 114 (60.6%) were not infected with COVID-19 and were dismissed. Of the 74 confirmed patients with COVID-19, 26 (35%) recovered during the study period and voluntarily stopped using the system. The remaining 48/76 confirmed patients with COVID-19 (63%) used the system until the end of the study, including 6 patients whose conditions progressed to severe or critical. These 6 patients were admitted to hospital and were stabilized (one received extracorporeal membrane oxygenation support for 17 days). All 74 patients with COVID-19 eventually recovered. Through a comparison of the monitored symptoms between hospitalized and nonhospitalized patients, we found prolonged persistence and deterioration of fever, dyspnea, lack of strength, and muscle soreness to be diagnostic of need for hospitalization. CONCLUSIONS: By continuously monitoring the changes in several key symptoms, the telemedicine system reduces the risks of delayed hospitalization due to disease progression for patients with COVID-19 quarantined at home. The system uses a set of scales for quarantine management assessment that enables patients to self-assess their conditions. The results are useful for medical staff to identify disease progression and, hence, make appropriate and timely treatment decisions. The system requires few staff to manage a large cohort of patients. In addition, the system can solicit help from recovered but self-quarantined medical workers to alleviate shortages in the medical workforce and free healthy medical workers to fight COVID-19 on the front line. Thus, it optimizes the usage of local medical resources and prevents cross-infections among medical workers and patients.