Literature DB >> 35125927

An enhanced algorithm for improving real-time video transmission for tele-training education.

Pooja Maharjan1, Abeer Alsadoon1,2,3,4, P W C Prasad1,2,3,5, Ahmad B Al-Khalil6, Oday D Jerew4, Ghossoon Alsadoon7, Binod Chapagain1.   

Abstract

Tele-training in surgical education has not been effectively implemented. There is a stringent need for a high transmission rate, reliability, throughput, and reduced distortion for high-quality video transmission in the real-time network. This work aims to propose a system that improves video quality during real-time surgical tele-training. The proposed approach aims to minimise the video frame's total distortion, ensuring better flow rate allocation and enhancing the video frames' reliability. The proposed system consists of a proposed algorithm for Enhancing Video Quality, Distorting Minimization, Bandwidth efficiency, and Reliability Maximization called (EVQDMBRM) algorithm. The proposed algorithm reduces the video frame's total distortion. In addition, it enhances the video quality in a real-time network by dynamically allocating the flow rate at the video source and maximizing the transmission reliability of the video frames. The result shows that the proposed EVQDMBRM algorithm improves the video quality with the minimized total distortion. Therefore, it improves the Peak Signal to Noise Ratio (PSNR) average by 51.13 dB against 47.28 dB in the existing systems. Furthermore, it reduces the video frames processing time average by 58.2 milliseconds (ms) against 76.1, and the end-to-end delay average by 114.57 ms against 133.58 ms comparing to the traditional methods. The proposed system concentrates on minimizing video distortion and improving the surgical video transmission quality by using an EVQDMBRM algorithm. It provides the mechanism to allocate the video rate at the source dynamically. Besides that, it minimizes the packet loss ratio and probing status, which estimates the available bandwidth.
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022.

Entities:  

Keywords:  Distortion minimization; Heterogeneous wireless networks; Reliability; Surgical tele-training; Video quality

Year:  2022        PMID: 35125927      PMCID: PMC8809212          DOI: 10.1007/s11042-022-12045-5

Source DB:  PubMed          Journal:  Multimed Tools Appl        ISSN: 1380-7501            Impact factor:   2.577


  5 in total

1.  Real-Time Learning Through Telemedicine Enhances Professional Training in Rural Emergency Departments.

Authors:  Xi Zhu; Kimberly A S Merchant; Nicholas M Mohr; Amy J Wittrock; Amanda L Bell; Marcia M Ward
Journal:  Telemed J E Health       Date:  2020-06-17       Impact factor: 3.536

2.  Advanced head and neck surgery training during the COVID-19 pandemic.

Authors:  Babak Givi; Michael G Moore; Arnaud F Bewley; Charles S Coffey; Marc A Cohen; Amy C Hessel; Scharukh Jalisi; Steven Kang; Jason G Newman; Liana Puscas; Maisie Shindo; Andrew Shuman; Punam Thakkar; Donald T Weed; Ara Chalian
Journal:  Head Neck       Date:  2020-05-08       Impact factor: 3.147

3.  Ten Rules for Implementation of a Telemedicine Program to Care for Patients with Asthma.

Authors:  Yudy K Persaud; Jay M Portnoy
Journal:  J Allergy Clin Immunol Pract       Date:  2020-10-08

4.  Robotics and AI for Teleoperation, Tele-Assessment, and Tele-Training for Surgery in the Era of COVID-19: Existing Challenges, and Future Vision.

Authors:  Navid Feizi; Mahdi Tavakoli; Rajni V Patel; S Farokh Atashzar
Journal:  Front Robot AI       Date:  2021-04-14

5.  Telehealth for Upper Extremity Conditions: Perceptions of the Patient and Provider.

Authors:  Brian M Katt; Casey Imbergamo; Daniel Fletcher; Daren Aita; Michael Nakashian; Moody Kwok; Pedro K Beredjiklian
Journal:  J Am Acad Orthop Surg Glob Res Rev       Date:  2020-09
  5 in total

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