A New Robotic Application for COVID-19 Specimen Collection Process

Author:

Deniz CengizORCID,Gökmen Gürsel

Abstract

Covid-19 manual specimen collection process is too critical for health care workers due to they are able to getting infection from Covid-19-patient during the medical interaction. The purpose of this study, a novel robotic application is developed to achieve automatic specimen collection process for new corona virus (COVID-19). This application is a protection tool for health care workers for the Covid-19 pandemic. This robotic application easily and safely complete the sampling process task and assist to health care workers to prevent infection. The application is basically consist of a collaborative robot (COBOT), base plate, fixtures and a gripper. There are co-operation activities between the COBOT and health care worker to complete all tasks. The robotic application has been tested in the plant health care center as a prototype. The cycle-time (192 sec) for the robotic process needs to be improved. The Manual process is still %60 faster than robotic application. The biggest challenge in this application is patient’s mouth and nose physical size changes. Robot movements for the specimen collection in nose and mouth are arranged just based on the fixed point. This needs to be improved according to size changes. Covid-19 specimen collection process with a robotic application has been presented which don’t need any health care worker interaction with patient. This application needs to be improved related with above challenges to make a shelf product. It will create valuable impact and save lives in this pandemic.

Publisher

Universitas Muhammadiyah Yogyakarta

Subject

Artificial Intelligence,Control and Systems Engineering

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. COBOTS;Advances in Computational Intelligence and Robotics;2024-06-06

2. A review of external sensors for human detection in a human robot collaborative environment;Journal of Intelligent Manufacturing;2024-04-04

3. Systematic Review of Recent Trends of Industry 5.0 with Assistive Technologies in Higher Education and Smart Healthcare;Applied Intelligence and Informatics;2024

4. Hand-in-Hand: Investigating Mechanical Tracking for User Identification in Cobot Interaction;Proceedings of the 22nd International Conference on Mobile and Ubiquitous Multimedia;2023-12-03

5. A Research on the Developing and Increasing Roles of Collaborative Robots in the Covid-19 Pandemic Process;Mehmet Akif Ersoy Üniversitesi Fen Bilimleri Enstitüsü Dergisi;2022-10-20

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