Swab Testing Robotic Arm
Journal: International Journal of Science and Research (IJSR) (Vol.11, No. 7)Publication Date: 2022-07-05
Authors : Sairaj U. Kerkar; Jyothi Warrier; U. R. Bagal;
Page : 1297-1301
Keywords : COVID-19 disease; oropharyngeal-swab testing; robotic arm; machine learning algorithm; healthcare workers;
Abstract
This review paper describes the development of robotic arm swab testing system for COVID-19 disease and the evaluation of its safety and efficacy for the oropharyngeal-swab testing method in coronavirus detection. In this system, machine learning algorithms are used to detect the cotton swab and the region of swabbing, i.e., the back of the human throat. It employs a serially connected microcontroller-based robotic arm to pick up the cotton swab stick and perform the swab test by swabbing the cotton swab stick into the patient's throat and dropping the cotton swab stick back into the transportation test tube using a gripper. The main objective behind introducing this system is to reduce the risk to the lives of healthcare workers who perform swab testing due to aerosol from patients during the process of testing. Also the quality of manual swab testing is inconsistent among different collectors, which may lead to misdiagnosis. The replacement of manual testing by a robot has the potential to avoid close contact between healthcare workers and patients, and thus reduce the risk of Corona virus infection during testing.
Other Latest Articles
- Significance of High-Resolution Computed Tomography (HRCT) Chest in Screening Hospital Admissions for Coronavirus Disease (COVID-19) in Preoperative and Non-COVID-19 Clinical Settings
- Assessment of awareness of Ayushman Bharat Arogya Karnataka Scheme among Patients of Orthopaedic Department in Tertiary Care Hospital
- Application of Natural Fibers as Composite Reinforcement Materials in Fabrication of Trans-Tibial Prosthetic Sockets
- Development of Methodology for Identification of Landslide Susceptible areas along NH-10 from Singtam to Gangtok, East Sikkim using GIS based Modelling
- A Comparative Review of Recent Architectures of Convolutional Neural Networks
Last modified: 2022-09-07 15:19:11