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A COVID-19 Emergency Response for Remote Control of a Dialysis Machine with Mobile HRI
Healthcare workers face a high risk of contagion during a pandemic due to their close proximity to patients. The situation is further exacerbated in the case of a shortage of personal protective equipment that can increase the risk of exposure for the healthcare workers and even non-pandemic related...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8275272/ https://www.ncbi.nlm.nih.gov/pubmed/34262944 http://dx.doi.org/10.3389/frobt.2021.612855 |
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author | Wazir, Hassam Khan Lourido, Christian Chacko, Sonia Mary Kapila, Vikram |
author_facet | Wazir, Hassam Khan Lourido, Christian Chacko, Sonia Mary Kapila, Vikram |
author_sort | Wazir, Hassam Khan |
collection | PubMed |
description | Healthcare workers face a high risk of contagion during a pandemic due to their close proximity to patients. The situation is further exacerbated in the case of a shortage of personal protective equipment that can increase the risk of exposure for the healthcare workers and even non-pandemic related patients, such as those on dialysis. In this study, we propose an emergency, non-invasive remote monitoring and control response system to retrofit dialysis machines with robotic manipulators for safely supporting the treatment of patients with acute kidney disease. Specifically, as a proof-of-concept, we mock-up the touchscreen instrument control panel of a dialysis machine and live-stream it to a remote user’s tablet computer device. Then, the user performs touch-based interactions on the tablet device to send commands to the robot to manipulate the instrument controls on the touchscreen of the dialysis machine. To evaluate the performance of the proposed system, we conduct an accuracy test. Moreover, we perform qualitative user studies using two modes of interaction with the designed system to measure the user task load and system usability and to obtain user feedback. The two modes of interaction included a touch-based interaction using a tablet device and a click-based interaction using a computer. The results indicate no statistically significant difference in the relatively low task load experienced by the users for both modes of interaction. Moreover, the system usability survey results reveal no statistically significant difference in the user experience for both modes of interaction except that users experienced a more consistent performance with the click-based interaction vs. the touch-based interaction. Based on the user feedback, we suggest an improvement to the proposed system and illustrate an implementation that corrects the distorted perception of the instrumentation control panel live-stream for a better and consistent user experience. |
format | Online Article Text |
id | pubmed-8275272 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82752722021-07-13 A COVID-19 Emergency Response for Remote Control of a Dialysis Machine with Mobile HRI Wazir, Hassam Khan Lourido, Christian Chacko, Sonia Mary Kapila, Vikram Front Robot AI Robotics and AI Healthcare workers face a high risk of contagion during a pandemic due to their close proximity to patients. The situation is further exacerbated in the case of a shortage of personal protective equipment that can increase the risk of exposure for the healthcare workers and even non-pandemic related patients, such as those on dialysis. In this study, we propose an emergency, non-invasive remote monitoring and control response system to retrofit dialysis machines with robotic manipulators for safely supporting the treatment of patients with acute kidney disease. Specifically, as a proof-of-concept, we mock-up the touchscreen instrument control panel of a dialysis machine and live-stream it to a remote user’s tablet computer device. Then, the user performs touch-based interactions on the tablet device to send commands to the robot to manipulate the instrument controls on the touchscreen of the dialysis machine. To evaluate the performance of the proposed system, we conduct an accuracy test. Moreover, we perform qualitative user studies using two modes of interaction with the designed system to measure the user task load and system usability and to obtain user feedback. The two modes of interaction included a touch-based interaction using a tablet device and a click-based interaction using a computer. The results indicate no statistically significant difference in the relatively low task load experienced by the users for both modes of interaction. Moreover, the system usability survey results reveal no statistically significant difference in the user experience for both modes of interaction except that users experienced a more consistent performance with the click-based interaction vs. the touch-based interaction. Based on the user feedback, we suggest an improvement to the proposed system and illustrate an implementation that corrects the distorted perception of the instrumentation control panel live-stream for a better and consistent user experience. Frontiers Media S.A. 2021-05-07 /pmc/articles/PMC8275272/ /pubmed/34262944 http://dx.doi.org/10.3389/frobt.2021.612855 Text en Copyright © 2021 Wazir, Lourido, Chacko and Kapila. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Robotics and AI Wazir, Hassam Khan Lourido, Christian Chacko, Sonia Mary Kapila, Vikram A COVID-19 Emergency Response for Remote Control of a Dialysis Machine with Mobile HRI |
title | A COVID-19 Emergency Response for Remote Control of a Dialysis Machine with Mobile HRI |
title_full | A COVID-19 Emergency Response for Remote Control of a Dialysis Machine with Mobile HRI |
title_fullStr | A COVID-19 Emergency Response for Remote Control of a Dialysis Machine with Mobile HRI |
title_full_unstemmed | A COVID-19 Emergency Response for Remote Control of a Dialysis Machine with Mobile HRI |
title_short | A COVID-19 Emergency Response for Remote Control of a Dialysis Machine with Mobile HRI |
title_sort | covid-19 emergency response for remote control of a dialysis machine with mobile hri |
topic | Robotics and AI |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8275272/ https://www.ncbi.nlm.nih.gov/pubmed/34262944 http://dx.doi.org/10.3389/frobt.2021.612855 |
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