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Development of a Real-Time Thermoplastic Mask Compression Force Monitoring System Using Capacitive Force Sensor

Purpose: Thermoplastic masks keep patients in an appropriate position to ensure accurate radiation delivery. For a thermoplastic mask to maintain clinical efficacy, the mask should wrap the patient's surface properly and provide uniform pressure to all areas. However, to our best knowledge, no...

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Autores principales: Kim, Tae-Ho, Cho, Min-Seok, Shin, Dong-Seok, Shin, Dong Ho, Kim, Siyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9298856/
https://www.ncbi.nlm.nih.gov/pubmed/35875702
http://dx.doi.org/10.3389/frobt.2022.778594
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author Kim, Tae-Ho
Cho, Min-Seok
Shin, Dong-Seok
Shin, Dong Ho
Kim, Siyong
author_facet Kim, Tae-Ho
Cho, Min-Seok
Shin, Dong-Seok
Shin, Dong Ho
Kim, Siyong
author_sort Kim, Tae-Ho
collection PubMed
description Purpose: Thermoplastic masks keep patients in an appropriate position to ensure accurate radiation delivery. For a thermoplastic mask to maintain clinical efficacy, the mask should wrap the patient's surface properly and provide uniform pressure to all areas. However, to our best knowledge, no explicit method for achieving such a goal currently exists. Therefore, in this study, we intended to develop a real-time thermoplastic mask compression force (TMCF) monitoring system to measure compression force quantitatively. A prototype system was fabricated, and the feasibility of the proposed method was evaluated. Methods: The real-time TMCF monitoring system basically consists of four force sensor units, a microcontroller board (Arduino Bluno Mega 2560), a control PC, and an in-house software program. To evaluate the reproducibility of the TMCF monitoring system, both a reproducibility test using a micrometer and a setup reproducibility test using a head phantom were performed. Additionally, the reproducibility tests of mask setup and motion detection tests were carried out with a cohort of six volunteers. Results: The system provided stable pressure readings in all 10 trials during the sensor unit reproducibility test. The largest standard deviation (SD) among trials was about 36 gf/cm(2) (∼2.4% of the full-scale range). For five repeated mask setups on the phantom, the compression force variation of the mask was less than 39 gf/cm(2) (2.6% of the full-scale range). We were successful in making masks together with the monitoring system connected and demonstrated feasible utilization of the system. Compression force variations were observed among the volunteers and according to the location of the sensor (among forehead, both cheekbones, and chin). The TMCF monitoring system provided the information in real time on whether the mask was properly pressing the human subject as an immobilization tool. Conclusion: With the developed system, it is possible to monitor the effectiveness of the mask in real time by continuously measuring the compression force between the mask and patient during the treatment. The graphical user interface (GUI) of the monitoring system developed provides a warning signal when the compression force of the mask is insufficient. Although the number of volunteers participated in the study was small, the obtained preliminary results suggest that the system could ostensibly improve the setup accuracy of a thermoplastic mask.
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spelling pubmed-92988562022-07-21 Development of a Real-Time Thermoplastic Mask Compression Force Monitoring System Using Capacitive Force Sensor Kim, Tae-Ho Cho, Min-Seok Shin, Dong-Seok Shin, Dong Ho Kim, Siyong Front Robot AI Robotics and AI Purpose: Thermoplastic masks keep patients in an appropriate position to ensure accurate radiation delivery. For a thermoplastic mask to maintain clinical efficacy, the mask should wrap the patient's surface properly and provide uniform pressure to all areas. However, to our best knowledge, no explicit method for achieving such a goal currently exists. Therefore, in this study, we intended to develop a real-time thermoplastic mask compression force (TMCF) monitoring system to measure compression force quantitatively. A prototype system was fabricated, and the feasibility of the proposed method was evaluated. Methods: The real-time TMCF monitoring system basically consists of four force sensor units, a microcontroller board (Arduino Bluno Mega 2560), a control PC, and an in-house software program. To evaluate the reproducibility of the TMCF monitoring system, both a reproducibility test using a micrometer and a setup reproducibility test using a head phantom were performed. Additionally, the reproducibility tests of mask setup and motion detection tests were carried out with a cohort of six volunteers. Results: The system provided stable pressure readings in all 10 trials during the sensor unit reproducibility test. The largest standard deviation (SD) among trials was about 36 gf/cm(2) (∼2.4% of the full-scale range). For five repeated mask setups on the phantom, the compression force variation of the mask was less than 39 gf/cm(2) (2.6% of the full-scale range). We were successful in making masks together with the monitoring system connected and demonstrated feasible utilization of the system. Compression force variations were observed among the volunteers and according to the location of the sensor (among forehead, both cheekbones, and chin). The TMCF monitoring system provided the information in real time on whether the mask was properly pressing the human subject as an immobilization tool. Conclusion: With the developed system, it is possible to monitor the effectiveness of the mask in real time by continuously measuring the compression force between the mask and patient during the treatment. The graphical user interface (GUI) of the monitoring system developed provides a warning signal when the compression force of the mask is insufficient. Although the number of volunteers participated in the study was small, the obtained preliminary results suggest that the system could ostensibly improve the setup accuracy of a thermoplastic mask. Frontiers Media S.A. 2022-07-06 /pmc/articles/PMC9298856/ /pubmed/35875702 http://dx.doi.org/10.3389/frobt.2022.778594 Text en Copyright © 2022 Kim, Cho, Shin, Shin and Kim. 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
Kim, Tae-Ho
Cho, Min-Seok
Shin, Dong-Seok
Shin, Dong Ho
Kim, Siyong
Development of a Real-Time Thermoplastic Mask Compression Force Monitoring System Using Capacitive Force Sensor
title Development of a Real-Time Thermoplastic Mask Compression Force Monitoring System Using Capacitive Force Sensor
title_full Development of a Real-Time Thermoplastic Mask Compression Force Monitoring System Using Capacitive Force Sensor
title_fullStr Development of a Real-Time Thermoplastic Mask Compression Force Monitoring System Using Capacitive Force Sensor
title_full_unstemmed Development of a Real-Time Thermoplastic Mask Compression Force Monitoring System Using Capacitive Force Sensor
title_short Development of a Real-Time Thermoplastic Mask Compression Force Monitoring System Using Capacitive Force Sensor
title_sort development of a real-time thermoplastic mask compression force monitoring system using capacitive force sensor
topic Robotics and AI
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9298856/
https://www.ncbi.nlm.nih.gov/pubmed/35875702
http://dx.doi.org/10.3389/frobt.2022.778594
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