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Novel Software for Pain Drawing Analysis
Introduction Pain drawings (PDs) are an important component of the assessment of a patient with pain. Although analog pain drawings (APDs), such as pen-on-paper drawings, have been extensively used in clinical assessment and clinical research, there is a lack of digital pain drawing (DPD) software t...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cureus
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8759709/ https://www.ncbi.nlm.nih.gov/pubmed/35047261 http://dx.doi.org/10.7759/cureus.20422 |
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author | Kanellopoulos, Asimakis K Kanellopoulos, Emmanouil K Dimitriadis, Zacharias Strimpakos, Nikolaos S Koufogianni, Andriana Kellari, Anthi A Poulis, Ioannis A |
author_facet | Kanellopoulos, Asimakis K Kanellopoulos, Emmanouil K Dimitriadis, Zacharias Strimpakos, Nikolaos S Koufogianni, Andriana Kellari, Anthi A Poulis, Ioannis A |
author_sort | Kanellopoulos, Asimakis K |
collection | PubMed |
description | Introduction Pain drawings (PDs) are an important component of the assessment of a patient with pain. Although analog pain drawings (APDs), such as pen-on-paper drawings, have been extensively used in clinical assessment and clinical research, there is a lack of digital pain drawing (DPD) software that would be able to quantify and analyze the digital pain distribution obtained by the patients. The aim of this work is to describe a method that can quantify the extent and location of pain through novel custom-built software able to analyze data from the digital pain drawings obtained from the patients. Methods The application analysis and software specifications were based on the information gathered from the literature, and the programmers created the custom-built software according to the published needs of the pain scientific community. Results We developed a custom-built software named “Pain Distribution,” which, among others, automatically calculates the number of the pixels the patient has chosen and therefore quantifies the pain extent, provides the frequency distribution from a group of images, and has the option to select the threshold over which the patient is considered with central sensitization (CS). Additionally, it delivers results and statistics for both every image and the frequency distribution, providing mean values, standard deviations, and CS indicators, as well as the ability to export them in *.txt file format for further analysis. Conclusion A novel Pain Distribution application was developed, freely available for use in any setting, clinical, research, or academic. |
format | Online Article Text |
id | pubmed-8759709 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Cureus |
record_format | MEDLINE/PubMed |
spelling | pubmed-87597092022-01-18 Novel Software for Pain Drawing Analysis Kanellopoulos, Asimakis K Kanellopoulos, Emmanouil K Dimitriadis, Zacharias Strimpakos, Nikolaos S Koufogianni, Andriana Kellari, Anthi A Poulis, Ioannis A Cureus Pain Management Introduction Pain drawings (PDs) are an important component of the assessment of a patient with pain. Although analog pain drawings (APDs), such as pen-on-paper drawings, have been extensively used in clinical assessment and clinical research, there is a lack of digital pain drawing (DPD) software that would be able to quantify and analyze the digital pain distribution obtained by the patients. The aim of this work is to describe a method that can quantify the extent and location of pain through novel custom-built software able to analyze data from the digital pain drawings obtained from the patients. Methods The application analysis and software specifications were based on the information gathered from the literature, and the programmers created the custom-built software according to the published needs of the pain scientific community. Results We developed a custom-built software named “Pain Distribution,” which, among others, automatically calculates the number of the pixels the patient has chosen and therefore quantifies the pain extent, provides the frequency distribution from a group of images, and has the option to select the threshold over which the patient is considered with central sensitization (CS). Additionally, it delivers results and statistics for both every image and the frequency distribution, providing mean values, standard deviations, and CS indicators, as well as the ability to export them in *.txt file format for further analysis. Conclusion A novel Pain Distribution application was developed, freely available for use in any setting, clinical, research, or academic. Cureus 2021-12-14 /pmc/articles/PMC8759709/ /pubmed/35047261 http://dx.doi.org/10.7759/cureus.20422 Text en Copyright © 2021, Kanellopoulos et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Pain Management Kanellopoulos, Asimakis K Kanellopoulos, Emmanouil K Dimitriadis, Zacharias Strimpakos, Nikolaos S Koufogianni, Andriana Kellari, Anthi A Poulis, Ioannis A Novel Software for Pain Drawing Analysis |
title | Novel Software for Pain Drawing Analysis |
title_full | Novel Software for Pain Drawing Analysis |
title_fullStr | Novel Software for Pain Drawing Analysis |
title_full_unstemmed | Novel Software for Pain Drawing Analysis |
title_short | Novel Software for Pain Drawing Analysis |
title_sort | novel software for pain drawing analysis |
topic | Pain Management |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8759709/ https://www.ncbi.nlm.nih.gov/pubmed/35047261 http://dx.doi.org/10.7759/cureus.20422 |
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