Creating a Pain Assessment Tool to Track the Development of Pain
Nieminen, Kiia (2025)
2025
Bioteknologian ja biolääketieteen tekniikan maisteriohjelma - Master's Programme in Biotechnology and Biomedical Engineering
Lääketieteen ja terveysteknologian tiedekunta - Faculty of Medicine and Health Technology
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Hyväksymispäivämäärä
2025-07-29
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tuni-202507287855
https://urn.fi/URN:NBN:fi:tuni-202507287855
Tiivistelmä
Pain is subjective experience and therefore difficult to quantify. Attempts to form more objective view on pain data have been done by combining the collection of multiple types of pain-related data into pain assessment tools. Collecting more data enables wider range of analysis, which is essential for a better understanding of pain.
A need for an easy-to-use solution for long-term self-reported pain data collection and visualisation features was recognized, as existing solutions lacked flexibility and sufficient customisation. Comprehensive regulatory analysis and requirement gathering were concluded to evaluate the operating environment of a mobile application utilising health data. Approaches to find best practises to collect and store pain data, define the needed features, and design the application were studied and implemented within the application.
A working beta version of a pain assessment mobile application was developed on Flutter and additionally, utilising Backend-as-a-Service platform Firebase. The application features an interactive human body layout allowing research participants to log pain location, pain intensity, and pain type within a predefined collection intervals. The data is encrypted symmetrically with AES and stored in the local device, and can be retrieved by the research group during study sessions. The application supports visualisation of the collected data through heat maps. Based on a literature review, both segmented and gradient heat maps were implemented to offer more comprehensive understanding of pain. Additionally, two algorithms based on frequency and intensity of pain are available for defining the data visualisation even more.
By combining this pain assessment tool's features with interventions, it has the potential to improve current knowledge on pain management and pain development. Initial testing was concluded during the development of the application and first pilot studies can be carried out with this application to recognise possible issues with features, functionality, or feasibility.
A need for an easy-to-use solution for long-term self-reported pain data collection and visualisation features was recognized, as existing solutions lacked flexibility and sufficient customisation. Comprehensive regulatory analysis and requirement gathering were concluded to evaluate the operating environment of a mobile application utilising health data. Approaches to find best practises to collect and store pain data, define the needed features, and design the application were studied and implemented within the application.
A working beta version of a pain assessment mobile application was developed on Flutter and additionally, utilising Backend-as-a-Service platform Firebase. The application features an interactive human body layout allowing research participants to log pain location, pain intensity, and pain type within a predefined collection intervals. The data is encrypted symmetrically with AES and stored in the local device, and can be retrieved by the research group during study sessions. The application supports visualisation of the collected data through heat maps. Based on a literature review, both segmented and gradient heat maps were implemented to offer more comprehensive understanding of pain. Additionally, two algorithms based on frequency and intensity of pain are available for defining the data visualisation even more.
By combining this pain assessment tool's features with interventions, it has the potential to improve current knowledge on pain management and pain development. Initial testing was concluded during the development of the application and first pilot studies can be carried out with this application to recognise possible issues with features, functionality, or feasibility.