The overall theme of this thesis is the study of sensory pain assessment and describes how digital pain mapping using standardized iconography can be used to help portray and understand the sensory pain experience. The research presented in this thesis is focused on the design, development, and use of a web-based sensory pain assessment tool for individuals with chronic pain called the Pain-QuILT. “QuILT” is an acronym describing the different parameters that are captured by the tool: pain quality, intensity, and location in a digital format that can be tracked over time. The central hypothesis guiding this work is that users of pain assessment tools will tend to favour a digital icon-based sensory pain mapping tool (‘PainQuILT’) over currently available sensory pain assessment tools. “Pain assessment tool” has been operationally defined as a standardized method for capturing information about an individual’s sensory pain experience. In this context, “users” include both individuals experiencing chronic pain and healthcare providers who seek to assess and understand pain. Research to date has focused on phased evaluation of the Pain-QuILT in the context of clinical sensory pain assessment for two distinct user groups: adolescents (aged 12 to 18 years) and adults (aged 19 years and older) with chronic pain. Each stage of research has generated and been informed by user feedback, leading to iterative improvements in tool functionality. Thus, as a whole, this body of work represents an evolving effort to improve the clinical assessment of sensory pain using the approach of icon-based pain mapping in a digital and visual format. Through the collective research presented in this thesis, we have affirmed that digital pain mapping using iconography is a viable solution to the clinical challenge of sensory pain assessment in adolescents and adults with chronic pain. / Dissertation / Doctor of Philosophy (PhD)

[ES] El acceso a una atención sanitaria de alta calidad es un marcador importante del desarrollo de las sociedades humanas. Los aportes tecnológicos a la medicina han mostrado un potencial relevante para descubrir procedimientos efectivos a nivel preventivo, diagnóstico y terapéutico. En particular, los métodos computacionales permiten el procesamiento eficaz de datos médicos y, por tanto, pueden modelar sistemas biológicos complejos. Esto ha influido en el desarrollo de la Medicina Personalizada (MP) durante las últimas décadas, donde la obtención de conocimiento específico de cada caso permite realizar intervenciones a medida, todo ello a un coste de recursos accesible. La simulación de remodelación ósea es un campo prometedor en el contexto de la MP. Predecir un proceso de adaptación ósea en un caso concreto puede dar lugar a numerosas aplicaciones en el campo de las enfermedades óseas, tanto a nivel clínico como experimental. Mediante la combinación del Método de Elementos Finitos (FEM) y los algoritmos de remodelación ósea, es posible obtener modelos numéricos de un hueso específico a partir de datos médicos (por ejemplo, una tomografía computarizada). Todo ello puede dar lugar a una revolución en la medicina personalizada. / [CA] L'accés a una atenció sanitària d'alta qualitat és un marcador important del desenvolupament de les societats humanes. Les aportacions tecnològiques a la medicina han mostrat un potencial rellevant per a descobrir procediments efectius a nivell preventiu, diagnòstic i terapèutic. En particular, els mètodes computacionals permeten el processament eficaç de dades mèdiques i, per tant, poden modelar sistemes biològics complexos. Això ha influït en el desenvolupament de la Medicina Personalitzada (MP) durant les últimes dècades, on l'obtenció de coneixement específic de cada cas permet realitzar intervencions a mesura, tot això a un cost de recursos accessible. La simulació de remodelació òssia és un camp prometedor en el context de la MP. Predir un procés d'adaptació òssia en un cas concret pot donar lloc a nombroses aplicacions en el camp de les malalties òssies, tant a nivell clínic com experimental. Mitjançant la combinació del Mètode d'Elements Finits (*FEM) i els algorismes de remodelació òssia, és possible obtindre models numèrics d'un os específic a partir de dades mèdiques (per exemple, una tomografia computada). Tot això pot donar lloc a una revolució en la medicina personalitzada. / [EN] Access to high-quality healthcare is an important marker of the development of human societies. Technological contributions to medicine have shown relevant potential to discover effective procedures at a preventive, diagnostic and therapeutic level. In particular, computational methods enable efficient processing of medical data and can therefore model complex biological systems. This has influenced the development of Personalized Medicine (PM) over recent decades, where obtaining specific knowledge of each case allows for tailored interventions, all at an affordable resource cost. Simulation of bone remodeling is a promising field in the context of PM. Predicting a bone adaptation process in a specific case can lead to numerous applications in the field of bone diseases, both clinically and experimentally. By combining the Finite Element Method (FEM) and bone remodeling algorithms, it is possible to obtain numerical models of a specific bone from medical data (for example, a CT scan). All of this can lead to a revolution in personalized medicine. / Thanks to the Valencian funding programme FDGENT/2018, for providing economic resources to develop this long-term work. / Gutiérrez Gil, J. (2023). Personalization of Bone Remodelling Simulation Models for Clinical Applications [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/202059