Sporala red del conocimiento
Universidad Antonio Nariño

Ingeniería Biomédica · 2026

Simulación de un sistema de monitorización de presión y temperatura para la prevención de úlceras por presión en pacientes hospitalizados: un análisis mediante Comsol Multiphysics.

Alegría Ordóñez, Juan ManuelAsesor: Gutierrez Gutierrez, Edgar Willinton

Pressure ulcers (PU) are a critical problem in hospital care—especially among immobilized patients—with significant risk in Colombia and high associated costs. Despite advances in monitoring technologies, there are persistent limitations in integrating systems that simultaneously account for the multiphysics interaction among pressure, temperature, and tissue response. This work proposes the development and validation, via simulation in COMSOL Multiphysics®, of an integrated monitoring system that issues preventive risk alarms for PU while incorporating interindividual variability and real clinical conditions. The research methodology employs biomechanical and thermal models to optimize sensor design and placement (FSR and MLX90614), enabling more timely clinical interventions. Parameters such as ambient temperature, immobility time, and material density were considered, and pressure and temperature variables were measured in the affected regions (sacrum and heels). This degree project falls within the preventive bioinstrumentation track, contributing innovation in computational simulation applied to health care. The following key results were obtained: the simulated system showed reliable performance across both parameters analyzed. For pressure, sensitivity was 94.0%, specificity 92.0%, precision 92.2%, accuracy 93.0%, root-mean-square error 0.0118 mmHg, and resolution 0.01 mmHg. For temperature, metrics reached a sensitivity of 88.0%, specificity 96.0%, precision 95.65%, and accuracy 92.0%, with an overall thermal precision of ±0.151 °C and a resolution of 0.02 °C. The total system response time was approximately 2.5 seconds. These values confirm the feasibility of the device for early PU detection and show that integrating pressure and temperature signals, together with the proposed algorithmic processing, delivers a high level of performance.

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