Cardiac arrhythmias pose a significant global health concern, necessitating early diagnosis for timely intervention. While automatic cardiac arrhythmia detection has been integrated into vital sign monitors, selecting the most suitable device for individual needs remains a complex task involving multiple conflicting criteria. This research addresses this challenge by developing a novel software tool that assists users in selecting the optimal vital sign monitor. The software employs the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) multi-criteria decision-making method to evaluate and rank available devices based on user-defined preferences. Compared to simpler decision-making approaches that may rely on subjective evaluations or single-criterion assessments, the TOPSIS-based tool provides a quantitative and systematic framework for device selection. It achieves this by calculating a closeness coefficient for each device, representing its relative distance to the ideal and negative-ideal solutions across multiple weighted criteria. This allows for a more objective and comprehensive ranking of devices, considering trade-offs between different factors such as clinical performance, cost, and usability. Furthermore, the software has been expanded to incorporate crucial considerations such as compliance with Mexican NOM-035 regulations for psychological risk assessment and carbon footprint analysis, enabling users to make informed decisions that prioritize both health and environmental sustainability. This research contributes to improved patient care and a more sustainable healthcare system by empowering individuals and healthcare providers with a robust and comprehensive tool for selecting the most appropriate vital sign monitoring devices.