This work is developed within the framework of a national research project focused on designing and developing a system for monitoring depression using a platform based on wearable devices. In a preceding project, various physiological markers for depression monitoring were identified through the combination of physiological signals, capable of assessing the autonomic nervous system response to cognitive stress/stimuli and distinguishing between individuals with depression and control subjects. To ensure the applicability and utility of the findings in clinical settings, endeavors have been directed towards extracting these markers not from medical or research-grade equipment, but from low-cost and easily accessible devices, which can be utilized by a wide segment of the population, with minimal interference in daily life. We present the perspective from the design domain regarding the ideation and design process of the user interaction. Specifically, a mobile application has been designed and tested to be utilized by patients undergoing treatment. Through this application, the patient can autonomously and remotely register his physiological state, while the system generates valuable insights for the specialist, who could detect critical cases, adjust treatments, or prioritize consultations. As with any multi-user health-focused application, achieving this goal has been a complex endeavor. We have faced various design challenges, including user complexity, feedback integration, validation of results, and optimizing interface usability, some of them reflected in the scientific literature. Furthermore, the project has presented additional interesting challenges, such as digitalizing standardized neuropsychological tests which traditionally have been conducted in analog formats.