A Mobile Application Using a Low-Cost EEG Device for Real-Time Stress Detection to Support Mental Well-Being

Nowadays, increasing workload, fast-paced lifestyles negatively affectindividuals' mental well-being by increasing stress. However, effectivetechnological solutions for stress management are often inaccessible due to highcosts and processing power requirements. This study presents a low-cost mobilerecommendation application capable of stress detection in real time usingelectroencephalography (EEG) data from a single-channel NeuroSky MindWaveMobile 2 device. The application analyzes the data with low processing power toassess stress levels and provides personalized relaxation suggestions such asmusic, breathing exercises, or meditation. Furthermore, a user study with 28participants revealed that EEG based measurements and self-reported scores ofState-Trait Anxiety Inventory (STAI) reflected users' stress levels in a similarway. Additionally, user experience evaluation of the application revealed highperceived usability and a generally positive interaction experience based onUMUX-Lite score of 86.31 and AttrakDiff score of 1.89. These findings suggestthat the application can support mental well-being through accessible, real-timestress detection and interactive feedback mechanisms. In addition, the resultshighlight the potential of EEG-based mobile technologies in promotingemotional wellness and offer a promising example of user-centered design forquality-of-life enhancement.