Prompt and accurate detection of stress is essential to the monitoring and management of mental health and human performance. Considering that current methods such as questionnaires are very subjective, we propose a highly sensitive, selective, miniaturized mHealth device based on laser-enabled flexible graphene sensor to non-invasively monitor the level of stress hormones (e.g., cortisol). We report a strong correlation between sweat and circulating cortisol and demonstrate the prompt determination of sweat cortisol variation in response to acute stress stimuli. Moreover, we demonstrate, for the first time, the diurnal cycle and stress-response profile of sweat cortisol, revealing the potential of dynamic stress monitoring enabled by this mHealth sensing system. We believe that this platform could contribute to fast, reliable, and decentralized healthcare vigilance at the metabolic level, thus providing an accurate snapshot of our physical, mental, and behavioral changes
