Panic attacks are an impairing mental health problem that affects 11% of adults every year [1]. Those who suffer from panic attacks often do not seek psychological treatment, citing the inability to receive care during their attacks as a contributing factor. A digital medicine solution which provides an accessible, real-time mobile health (mHealth) biofeedback intervention for panic attacks may address this problem. Critical to this approach are methods for capturing physiological arousal during an attack. Herein, we validate an algorithm for capturing physiological arousal using smartphone video of the fingertip. Results demonstrate that the algorithm is able to estimate heart rates that are highly correlated with ECG-derived values (r > 0.99), effectively reject low-quality data often captured outside of controlled laboratory environments (AUC > 0.90), and resolve the physiological arousal experienced during a panic attack. Moreover, patient reported measures indicate that this measurement modality is feasible during panic attacks, and the act of taking the measurement may stop the attack. These results point toward the need for future development and clinical evaluation of this mHealth intervention for preventing panic attacks.