Farhad Abtahi

MoodMon is an AI-powered digital monitoring tool designed for the proactive and personalized care of patients with affective disorders, such as bipolar disorder and recurrent depression. It addresses the challenges of subjective diagnostics and limited access to mental healthcare by continuously and objectively tracking a patient's mental health. The system's AI engine analyzes behavioral data, including voice samples, physical activity, social activity, and sleep patterns, to detect early signs of mood changes. When a potential mood shift is identified, MoodMon sends alerts to the patient, their caregivers, and clinicians, enabling timely and proactive intervention. The system, which includes a voicebot for natural voice sample collection, has demonstrated high sensitivity (89.5%) and specificity (98.83%) in clinical trials. The goal of the project is to commercialize MoodMon, aiming for CE certification as a Class IIa medical device by mid-2025. The expected impact includes improving patients' quality of life, reducing hospitalizations and healthcare costs, and enhancing treatment effectiveness for clinicians. The lead partner for the project is Britenet Med.