Breakthrough Mental Health Diagnostic for Depression and PTSD

Senseye has developed a breakthrough AI-driven platform that uses smartphones to capture video of the eye, which delivers highly accurate and objective data about an individual’s mental health. Through our platform, we help clinicians personalize care with fast and accurate tools to establish a clear baseline and track long-term progress and outcomes. By creating objective mental health diagnostics for the first time, we believe it is possible to empower the Air Force with tools to provide better and quicker mental health care to all service members. Clinicians will be able to use Senseye’s tools longitudinally to understand patient improvement and treatment efficacy. Our unique approach to both deep learning and signal extraction are fully patented, and we continue investigating aggressively in research and development. Our pipeline includes diagnostics for Post-Traumatic Stress Disorder (PTSD), Generalized Anxiety Disorder (GAD), and Major Depressive Disorder (MDD). Diagnosis of MDD and PTSD is complicated due to the lack of objective criteria and a reliance on the self-report of symptoms. All of these mental health conditions exist on a spectrum of severity. Diagnosis of these conditions and detecting the severity is further complicated due to the lack of objective criteria and a reliance on the patient’s self-report of symptoms. Senseye technology uses high-resolution video footage of the eye and heart-rate measurements to quantify previously inaccessible physiological insights for mental health. Senseye’s approach to quantifying brain activity is non-invasive, inexpensive, and highly accessible. Senseye is currently developing diagnostic tools for both PTSD and MDD. The results from the initial pilot study conducted at UCLA for the PTSD diagnostic tool are extremely promising and show clear differences in ocular and heart rate metrics between PTSD patients and healthy controls. For the PTSD pilot study, both control and PTSD patients are instructed to view various visual stimuli (moving dots, various images, and varying brightness on screen) and their heart rate and ocular signals (pupil dilation, constriction, eye movement, blinks etc.) are measured throughout. The Senseye PTSD diagnostic tool has measured significant differences in several ocular metrics as well as heart rate and heart rate variability during the pilot study.  The proposed MDD diagnostic tool will be developed using similar methodology as the PTSD diagnostic tool. A similar mobile application will be developed, and the same computer vision and analytical processes will be used to extract features from the video and heart rate data. The MDD diagnostic tool will use different stimuli and tasks that are specifically targeted to detect neurophysiological differences relevant to MDD.