Multimodal digital phenotyping system for objective mental health assessment and diagnosis
This technology is a hardware and software platform for the digital phenotyping of mental health states that synchronizes neural recordings, wearable sensors, and smartphone data.
Unmet Need: Machine learning software for unbiased, automated mental health assessment
Current methods to assess and diagnose mental health and psychiatric state rely on subjective patient self-assessments, interviews, and physician interpretation, which can be time-consuming and lead to inaccurate diagnoses. While digital and offline platforms show promise in monitoring physiological and behavioral states, accurately phenotyping mental health based on high-dimensional, multimodal data remains challenging. At present, no platforms exist that can analyze multimodal patient data to provide accurate assessments and diagnoses for anxiety, depression, and other related psychiatric disorders.
The Technology: Objective assessment system for mental and psychiatric illness
This technology is a digital phenotyping platform that collects physiological and behavioral data from patients and uses a machine learning algorithm to predict and assess psychiatric state. The hardware and software platform integrates and synchronizes neural recordings, wearable sensors, smartphone data, and environmental context to perform predictive, high-dimensional phenotyping. This approach improves upon current subjective assessments of mental health by leveraging multimodal data to predict anxiety levels, cognitive performance, and human behavior. Ultimately, this technology has the potential to improve treatment outcomes for psychiatric illnesses and mental health disorders.
Applications:
- Monitoring software for mental health and behavior
- Research tool for studying anxiety, depression, and other mental health disorders
- Behavioral monitoring and consumer use tool for targeted advertising
- Biological sensor for healthcare monitoring
- Machine learning software for automated healthcare applications
- Diagnostic tool for mental health applications or other diseases with behavioral and cognitive signatures
Advantages:
- Mental health assessment based on empirical data
- Integrates physiological, behavioral, and environmental context data from multiple sources
- Incorporates neural data collection and analysis into phenotypic models of mental health
- Reduces reliance on subjective assessments of mental health
- Improves behavioral and cognitive risk predictions
- Accessible, digital platform
Lead Inventors:
Joshua Jacobs, Ph.D.
Brett Youngerman, M.D.
Patent Information:
Patent Pending
Related Publications:
Tech Ventures Reference:
IR CU24388
Licensing Contact: Dovina Qu