Invention Summary:
Schizophrenia is a psychiatric disorder characterized by hallucinations, disorganized thought, delusions, and a decline in both mental and physical functioning. The disorder affects about 1% of the population. Early detection and treatment significantly improves patient response to treatment; and can prevent progression to full relapse by prompting adequate clinical intervention. In addition, currently schizophrenia diagnosis requires a diagnostic battery such as the SCID-II personality assessment which can take up to an hour and must be administered by a mental health professional, psychologist, or psychiatrist.
Researchers at Rutgers have developed a diagnostic software system that can be hosted on a variety of computer platforms (e.g., mobile device) that allows clinicians to use displayed dynamic 3-D computer graphics to assess disease severity in schizophrenia patients. The diagnostic tool’s basic stimulus is a 3-D hollow mask object that is normally perceived as a regular convex mask, an illusion known as the Hollow-Mask Illusion (HMI), a member of the class of Depth Inversion Illusions (DII). Schizophrenia patients are known to be less sensitive to HMI. The Rutgers technology makes it possible to increase and decrease the strength of the DII by manipulating the texture that is mapped onto the hollow mask object. This establishes a sensitive diagnostic procedure that maps the differences in perceptual responses of patients and healthy controls. The analysis of differences can be used as an indicator of disease severity and also has the potential to assess therapeutic efficacy.
Advantages:
- Fast and efficient, can be administered in 15-20 minutes
- Decreased costs, does not require a professional to administer the test and can be administered anywhere
Market Applications:
- Mobile healthcare and diagnostics
- Clinical trials (to assess the efficacy of therapeutic regimes for schizophrenia patients)
Intellectual Property & Development Status:
Patent pending. Available for licensing and/or research collaboration.
