Project to predict schizophrenia and Depression from activity data
It has been well-established that behavioral disorders such as depression and schizophrenia are hard to diagnose. Classifying the type of the disorder is a challenging task because of the diversity of the symptoms. Furthermore, estimation of the severity level of such disorders is another challenging factor in the diagnosis process. Current clinical diagnostic procedures tend to be mostly dependent on the self-reporting of patients or the limited observational evaluations of clinicians. Hence, there is a need for objective analytical methods that leverage the current informatics advancements in studying behavior disorders.
77 particpants [23 diagnosed depression; 22 diagnosed schizophrenic and 32 Control patients] wore devices ro record activity levels. Per minute readings over an 2 week period [approx] was taken.
It is hoped that the results of this project will assist in the development of automated systems supporting the existing subjective diagnostic practice within mental health.