Using Smartphone-recorded Facial and Verbal Features to Predict Clinical Functioning in Individuals with Neuro-psychiatric Disorders
In this poster you will learn:
- Measuring severity of symptoms in individuals with neuropsychiatric disorders often requires clinician-administered assessments, which can be laborious, costly, and subjective to rater variability
- Facial, voice, and motor have been shown to differentiate individuals with and without diverse neuropsychiatric disorders including schizophrenia;
- With advancements in machine learning it is increasingly feasible to accurately capture and quantify such clinical characteristics.
- Here, we use videos collected through a smartphone-based platform to extract facial, verbal, and movement features in healthy controls and individuals with schizophrenia and determine their ability to differentiate clinical from non-clinical populations