Emotion Forecasting: A Transformer-Based Approach.

ABSTRACT:

Background

Monitoring the emotional states of patients with psychiatric problems has always been challenging due to the noncontinuous nature of clinical assessments, the effect of the health care environment, and the inherent subjectivity of evaluation instruments. However, mental states in psychiatric disorders exhibit substantial variability over time, making real-time monitoring crucial for preventing risky situations and ensuring appropriate treatment.

Objective

This study aimed to leverage new technologies and deep learning techniques to enable more objective, real-time monitoring of patients. This was achieved by passively monitoring variables such as step count, patient location, and sleep patterns using mobile devices. We aimed to predict patient self-reports and det

SUBMITTER: Paz-Arbaizar L 

PROVIDER: S-EPMC11962324 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature