Artificial Intelligence for Mental Telehealth Applications: Data Modalities, Systems, and Evaluation Metrics
Publication Date
1-1-2026
Document Type
Conference Proceeding
Publication Title
Conference Proceedings IEEE SOUTHEASTCON
DOI
10.1109/SoutheastCon63549.2026.11476390
Abstract
Telehealth services have increased for mental healthcare since 2020. This study surveys the state of mental telehealth, considering technological, clinical, and ethical factors. Performing literature review helps uncover the state of mental telehealth, identifies strengths and limitations, and analyzes the latest approaches and technologies. This overview of current state-of-the-art technologies includes reviewing mental health applications based on companies' products and existing research. By finding key gaps in mental health practices in telehealth, we introduce a framework to improve its overall experience. This framework is tested against models from Kintsugi Health and Sonde Health. The study also aims to introduce an artificial intelligence-based system that will better assist with telehealth sessions between a clinician and a patient.
Keywords
artificial intelligence, explainable artificial intelligence, feed-forward neural networks, mental health, speech processing, telehealth, variational autoencoders
Department
Computer Engineering
Recommended Citation
Sonal Prasad and Bernardo Flores. "Artificial Intelligence for Mental Telehealth Applications: Data Modalities, Systems, and Evaluation Metrics" Conference Proceedings IEEE SOUTHEASTCON (2026). https://doi.org/10.1109/SoutheastCon63549.2026.11476390
