Comprehensive Literature Review on Large Language Models and Smart Monitoring Devices for Stress Management
Year: 2025
Type: conference-paper
Abstract: This review evaluates the complementary roles of Large Language Models (LLMs) and smart monitoring devices in stress management, aiming to identify synergies for improved mental health solutions. It explores the evolution of LLM architectures (Encoder-Decoder, Encoder-Only, Decoder-Only, and Mixture of Experts), emphasizing their strengths in personalized interventions. Simultaneously, it examines physiological monitoring technologies, ranging from traditional biometric sensors to AI-enhanced platforms, focusing on bioelectrical signals (ECG, EEG, EMG, GSR) and optical measurements (PPG, BVP, SpO2). By detailing the principles, devices, and stress monitoring applications of these modalities, the review uncovers opportunities for integration. The findings provide a foundation for future research into AI-driven, multimodal stress management systems, promoting more effective and accessible mental health support.
Source: Procedia Computer Science
Authors: Othman Wahab, Mehdi Adda
Institution: Université du Québec à Rimouski
Language: English
Topic: Emotion and Mood Recognition
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4409814470