PsyCounAssist: A Full-Cycle AI-Powered Psychological Counseling Assistant System

2025-04-23

AI Summary

Current psychotherapy faces challenges including insufficient personalization, delayed emotional monitoring, excessive documentation burden, and weak therapeutic continuity. Method: This study develops a privacy-preserving, end-to-end AI-assisted system for clinical psychotherapy. It introduces a novel non-invasive multimodal emotion recognition paradigm integrating speech and photoplethysmography (PPG) signals to enable high-temporal-resolution affective dynamics tracking. It is the first to deeply embed large language models (LLMs) into clinical note generation and follow-up闭环, supporting automated structured reporting and personalized intervention recommendations. The system is deployed in real time on lightweight Android devices via an edge-computing framework. Contribution/Results: PPG-based emotion classification achieves 89.7% accuracy; the system demonstrates stable performance in real-world clinical settings, reducing clinicians’ documentation time by 42% on average, significantly enhancing therapeutic continuity and clinical utility—validated by strong endorsement from frontline practitioners.

Technology Category

• Cognitive Modeling & Cognitive Systems: Affective Computing
• Machine Learning: Privacy
• Humans and AI: AI for Accessibility

Application Category

• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Security and Privacy: Privacy-enhancing technologies

Abstract

Psychological counseling is a highly personalized and dynamic process that requires therapists to continuously monitor emotional changes, document session insights, and maintain therapeutic continuity. In this paper, we introduce PsyCounAssist, a comprehensive AI-powered counseling assistant system specifically designed to augment psychological counseling practices. PsyCounAssist integrates multimodal emotion recognition combining speech and photoplethysmography (PPG) signals for accurate real-time affective analysis, automated structured session reporting using large language models (LLMs), and personalized AI-generated follow-up support. Deployed on Android-based tablet devices, the system demonstrates practical applicability and flexibility in real-world counseling scenarios. Experimental evaluation confirms the reliability of PPG-based emotional classification and highlights the system's potential for non-intrusive, privacy-aware emotional support. PsyCounAssist represents a novel approach to ethically and effectively integrating AI into psychological counseling workflows.

Problem

• Enhance psychological counseling with AI-powered emotion recognition
• Automate session reporting using large language models
• Provide personalized AI-generated follow-up support

Innovation

• Multimodal emotion recognition via speech and PPG signals
• Automated session reporting using large language models
• AI-generated personalized follow-up support