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

• URL: http://arxiv.org/abs/2504.16573v1
• Date: Wed, 23 Apr 2025 09:49:05 GMT
• Title: PsyCounAssist: A Full-Cycle AI-Powered Psychological Counseling Assistant System
• Authors: Xianghe Liu, Jiaqi Xu, Tao Sun,
• Abstract summary: PsyCounAssist is a comprehensive AI-powered counseling system specifically designed to augment psychological counseling practices.<n>It integrates multimodal emotion recognition, automated structured session reporting, and personalized AI-generated follow-up support.<n> Deployed on Android-based tablet devices, the system demonstrates practical applicability and flexibility in real-world counseling scenarios.
• Score: 6.868956036918275
• License: http://creativecommons.org/licenses/by/4.0/
• 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.

Related papers

• AutoPsyC: Automatic Recognition of Psychodynamic Conflicts from Semi-structured Interviews with Large Language Models [13.619243319107596]
  Psychodynamic conflicts are persistent, often unconscious themes that shape a person's behaviour and experiences. Existing automated solutions for psychiatric diagnosis tend to focus on the recognition of broad disorder categories. We propose AutoPsyC, the first method for recognising the presence and significance of psychodynamic conflicts.
  arXiv  Detail & Related papers  (2025-03-27T18:41:35Z)
• AutoCBT: An Autonomous Multi-agent Framework for Cognitive Behavioral Therapy in Psychological Counseling [57.054489290192535]
  Traditional in-person psychological counseling remains primarily niche, often chosen by individuals with psychological issues.<n>Online automated counseling offers a potential solution for those hesitant to seek help due to feelings of shame.
  arXiv  Detail & Related papers  (2025-01-16T09:57:12Z)
• Enhancing AI-Driven Psychological Consultation: Layered Prompts with Large Language Models [44.99833362998488]
  We explore the use of large language models (LLMs) like GPT-4 to augment psychological consultation services. Our approach introduces a novel layered prompting system that dynamically adapts to user input. We also develop empathy-driven and scenario-based prompts to enhance the LLM's emotional intelligence.
  arXiv  Detail & Related papers  (2024-08-29T05:47:14Z)
• CPsyCoun: A Report-based Multi-turn Dialogue Reconstruction and Evaluation Framework for Chinese Psychological Counseling [27.193022503592342]
  We propose CPsyCoun, a report-based multi-turn dialogue reconstruction and evaluation framework for Chinese psychological counseling. To fully exploit psychological counseling reports, a two-phase approach is devised to construct high-quality dialogues. A comprehensive evaluation benchmark is developed for the effective automatic evaluation of multi-turn psychological consultations.
  arXiv  Detail & Related papers  (2024-05-26T05:18:00Z)
• PsychoGAT: A Novel Psychological Measurement Paradigm through Interactive Fiction Games with LLM Agents [68.50571379012621]
  Psychological measurement is essential for mental health, self-understanding, and personal development. PsychoGAT (Psychological Game AgenTs) achieves statistically significant excellence in psychometric metrics such as reliability, convergent validity, and discriminant validity.
  arXiv  Detail & Related papers  (2024-02-19T18:00:30Z)
• K-ESConv: Knowledge Injection for Emotional Support Dialogue Systems via Prompt Learning [83.19215082550163]
  We propose K-ESConv, a novel prompt learning based knowledge injection method for emotional support dialogue system. We evaluate our model on an emotional support dataset ESConv, where the model retrieves and incorporates knowledge from external professional emotional Q&A forum.
  arXiv  Detail & Related papers  (2023-12-16T08:10:10Z)
• Psy-LLM: Scaling up Global Mental Health Psychological Services with AI-based Large Language Models [3.650517404744655]
  Psy-LLM framework is an AI-based tool leveraging Large Language Models for question-answering in psychological consultation settings. Our framework combines pre-trained LLMs with real-world professional Q&A from psychologists and extensively crawled psychological articles. It serves as a front-end tool for healthcare professionals, allowing them to provide immediate responses and mindfulness activities to alleviate patient stress.
  arXiv  Detail & Related papers  (2023-07-22T06:21:41Z)
• Enabling AI and Robotic Coaches for Physical Rehabilitation Therapy: Iterative Design and Evaluation with Therapists and Post-Stroke Survivors [66.07833535962762]
  Artificial intelligence (AI) and robotic coaches promise the improved engagement of patients on rehabilitation exercises through social interaction. Previous work explored the potential of automatically monitoring exercises for AI and robotic coaches, but deployment remains a challenge. We present our efforts on eliciting the detailed design specifications on how AI and robotic coaches could interact with and guide patient's exercises.
  arXiv  Detail & Related papers  (2021-06-15T22:06:39Z)
• Pose-based Body Language Recognition for Emotion and Psychiatric Symptom Interpretation [75.3147962600095]
  We propose an automated framework for body language based emotion recognition starting from regular RGB videos. In collaboration with psychologists, we extend the framework for psychiatric symptom prediction. Because a specific application domain of the proposed framework may only supply a limited amount of data, the framework is designed to work on a small training set.
  arXiv  Detail & Related papers  (2020-10-30T18:45:16Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.