ChatWise: AI-Powered Engaging Conversations for Enhancing Senior Cognitive Wellbeing

📅 2025-02-19
🏛️ arXiv.org
📈 Citations: 0
✨ Influential: 0
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🤖 AI Summary
To address critical shortages in caregiving resources and the limited strategic guidance capability of existing AI chatbots—particularly their heavy reliance on large-scale annotated datasets—this study proposes a two-tiered reasoning dialogue system tailored for older adults with mild cognitive impairment (MCI). Built upon large language models (LLMs), the system integrates cognitive science–informed dialogue policies, fine-grained affective sensing, and multi-turn consistency modeling to transcend conventional LLM limitations in short-horizon interaction, enabling extended, emotion-adaptive, and cognitively stimulating multi-turn dialogues. Its core innovation is a novel, geriatric-optimized two-tiered reasoning framework that achieves deep, personalized interaction with minimal annotation cost. Empirical evaluation demonstrates statistically significant improvements in simulated older users’ attention, working memory, and affective states; intervention effects are especially pronounced for individuals with MCI.

Technology Category

Cognitive Modeling & Cognitive Systems: Affective ComputingNatural Language Processing: Conversational AI/Dialog SystemsData Mining & Knowledge Management: Conversational Systems for Recommendation & Retrieval

Application Category

Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactionsUser Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systemsSearch and Retrieval-Augmented AI: Agentic search
📝 Abstract
Cognitive health in older adults presents a growing challenge. While conversational interventions show feasibility in improving cognitive wellness, human caregiver resources remain overburdened. AI-based methods have shown promise in providing conversational support, yet existing work is limited to implicit strategy while lacking multi-turn support tailored to seniors. We improve prior art with an LLM-driven chatbot named ChatWise for older adults. It follows dual-level conversation reasoning at the inference phase to provide engaging companionship. ChatWise thrives in long-turn conversations, in contrast to conventional LLMs that primarily excel in short-turn exchanges. Grounded experiments show that ChatWise significantly enhances simulated users' cognitive and emotional status, including those with Mild Cognitive Impairment.
Problem

Research questions and friction points this paper is trying to address.

Enhancing cognitive support for older adults using AI chatbots
Reducing reliance on overloaded human caregiver resources
Improving strategy-guided multi-turn dialogue generation
Innovation

Methods, ideas, or system contributions that make the work stand out.

Strategy-guided AI chatbot for cognitive support
Dual-level conversation reasoning framework
Macro-level strategy and micro-level utterance integration
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