An AI-Supported Communication and Cognitive Monitoring System for Older Adults
A MAARS Platform Project
Combining large language models, natural language processing, and voice interaction to create a companion system that monitors cognitive health and reduces loneliness in adults aged 65+.
Cognitive decline and social isolation are among the most pressing health concerns for older adults worldwide. Traditional screening methods are often infrequent, clinic-dependent, and unable to capture subtle longitudinal changes in cognitive and emotional well-being.
Project iShe develops an AI-powered voice companion that engages older adults in natural daily conversations. Through dialogue, the system performs continuous cognitive screening, monitors emotional states via NLP-based sentiment analysis, and reduces loneliness through meaningful social engagement.
The pilot study (TÜBİTAK 1002-A, Project No: 324S300) established the foundational framework for the iShe system. Part I demonstrated the feasibility and potential of AI-powered voice interaction with older adults and validated the core technological approach.
Part I — System Design and Pilot Validation
The Scientific and Technological Research Council of Türkiye (TÜBİTAK)
Large Language Model-powered conversational AI that engages older adults in natural, empathetic daily dialogues through voice interaction on iOS and Android.
Automated cognitive assessment embedded within natural conversation, enabling continuous longitudinal monitoring without clinical visit dependency.
Real-time emotion and mood detection through natural language processing, tracking psychological well-being and detecting early signs of depression or distress.
A multidisciplinary team combining expertise in neurosurgery, anesthesiology, geriatrics, computer engineering, and data science.
Department of Neurosurgery
İstanbul Aydın University
Department of Geriatrics
Ege University
Department of Anesthesiology and Reanimation
İstanbul Aydın University
Department of Computer Engineering
Ege University
Department of Computing Science
University of Alberta, Canada
Faculty of Medicine, İstanbul
Faculty of Medicine & Engineering, İzmir
Computing Science, Edmonton, Canada
Building on the success of Part I, we are preparing a large-scale randomized controlled trial to evaluate the clinical effectiveness of the iShe system. Part II will expand the scope with a multicenter RCT design, validated outcome measures, and a broader participant cohort.
For inquiries about the project, collaboration opportunities, or participation, please reach out to us.
İstanbul Aydın University, Faculty of Medicine
Department of Neurosurgery & Anesthesiology, İstanbul, Türkiye
Ege University, Faculty of Medicine
Department of Geriatrics, İzmir, Türkiye
University of Alberta
Department of Computing Science, Edmonton, Canada