AI 기반 노인 돌봄에 관한 국내외 연구 동향 분석 : 2015-2024년 등재학술지 중심으로
A Comparative Analysis of Domestic and International Research Trends on AI-Based Elderly Care: A Review of Indexed Journals from 2015 to 2024
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This study investigates the trends of AI-based elderly care research published between 2015 and 2024 in domestic (KCI) and international (SCI, SSCI) journals. In an era of accelerating population aging, the application of AI technologies—including machine learning, robotics, and IoT—is rapidly expanding in elderly care. This study classifies 128 papers by year, care purpose, AI technology type, and research design, comparing research directions between Korea and overseas. The results reveal that while domestic research focuses on emotional support, safety monitoring, and robot use—primarily emphasizing empirical verification—international studies more actively link AI with healthcare systems, policies, and ethical considerations. Since 2020, studies on emotional and cognitive care, privacy, and system integration have surged. This paper contributes by identifying research gaps and proposing interdisciplinary and policy-integrated directions for future AI-based elderly care services.
Abstract
This study investigates the trends of AI-based elderly care research published between 2015 and 2024 in domestic (KCI) and international (SCI, SSCI) journals. In an era of accelerating population aging, the application of AI technologies—including machine learning, robotics, and IoT—is rapidly expanding in elderly care. This study classifies 128 papers by year, care purpose, AI technology type, and research design, comparing research directions between Korea and overseas. The results reveal that while domestic research focuses on emotional support, safety monitoring, and robot use—primarily emphasizing empirical verification—international studies more actively link AI with healthcare systems, policies, and ethical considerations. Since 2020, studies on emotional and cognitive care, privacy, and system integration have surged. This paper contributes by identifying research gaps and proposing interdisciplinary and policy-integrated directions for future AI-based elderly care services.