面向老年人的个性化认知增强：一个对老年人友好的闭环人机界面框架

IF 12.4 1区医学 Q1 CELL BIOLOGY

Ageing Research Reviews Pub Date : 2025-08-22 DOI:10.1016/j.arr.2025.102877

Sa Zhou , Yang Liu , Adam Turnbull , Cristiano Tapparello , Ehsan Adeli , F. Vankee Lin

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引用次数: 0

摘要

新兴的数字传递非药物干预（dnpi）为增强老年人的认知功能提供了可扩展、低风险的解决方案，但由于缺乏个性化和精确的作用机制，其有效性仍然不一致。通用的、基于人群的设计往往不能预测个人收益，强调需要更有针对性的方法。为了解决这个问题，我们提出了一个闭环人机界面（HMI）框架，通过优化神经认知资源的参与来增强认知，从而个性化dnpi。我们的框架解决了三个主要挑战：(1)认知解码的全面有效的神经行为表征，(2)针对特定领域的认知过程定制干预措施，以及(3)确保长期依从性的可用性，有效性和可靠性的老龄化友好设计。我们通过概述三个关键组件（传感器、控制器和外部执行器）的操作细节，通过实时自适应干预来监测、分析和调节神经行为活动，为闭环hmi的发展提供评论和观点。围绕老年人的神经行为特征，我们建议将闭环hmi推进到：(1)部署多模态传感器网络，捕获来自中枢和周围神经系统的活动；(2)人工智能（AI）驱动的认知解码和调制，集成多模态易于获取的神经行为信号，并预测跨模态难以获取的信号；(3)通过内部和/或外部调节靶向神经行为过程。我们设想所提出的闭环人机交互框架可以为老年人的认知增强提供个性化的dNPI，增强其有效性和可扩展性，促进老年人的大脑弹性和健康长寿。

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Personalized cognitive enhancement for older adults: An aging-friendly closed-loop human-machine interface framework

Emerging digitally delivered non-pharmacological interventions (dNPIs) offer scalable, low-risk solutions for enhancing cognitive function in older adults, yet their effectiveness remains inconsistent due to a lack of personalization and precise mechanisms of action. Generic, population-based designs often fail to predict individual gains, underscoring the need for more tailored approaches. To address this, we propose a closed-loop human-machine interface (HMI) framework for personalizing dNPIs by optimizing the engagement of neurocognitive resources for cognitive enhancement. Our framework tackles three major challenges: (1) comprehensive and effective neurobehavioral representations for cognitive decoding, (2) tailoring interventions for domain-specific cognitive processes, and (3) ensuring aging-friendly design on usability, validity, and reliability for long-term adherence. We provide reviews and perspectives to guide the development of closed-loop HMIs by outlining the operational details of three key components—sensor, controller, and external actuator—that monitor, analyze, and modulate neurobehavioral activities through real-time adaptive interventions. Centering on neurobehavioral characteristics of older adults, we propose to advance closed-loop HMIs toward (1) deploying multimodal sensor network that captures activities from both central and peripheral nervous systems, (2) artificial intelligence (AI)-powered cognitive decoding and modulation that integrates multi-modal easy-to-acquire neurobehavioral signals and predicts the cross-modal harder-to-acquire signals, and (3) targeting neurobehavioral processes via internal and/or external regulation. We envision that the proposed closed-loop HMI framework could provide personalized dNPI with enhanced effectiveness and scalability for cognitive enhancement in older adults, promoting brain resilience and healthy longevity in the aging population.

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来源期刊

Ageing Research Reviews 医学-老年医学

CiteScore

19.80

自引率

2.30%

发文量

216

审稿时长

55 days

期刊介绍： With the rise in average human life expectancy, the impact of ageing and age-related diseases on our society has become increasingly significant. Ageing research is now a focal point for numerous laboratories, encompassing leaders in genetics, molecular and cellular biology, biochemistry, and behavior. Ageing Research Reviews (ARR) serves as a cornerstone in this field, addressing emerging trends. ARR aims to fill a substantial gap by providing critical reviews and viewpoints on evolving discoveries concerning the mechanisms of ageing and age-related diseases. The rapid progress in understanding the mechanisms controlling cellular proliferation, differentiation, and survival is unveiling new insights into the regulation of ageing. From telomerase to stem cells, and from energy to oxyradical metabolism, we are witnessing an exciting era in the multidisciplinary field of ageing research. The journal explores the cellular and molecular foundations of interventions that extend lifespan, such as caloric restriction. It identifies the underpinnings of manipulations that extend lifespan, shedding light on novel approaches for preventing age-related diseases. ARR publishes articles on focused topics selected from the expansive field of ageing research, with a particular emphasis on the cellular and molecular mechanisms of the aging process. This includes age-related diseases like cancer, cardiovascular disease, diabetes, and neurodegenerative disorders. The journal also covers applications of basic ageing research to lifespan extension and disease prevention, offering a comprehensive platform for advancing our understanding of this critical field.