智能家居健康监测系统适老化设计的老龄人因研究综述
A Review of Gerontological Ergonomic Research on the Adaptive Design of Smart Home Health Monitoring Systems
摘要: 人口老龄化深度推进下,智能家居健康监测系统成为老年居家健康管理的重要支撑,但现有产品多重技术、轻人因,忽视老年人生理与认知老化特征,易用性与适配性欠佳,难以满足实际养老需求。人因设计是优化老年用户产品体验的核心,神经人因学则为从脑认知层面破解适老化设计难题提供了新方向。研究系统梳理智能家居健康监测系统适老化人因设计在硬件适配、软件交互、功能服务方面的研究现状,结合典型产品案例剖析“表面适老”问题,并引入Persona与能力谱系框架讨论老年群体异质性及差异化设计策略。在此基础上,文章从神经人因学视角提出认知负荷量化、主客观融合评价、多模态自适应交互、多方协同服务与分层设计等研究展望,并进一步讨论其在真实场景中面临的技术、成本、伦理和隐私挑战及初步应对路径,以期为贴合老年群体需求的智慧养老产品设计提供理论参考,助力积极老龄化建设。
Abstract: As population aging intensifies, smart home health monitoring systems have become a crucial support for elderly home health management. However, existing products often prioritize multiple technologies over human-centered design, neglecting the physiological and cognitive aging characteristics of seniors, resulting in poor usability and adaptability that fail to meet practical elderly care needs. Human-centered design is central to optimizing product experiences for senior users, while neurohuman factors provide a new approach to addressing age-friendly design challenges at the cognitive level. This study systematically reviews current research on age-friendly human-centered design in smart home health monitoring systems across hardware compatibility, software interaction, and functional services. Through case analyses of representative products, it examines issues of “superficial age-friendliness” and employs the Persona and capability hierarchy frameworks to discuss population heterogeneity and tailored design strategies. From a neurohuman factors perspective, the paper proposes future research directions—including cognitive load quantification, integrated subjective-objective evaluation, multimodal adaptive interaction, collaborative multi-party services, and hierarchical design—while addressing technical, cost, ethical, and privacy challenges in real-world applications. These insights aim to provide theoretical foundations for developing intelligent elderly care products that better meet seniors’ needs and advance active aging initiatives.
文章引用:张潇颖. 智能家居健康监测系统适老化设计的老龄人因研究综述[J]. 老龄化研究, 2026, 13(7): 225-231. https://doi.org/10.12677/ar.2026.137448

参考文献

[1] Population Division of Department of Economic and Social Affairs of United Nations (2024) World Population Prospects 2024. United Nations.
[2] 窦金花, 覃京燕. 智慧健康养老产品适老化设计与老年用户研究方法[J]. 包装工程, 2021, 42(6): 62-68.
[3] Ghorayeb, J., Dieppe, P., Abbott, S., et al. (2021) Older Adults’ Perspectives on Smart Home Technology: A Systematic Review. Journal of Housing for the Elderly, 35, 153-181.
[4] Lindenberger, U., Lövdén, M., Schellenbach, M., et al. (2008) Psychological Principles of Successful Aging Technologies: A Mini-Review. Gerontology, 54, 59-68.
[5] Fisk, A.D., Rogers, W.A., Charness, N., et al. (2009) Designing for Older Adults: A Human Factors Interaction Guide. CRC Press.
[6] Salthouse, T.A. (1996) The Processing-Speed Theory of Adult Age Differences in Cognition. Psychological Review, 103, 403-428. [Google Scholar] [CrossRef] [PubMed]
[7] Peek, S.T.M., Wouters, E.J.M., van Hoof, J., et al. (2014) Factors Influencing Acceptance of Technology for Aging in Place: A Systematic Review. International Journal of Medical Informatics, 83, 235-248.
[8] 陈旭, 薛垒. 基于QFD/TRIZ的适老化智能家居产品交互设计研究[J]. 包装工程, 2019, 40(20): 74-80.
[9] Ismail, L.E. and Karwowski, W. (2020) Applications of EEG Indices for the Quantification of Human Cognitive Performance: A Systematic Review and Bibliometric Analysis. PLOS ONE, 15, e0242857. [Google Scholar] [CrossRef] [PubMed]
[10] Longo, L., Wickens, C.D., Hancock, G. and Hancock, P.A. (2022) Human Mental Workload: A Survey and a Novel Inclusive Definition. Frontiers in Psychology, 13, Article 883321. [Google Scholar] [CrossRef] [PubMed]
[11] 刘镇, 马文丽, 梁言珍. 新质生产力背景下塑料注塑智能家居设备适老化研究综述[J]. 塑料包装, 2025, 35(6): 243-248.
[12] 姚源, 曹建初, 吴建辉, 等. 基于毫米波雷达的非接触式生命体征监测技术研究进展[J]. 生物医学工程学杂志, 2021, 38(2): 380-386.
[13] Gomez-Hernandez, M., Ferre, X., Moral, C. and Villalba-Mora, E. (2023) Design Guidelines of Mobile Apps for Older Adults: Systematic Review and Thematic Analysis. JMIR mHealth and uHealth, 11, e43186. [Google Scholar] [CrossRef] [PubMed]
[14] 李邵恺, 黄柘伟, 李新羽, 等. 基于可重构智能超表面的智能家居健康监测系统[J]. 电波科学学报, 2026, 41(1): 155-162.
[15] Cai, T., Ma, J. and Ge-Zhang, S. (2025) Smart Cities and Smart Health: Innovations in Home Medical Devices for Efficient Healthcare Delivery. Results in Engineering, 27, Article 105739. [Google Scholar] [CrossRef
[16] 李芳菲, 薛澄交, 董明, 等. 面向老年人的智能家居语音交互适老化设计评价研究[J]. 包装工程, 2023, 44(8): 208-216.
[17] Cabeza, R., Albert, M., Belleville, S., Craik, F.I.M., Duarte, A., Grady, C.L., et al. (2018) Maintenance, Reserve and Compensation: The Cognitive Neuroscience of Healthy Ageing. Nature Reviews Neuroscience, 19, 701-710. [Google Scholar] [CrossRef] [PubMed]
[18] 林玉琴, 赵杨, 刘婉婷, 等. 数字产品适老化研究综述: 需求挖掘、障碍分析与优化设计[J]. 信息资源管理学报, 2024, 14(4): 146-160.
[19] 薛澄交, 李方慧, 牛亚峰, 等. 基于脑电信号的复杂信息界面认知负荷综合评价模型[J]. 机械工程学报, 2020, 56(10): 229-238.