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应对私人及住宅养老院中的人机交互挑战

Navigating human-robot interaction challenges in private and residential aged care homes

David Ahmedt-Aristizabal · Mohammad Ali Armin · Akila Pemasiri · Harshala Gammulle · Tharindu Fernando · David Silvera-Tawil · et al.

中文摘要

本章探讨机器人系统与环境智能如何提升住宅养老机构(RAC)和私人住宅中老年人的照护质量。两类环境空间杂乱、布局动态,住户需求多样,且现场技术支持有限,因而均被视为具挑战性的人机交互(HRI)环境。综述涵盖辅助日常生活、安全监测和社会互动的具身与非具身系统,并重点介绍机器人与固定式、可穿戴传感器协同的混合部署。设计需兼顾老年人的认知、身体和社会需求,包括采用稳健但简洁的语音界面、少量非语言提示、无障碍屏幕伴侣及安全的物品交接。设备端推理、数据最小化、可见的同意控制和透明数据处理则用于保障隐私、信任与可接受性。评估关注每日误报次数、故障恢复时间、工作人员负担和长期可靠性,并讨论可扩展、符合监管要求且支持尊严、安全与独立生活的部署方向。

关键要点

  1. 01将私人住宅和养老机构视为复杂的人机交互环境
  2. 02机器人可辅助日常生活、安全监测与社会互动
  3. 03混合部署结合机器人、固定传感器和可穿戴传感器
  4. 04设计需适应数字素养较低者并兼顾认知及身体需求
  5. 05评估关注误报、恢复时间、人员负担与长期可靠性

解读

尚无解读。

原始英文摘要

arXiv:2610.31149v1 Announce Type: cross Abstract: This chapter explores how robotic systems and ambient intelligence can enhance care for older adults in residential aged care (RAC) homes and private homes. Although these settings differ, we frame both as extreme and challenging environments for human-robot interaction (HRI), characterised by cluttered and dynamic layouts, diverse resident needs, and limited on-site technical support. We review embodied and non-embodied systems that assist with daily living, safety monitoring, and social engagement, highlighting hybrid deployments where robots complement fixed and wearable sensors. To ensure these technologies are usable and effective, design considerations consider the cognitive, physical, and social needs of older adults. Interaction design prioritises accessibility for older adults with low digital literacy, using robust but simple voice interfaces, small sets of non-verbal cues, accessible screen-based companions, and safe object handovers. Privacy, trust, and acceptability are addressed via practical strategies such as on-device inference, data minimisation, visible consent controls, and transparent data handling aligned with emerging artificial intelligence (AI) and privacy regulation. Evaluation emphasises real-world metrics including false alarms per day, time to recover from faults, staff workload, and long-term system reliability. We close by outlining open research challenges and future directions for scalable, regulation-ready deployments that support aging with dignity, safety, and independence.

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