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用于在日常环境中测量和可视化身体支撑力矢量场的便携式技术。

Portable Technology to Measure and Visualize Body-Supporting Force Vector Fields in Everyday Environments.

作者信息

Nomura Ayano, Nishida Yoshifumi

机构信息

Department of Mechanical Engineering, Institute of Science Tokyo, Tokyo 152-0033, Japan.

出版信息

Sensors (Basel). 2025 Jun 25;25(13):3961. doi: 10.3390/s25133961.

Abstract

Object-related accidents among older adults often result from inadequately designed furniture and fixtures that do not accommodate age-related changes. However, technologies for quantitatively capturing how furniture and fixtures assist the body in daily life remain limited. This study addresses this gap by introducing a portable, non-disruptive system that measures and visualizes how humans interact with environmental objects, particularly during transitional movements such as standing, turning, or reaching. The system integrates wearable force sensors, motion capture gloves, RGB-D cameras, and LiDAR-based environmental scanning to generate spatial maps of body-applied forces, overlaid onto point cloud representations of actual living environments. Through home-based experiments involving 13 older adults aged 69-86 across nine households, the system effectively identified object-specific support interactions with specific furniture (e.g., doorframes, shelves) and enabled a three-dimensional comparative analysis across different spaces, including living rooms, entryways, and bedrooms. The visualization captured essential spatial features-such as contact height and positional context-without altering the existing environment. This study presents a novel methodology for evaluating life environments from a life-centric perspective and offers insights for the inclusive design of everyday objects and spaces to support safe and independent aging in place.

摘要

老年人中与物体相关的事故往往是由于家具和固定装置设计不当,无法适应与年龄相关的变化。然而,用于定量捕捉家具和固定装置在日常生活中如何辅助身体的技术仍然有限。本研究通过引入一种便携式、非侵入性系统来填补这一空白,该系统可以测量并可视化人类与环境物体的交互方式,特别是在站立、转身或伸手等过渡动作过程中。该系统集成了可穿戴式力传感器、动作捕捉手套、RGB-D相机和基于激光雷达的环境扫描设备,以生成人体作用力的空间地图,并叠加在实际生活环境的点云表示上。通过在九个家庭中对13名年龄在69至86岁之间的老年人进行的居家实验,该系统有效地识别了与特定家具(如门框、架子)的特定物体支撑交互,并实现了对不同空间(包括客厅、入口和卧室)的三维比较分析。可视化捕捉了诸如接触高度和位置背景等基本空间特征,同时不会改变现有环境。本研究提出了一种从以生活为中心的角度评估生活环境的新方法,并为日常物品和空间的包容性设计提供了见解,以支持安全和独立的就地养老。

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