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使用惯性测量单元（IMU）传感器评估不同年龄组和地板材料的步行适宜性。

Evaluating walkability across age groups and flooring materials using IMU sensors.

作者信息

Jo Daehwi, Kim Hyunsoo

机构信息

Department of Architectural Engineering, Dankook University, Yongin-si, Gyeonggi-do, Republic of Korea.

出版信息

Front Public Health. 2024 Dec 5;12:1509602. doi: 10.3389/fpubh.2024.1509602. eCollection 2024.

DOI:10.3389/fpubh.2024.1509602
PMID:39703485
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11657239/
Abstract

This study presents a novel approach to quantitatively assess the impact of flooring materials on walkability using Inertial Measurement Unit (IMU) sensors and Dynamic Time Warping (DTW) algorithm. Four common pavement materials (wood, asphalt, concrete block, and cement) were evaluated across five age groups (20-30, 30-40, 40-50, 50-60, and over 60 years) with 80 participants walking 1,200 m on each surface. IMU sensors attached to the lumbar region recorded acceleration and gyroscope data, which were then analyzed using DTW to quantify gait stability. Results showed significant differences in DTW values among materials, with wood exhibiting the lowest average DTW value (12.99 ± 3.05) indicating the most stable walking environment, while cement showed the highest (39.14 ± 9.74). In addition, age-related analysis revealed increasing DTW values with age across all materials, with the most pronounced effect in the older adult group. The methodology presented offers sensor-based approach for evaluating and optimizing pedestrian infrastructure in smart city development.

摘要

本研究提出了一种新颖的方法，利用惯性测量单元（IMU）传感器和动态时间规整（DTW）算法来定量评估地板材料对步行适宜性的影响。对四种常见路面材料（木材、沥青、混凝土块和水泥）在五个年龄组（20 - 30岁、30 - 40岁、40 - 50岁、50 - 60岁和60岁以上）进行了评估，80名参与者在每种路面上行走1200米。附着在腰部区域的IMU传感器记录加速度和陀螺仪数据，然后使用DTW进行分析以量化步态稳定性。结果表明，不同材料之间的DTW值存在显著差异，木材的平均DTW值最低（12.99±3.05），表明步行环境最稳定，而水泥的DTW值最高（39.14±9.74）。此外，与年龄相关的分析显示，所有材料的DTW值均随年龄增长而增加，在老年组中影响最为明显。所提出的方法为智能城市发展中评估和优化行人基础设施提供了基于传感器的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1757/11657239/55cfad8624d4/fpubh-12-1509602-g007.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1757/11657239/55cfad8624d4/fpubh-12-1509602-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1757/11657239/dab18143a56b/fpubh-12-1509602-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1757/11657239/f3efaa2fc122/fpubh-12-1509602-g002.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1757/11657239/55cfad8624d4/fpubh-12-1509602-g007.jpg

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