MejiaCruz Yohanna, Franco Jean, Hainline Garret, Fritz Stacy, Jiang Zhaoshuo, Caicedo Juan M, Davis Benjamin, Hirth Victor
San Francisco State University, 1600 Holloway Ave, San Francisco, CA 94132.
University of South Carolina, 300 Main St, Columbia SC, 29201.
Curr Geriatr Rep. 2021 Mar;10(1):32-41. doi: 10.1007/s13670-020-00349-z. Epub 2021 Jan 20.
This article presents an overview of the main technologies used to estimate gait parameters, focusing on walking speed (WS).
New wearable and environmental technologies to estimate WS have been developed in the last five years. Wearable technologies refer to sensors attached to parts of the patient's body that capture the kinematics during walking. Alternatively, environmental technologies capture walking patterns using external instrumentation. In this review, wearable and external technologies have been included.From the different works reviewed, external technologies face the challenge of implementation outside controlled facilities; an advantage that wearable technologies have, but have not been fully explored. Additionally, systems that can track WS changes in daily activities, especially at-home assessments, have not been developed.
Walking speed is a gait parameter that can provide insight into an individual's health status. Image-based, walkways, wearable, and floor-vibrations technologies are the most current used technologies for estimating WS. In this paper, research from the last five years that explore each technology's capabilities on WS estimation and an evaluation of their technical and clinical aspects is presented.
本文概述了用于估计步态参数的主要技术,重点关注步行速度(WS)。
在过去五年中,已开发出用于估计步行速度的新型可穿戴和环境技术。可穿戴技术是指附着在患者身体部位的传感器,用于捕捉步行过程中的运动学信息。另外,环境技术使用外部仪器来捕捉步行模式。在本综述中,纳入了可穿戴技术和外部技术。从所综述的不同研究来看,外部技术面临在受控设施之外实施的挑战;而这是可穿戴技术所具有的优势,但尚未得到充分探索。此外,尚未开发出能够跟踪日常活动中步行速度变化的系统,尤其是在家中进行评估的系统。
步行速度是一种步态参数,可提供有关个人健康状况的信息。基于图像的技术、人行道技术、可穿戴技术和地面振动技术是目前用于估计步行速度的技术。本文介绍了过去五年中探索每种技术在估计步行速度方面的能力以及对其技术和临床方面进行评估的研究。