Estimating Walking Speed in the Wild.
Estimating Walking Speed in the Wild.
复制标题
估计野外的步行速度。
DOI：
10.3389/fspor.2020.583848
复制
发表时间：
2020
影响因子：
2.7
通讯作者：
Cain SM
中科院分区：
文献类型：
--
作者：
Baroudi L;Newman MW;Jackson EA;Barton K;Shorter KA;Cain SM
一个人的身体活动对预防和恢复包括心血管疾病在内的各种健康问题的潜力有着重大影响。精确量化患者的日常身体活动水平，可以通过运动的类型，强度和持续时间来表征，这对临床医生至关重要。对于大多数人来说，步行是一项主要且基本的身体活动。步行速度已被证明与各种心脏病和整体功能相关。因此，它经常被用作评估健康表现的指标。存在一系列临床行走测试来评估步态并为临床决策提供信息。然而，这些评估通常很短，提供定性的运动评估，并且在不代表真实世界的临床环境中进行。可穿戴传感和相关算法的技术进步为补充自由生活期间的临床运动评估提供了新的机会。然而，使用可穿戴设备通知临床决策提出了几个挑战，包括缺乏受试者依从性和有限的传感器电池寿命。为了弥合自由生活和临床环境之间的差距差距，我们提出了一种方法，在该方法中，我们利用不同的可穿戴传感器在不同的时间尺度和分辨率。在这里，我们提出了一种方法来准确地估计步态速度在自由生活的环境中，从低功耗，重量轻的基于加速度计的生物记录标签固定在大腿上。我们使用步态运动学的高分辨率测量来构建特定于受试者的数据驱动模型，以准确地将从生物记录系统中提取的步频映射到步速。基于模型的估计步幅速度进行了评估，使用长的户外行走，并比较步幅参数计算从脚穿惯性测量单元使用零速度更新算法。该方法对所有受试者的平均一致性相关系数为0.80，97%的误差在±0.2m· s−1以内。这里提出的方法提供了有希望的结果，可以使临床医生补充他们现有的活动水平和健身与运动持续时间和强度（步行速度）的测量提取在一周的时间尺度和患者的自由生活环境的评估。
An individual's physical activity substantially impacts the potential for prevention and recovery from diverse health issues, including cardiovascular diseases. Precise quantification of a patient's level of day-to-day physical activity, which can be characterized by the type, intensity, and duration of movement, is crucial for clinicians. Walking is a primary and fundamental physical activity for most individuals. Walking speed has been shown to correlate with various heart pathologies and overall function. As such, it is often used as a metric to assess health performance. A range of clinical walking tests exist to evaluate gait and inform clinical decision-making. However, these assessments are often short, provide qualitative movement assessments, and are performed in a clinical setting that is not representative of the real-world. Technological advancements in wearable sensing and associated algorithms enable new opportunities to complement in-clinic evaluations of movement during free-living. However, the use of wearable devices to inform clinical decisions presents several challenges, including lack of subject compliance and limited sensor battery life. To bridge the gap between free-living and clinical environments, we propose an approach in which we utilize different wearable sensors at different temporal scales and resolutions. Here, we present a method to accurately estimate gait speed in the free-living environment from a low-power, lightweight accelerometer-based bio-logging tag secured on the thigh. We use high-resolution measurements of gait kinematics to build subject-specific data-driven models to accurately map stride frequencies extracted from the bio-logging system to stride speeds. The model-based estimates of stride speed were evaluated using a long outdoor walk and compared to stride parameters calculated from a foot-worn inertial measurement unit using the zero-velocity update algorithm. The proposed method presents an average concordance correlation coefficient of 0.80 for all subjects, and 97% of the error is within ±0.2m· s−1. The approach presented here provides promising results that can enable clinicians to complement their existing assessments of activity level and fitness with measurements of movement duration and intensity (walking speed) extracted at a week time scale and in the patients' free-living environment.
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影响因子：
3.3
作者：
Giavarina D
通讯作者：
Giavarina D
影响因子：
11.7
作者：
Edwardson CL;Winkler EAH;Bodicoat DH;Yates T;Davies MJ;Dunstan DW;Healy GN
通讯作者：
Healy GN
影响因子：
3
作者：
Dean, CM;Richards, CL;Malouin, F
通讯作者：
Malouin, F
DOI：
10.1198/016214502753479392
发表时间：
2002-03-01
影响因子：
3.7
作者：
Lin, L;Hedayat, AS;Yang, M
通讯作者：
Yang, M
影响因子：
6.7
作者：
Bohannon, RW
通讯作者：
Bohannon, RW