下肢截肢者的运动活动。
Locomotor activities of individuals with lower-limb amputation.
机构信息
University of Washington, Seattle, WA.
Institute of Field Robotics, Bangkok, Thailand.
出版信息
Prosthet Orthot Int. 2021 Jun 1;45(3):191-197. doi: 10.1097/PXR.0000000000000009.
BACKGROUND
Ambulatory individuals with lower-limb amputation perform a variety of locomotor activities, but the step count distribution of these activities is unknown.
OBJECTIVE
To describe a novel method for activity monitoring and to use it to count steps taken while walking straight ahead on level ground, turning right and left, up and down stairs, and up and down ramps.
STUDY DESIGN
This is an observational study.
METHODS
A portable instrument to record leg motion was placed on or inside the prosthetic pylon of 10 individuals with unilateral transtibial amputations. Participants first walked a defined course in a hospital environment to train and validate a machine learning algorithm for classifying locomotor activity. Participants were then free to pursue their usual activities while data were continuously collected over 1-2 d.
RESULTS
Overall classification accuracy was 97.5% ± 1.5%. When participants were free to walk about their home, work, and community environments, 82.8% of all steps were in a straight line, 9.0% were turning steps, 4.8% were steps on stairs, and 3.6% were steps on ramps.
CONCLUSION
A novel activity monitoring method accurately classified the locomotion activities of individuals with lower-limb amputation. Nearly 1 in 5 of all steps taken involved turning or walking on stairs and ramps.
背景
下肢截肢的门诊患者进行各种步行活动，但这些活动的步数分布尚不清楚。
目的
描述一种新的活动监测方法，并使用该方法计算在平地直走、左右转弯、上下楼梯和上下斜坡时所走的步数。
研究设计
这是一项观察性研究。
方法
将一个用于记录腿部运动的便携式仪器放在假肢支柱上或内部，10 名单侧胫骨截肢患者参与研究。参与者首先在医院环境中走一段规定的路线，以训练和验证用于分类步行活动的机器学习算法。然后，参与者可以在 1-2 天内自由地进行他们的日常活动，同时连续收集数据。
结果
总体分类准确率为 97.5%±1.5%。当参与者自由地在家庭、工作和社区环境中行走时，82.8%的步数是直线行走，9.0%是转弯步，4.8%是楼梯步，3.6%是斜坡步。
结论
一种新的活动监测方法可以准确地对下肢截肢患者的步行活动进行分类。近五分之一的步数涉及转弯或上下楼梯和斜坡。
Zotero 插件