Towards Ubiquitous Acquisition and Processing of Gait Parameters
Towards Ubiquitous Acquisition and Processing of Gait Parameters
复制标题
迈向步态参数的普遍获取和处理
DOI：
--
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
A. Muñoz
中科院分区：
文献类型：
--
作者：
Irvin Hussein Lopez;A. Muñoz
步态分析是测量和评估步态和步行的时空模式，即人体运动的过程。该过程通常在能够采集大量数据并基于参考值提供步态分析评估的专用设备上执行。基于步态评估，治疗师和医生可以开药，并提供物理治疗康复步态问题的患者。这项工作是面向支持设计的流动和无处不在的步态监测技术。提出了一种利用无线加速度传感器提供的原始信号自动检测人体步幅的概率方法。从原始加速度信号中提取局部阈值，并将其用于区分实际步幅与通常由加速度信号的显著偏移产生的特征峰值。然后，用这些峰值训练baking分类器以检测和计数步幅。所提出的方法具有良好的精度分类的原始加速度信号的步伐，年轻人和老年人。需要步幅检测来计算步态参数并提供临床评估。
Gait analysis is the process of measuring and evaluating gait and walking spatio-temporal patterns, namely of human locomotion. This process is usually performed on specialized equipment that is capable of acquiring extensive data and providing a gait analysis assessment based on reference values. Based on gait assessments, therapists and physicians can prescribe medications and provide physical therapy rehabilitation to patients with gait problems. This work is oriented to support the design of ambulatory and ubiquitous technologies for gait monitoring. A probabilistic method to automatically detect human strides from raw signals provided by wireless accelerometers is presented. Local thresholds are extracted from raw acceleration signals, and used to distinguish actual strides from characteristic peaks commonly produced by significant shifts of the acceleration signals. Then, a bayesian classifier is trained with these peaks to detect and count strides. The proposed method has a good precision for classifying strides of raw acceleration signals for both, young and elderly individuals. Strides detection is required to calculate gait parameters and provide a clinical assessment.
DOI：
--
发表时间：
--
期刊：
--
影响因子：
--
作者：
Jeffrey M. Hausdorff
通讯作者：
Jeffrey M. Hausdorff