L2TI, University Paris 13, 93430 Villetaneuse, France.
COGNAC-G (UMR 8257), CNRS Service de Santé des Armées University Paris Descartes, 75006 Paris, France.
Sensors (Basel). 2018 Nov 19;18(11):4033. doi: 10.3390/s18114033.
This article presents a method for step detection from accelerometer and gyrometer signals recorded with Inertial Measurement Units (IMUs). The principle of our step detection algorithm is to recognize the start and end times of the steps in the signal thanks to a predefined library of templates. The algorithm is tested on a database of 1020 recordings, composed of healthy subjects and patients with various neurological or orthopedic troubles. Simulations on more than 40,000 steps show that the template-based method achieves remarkable results with a 98% recall and a 98% precision. The method adapts well to pathological subjects and can be used in a medical context for robust step estimation and gait characterization.
本文提出了一种基于加速度计和陀螺仪信号的惯性测量单元（IMU）的步频检测方法。我们的步频检测算法的原理是通过预定义的模板库来识别信号中步的起止时间。该算法在由 1020 个记录组成的数据库上进行了测试，这些记录包括健康受试者和患有各种神经或骨科疾病的患者。对超过 40000 步的模拟表明，基于模板的方法具有显著的效果，召回率为 98%，精度为 98%。该方法很好地适应了病理受试者，可以在医学环境中用于稳健的步频估计和步态特征描述。
