The BioRobotics Institute, Scuola Superiore Sant'Anna, 56127 Pisa, Italy.
Faculty of Electrical Engineering, University of Ljubljana, 1000 Ljubljana, Slovenia.
Sensors (Basel). 2020 Mar 6;20(5):1448. doi: 10.3390/s20051448.
Wearable robotic devices require sensors and algorithms that can recognize the user state in real-time, in order to provide synergistic action with the body. For devices intended for locomotion-related applications, shoe-embedded sensors are a common and convenient choice, potentially advantageous for performing gait assessment in real-world environments. In this work, we present the development of a pair of pressure-sensitive insoles based on optoelectronic sensors for the real-time estimation of temporal gait parameters. The new design makes use of a simplified sensor configuration that preserves the time accuracy of gait event detection relative to previous prototypes. The system has been assessed relatively to a commercial force plate recording the vertical component of the ground reaction force (vGRF) and the coordinate of the center of pressure along the so-called progression or antero-posterior plane (CoP) in ten healthy participants during ground-level walking at two speeds. The insoles showed overall median absolute errors (MAE) of 0.06 (0.02) s and 0.04 (0.02) s for heel-strike and toe-off recognition, respectively. Moreover, they enabled reasonably accurate estimations of the stance phase duration (2.02 (2.03) % error) and CoP profiles (Pearson correlation coefficient with force platform ρCoP = 0.96 (0.02)), whereas the correlation with vGRF measured by the force plate was lower than that obtained with the previous prototype (ρvGRF = 0.47 (0.20)). These results confirm the suitability of the insoles for online sensing purposes such as timely gait phase estimation and discrete event recognition.
可穿戴机器人设备需要能够实时识别用户状态的传感器和算法,以便与身体协同动作。对于用于与运动相关的应用的设备,鞋嵌入式传感器是一种常见且方便的选择,对于在现实环境中进行步态评估可能具有优势。在这项工作中,我们提出了一种基于光电传感器的压力敏感鞋垫的开发,用于实时估计时间步态参数。新设计利用简化的传感器配置,相对于先前的原型保持了步态事件检测的时间精度。该系统已经在十个健康参与者的地面行走时以两种速度相对于商用测力板进行了评估,测力板记录了垂直地面反作用力(vGRF)的垂直分量和沿所谓的行进或前后平面(CoP)的压力中心的坐标。鞋垫对足跟触地和足趾离地的识别的总体中位数绝对误差(MAE)分别为 0.06(0.02)秒和 0.04(0.02)秒。此外,它们能够对站立相持续时间进行合理准确的估计(2.02(2.03)%误差)和 CoP 轮廓(与力台的 Pearson 相关系数ρCoP = 0.96(0.02)),而与力台测量的 vGRF 的相关性低于与先前原型获得的相关性(ρvGRF = 0.47(0.20))。这些结果证实了鞋垫适合在线传感目的,例如及时的步态阶段估计和离散事件识别。