Nonlinear modeling of FES-supported standing-up in paraplegia for selection of feedback sensors
Nonlinear modeling of FES-supported standing-up in paraplegia for selection of feedback sensors
复制标题
FES 支持的截瘫站立非线性建模，用于选择反馈传感器
DOI：
10.1109/tnsre.2004.841879
复制
发表时间：
2005
影响因子：
4.9
通讯作者：
T. Bajd
中科院分区：
文献类型：
--
作者：
R. Kamnik;J. Shi;Roderick Murray;T. Bajd
本文分析了截瘫患者的站立动作，将身体支撑力作为功能性电刺激（FES）辅助站立的潜在反馈源。分析研究了手臂、脚和座椅反应信号对人体质心（COM）轨迹重建的意义。对8名截瘫患者的站立行为进行分析，测量其运动学和反作用力，为建模提供数据。两种非线性经验建模方法的实施高斯过程（GP）先验和多层感知器人工神经网络（ANN），并在垂直和水平COM组件重建的性能进行了比较。作为输入，结合不同数量的传感器的10个传感器配置进行了评估，权衡了所选变量的建模性能和日常应用中的易用性。为了评估的目的，计算模型输出和基于运动学的COM轨迹之间的均方根差。结果表明，在FES辅助站立COM评估的力反馈是可比的替代运动学测量系统。结果表明，GP提供了更好的建模性能，在更高的计算成本。此外，平均结果的基础上，使用的传感系统，包括一个六维的手柄力传感器和仪表脚鞋垫建议。该配置对于实现是实用的，并且使用GP模型在水平方向上实现了16 /spl plusmn/1.8mm和在垂直方向上实现了39 /spl plusmn/3.7mm的COM估计的平均精度。研究中分析的其他一些配置显示出更好的建模精度，但对于日常使用来说不太实用。
This paper presents analysis of the standing-up manoeuvre in paraplegia considering the body supportive forces as a potential feedback source in functional electrical stimulation (FES)-assisted standing-up. The analysis investigates the significance of arm, feet, and seat reaction signals to the human body center-of-mass (COM) trajectory reconstruction. The standing-up behavior of eight paraplegic subjects was analyzed, measuring the motion kinematics and reaction forces to provide the data for modeling. Two nonlinear empirical modeling methods are implemented-Gaussian process (GP) priors and multilayer perceptron artificial neural networks (ANN)-and their performance in vertical and horizontal COM component reconstruction is compared. As the input, ten sensory configurations that incorporated different number of sensors were evaluated trading off the modeling performance for variables chosen and ease-of-use in everyday application. For the purpose of evaluation, the root-mean-square difference was calculated between the model output and the kinematics-based COM trajectory. Results show that the force feedback in COM assessment in FES assisted standing-up is comparable alternative to the kinematics measurement systems. It was demonstrated that the GP provided better modeling performance, at higher computational cost. Moreover, on the basis of averaged results, the use of a sensory system incorporating a six-dimensional handle force sensor and an instrumented foot insole is recommended. The configuration is practical for realization and with the GP model achieves an average accuracy of COM estimation 16 /spl plusmn/ 1.8 mm in horizontal and 39 /spl plusmn/ 3.7 mm in vertical direction. Some other configurations analyzed in the study exhibit better modeling accuracy, but are less practical for everyday usage.