Reliability of neural-network functional electrical stimulation gait-control system
Reliability of neural-network functional electrical stimulation gait-control system
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DOI：
10.1007/bf02513359
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发表时间：
1999-09-01
影响因子：
3.2
通讯作者：
Granat, MH
中科院分区：
文献类型：
--
作者：
Tong, KY;Granat, MH
功能性电刺激（FES）已被用于恢复脊髓损伤（SCI）患者的行走。使用人工智能（AI），FES控制器已经开发出来，允许刺激的自动定相，以取代手或脚跟开关的功能。然而，还没有研究来评估这些人工智能系统的可靠性。神经网络被用来构建FES控制器来控制刺激的时间。使用传感器组中不同数量的传感器和来自每个传感器的不同数量的数据点。招募了两名不完全SCI受试者，每个人都在三个不同的场合进行测试。结果表明，神经网络控制器可以在六个月内保持高精度（两个和三个传感器组约90%，一个传感器组约80%）。两个或三个传感器足以提供足够的信息来构建可靠的FES控制系统，并且数据点的数量对系统的可靠性没有任何影响。
Functional electrical stimulation (FES) has been used for restoring walking in spinal-cord injured (SCI) persons. Using artificial intelligence (AI), FES controllers have been developed that allow the automatic phasing of stimulation, to replace the function of hand or heel switches. However, there has been no study to evaluate the reliability of these Al systems. Neural networks were used to construct FES controllers to control the timing of stimulation. Different numbers of sensors in the sensor set and different numbers of data points from each sensor were used. Two incomplete-SCI subjects were recruited, and each was tested on three separate occasions. The results show the neural-network controllers can maintain a high accuracy (around 90% for the two- and three-sensor groups and 80% for the one-sensor group) over a period of six months. Two or three sensors were sufficient to provide enough information to construct a reliable FES control system, and the number of data points did not have any effect on the reliability of the system.