Hoffer J A, Stein R B, Haugland M K, Sinkjaer T, Durfee W K, Schwartz A B, Loeb G E, Kantor C
Cleveland FES Center, OH 44106-3052, USA.
J Rehabil Res Dev. 1996 Apr;33(2):145-57.
In current functional neuromuscular stimulation systems (FNS), control and feedback signals are usually provided by external sensors and switches, which pose problems such as donning and calibration time, cosmesis, and mechanical vulnerability. Artificial sensors are difficult to build and are insufficiently biocompatible and reliable for implantation. With the advent of methods for electrical interfacing with nerves and muscles, natural sensors are being considered as an alternative source of feedback and command signals for FNS. Decision making methods for higher level control can perform equally well with natural or artificial sensors. Recording nerve cuff electrodes have been developed and tested in animals and demonstrated to be feasible in humans for control of dorsiflexion in foot-drop and grasp in quadriplegia. Electromyographic signals, being one thousand times larger than electroneurograms, are easier to measure but have not been able to provide reliable indicators (e.g., of muscle fatigue) that would be useful in FNS systems. Animal studies have shown that information about the shape and movement of arm trajectories can be extracted from brain cortical activity, suggesting that FNS may ultimately be directly controllable from the central nervous system.
在当前的功能性神经肌肉刺激系统(FNS)中,控制和反馈信号通常由外部传感器和开关提供,这带来了诸如穿戴和校准时间、美观性以及机械易损性等问题。人工传感器难以制造,且对于植入而言,其生物相容性和可靠性不足。随着与神经和肌肉进行电连接方法的出现,天然传感器正被视为FNS反馈和命令信号的替代来源。用于更高层次控制的决策方法使用天然或人工传感器时性能相当。记录神经袖套电极已在动物身上开发并测试,且已证明在人类中用于控制足下垂时的背屈和四肢瘫痪时的抓握是可行的。肌电信号比神经电图大一千倍,更容易测量,但尚未能够提供在FNS系统中有用的可靠指标(例如肌肉疲劳指标)。动物研究表明,可以从大脑皮层活动中提取有关手臂轨迹形状和运动的信息,这表明FNS最终可能直接由中枢神经系统控制。