...
首页> 外文期刊>IEEE Transactions on Biomedical Engineering >The electromyogram (EMG) as a control signal for functional neuromuscular stimulation. I. Autoregressive modeling as a means of EMG signature discrimination
【24h】

The electromyogram (EMG) as a control signal for functional neuromuscular stimulation. I. Autoregressive modeling as a means of EMG signature discrimination

机译:肌电图(EMG)作为功能性神经肌肉刺激的控制信号。 I.自回归建模作为EMG签名鉴别的一种手段

获取原文
获取原文并翻译 | 示例
   

获取外文期刊封面封底 >>

       

摘要

The successful application of functional neuromuscular stimulation to the muscles of paraplegics depends to a large extent on the adequate provision of a means by which the subject can exercise control over the resulting movement. The use of above-lesion electromyographic signals as a solution to the control problem is considered. A number of criteria for such a control system are defined. The general concepts underlying time-series analysis are described and the suitability of this method as a means of processing electromyographic signals is investigated. The electromyogram, which exhibits weak stationarity over short time intervals, is represented by a fourth-order autoregressive model. A sequential least-squares algorithm is used to determine the model parameters, which are then used to achieve signature discrimination.
机译:将功能性神经肌肉刺激成功地应用于截瘫患者的肌肉在很大程度上取决于是否适当提供了一种方法,使受试者能够对所产生的运动进行控制。考虑使用病变以上肌电信号作为控制问题的解决方案。定义了这种控制系统的许多标准。描述了时间序列分析的基本概念,并研究了该方法作为处理肌电信号的方法的适用性。肌电图在短时间间隔内表现出弱的平稳性,由四阶自回归模型表示。顺序最小二乘算法用于确定模型参数,然后将其用于实现特征识别。

著录项

相似文献

  • 外文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号