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Graded muscle contractions determined by temporal recruitment

机译:通过临时募集确定肌肉的分级收缩

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Electromyogram (EMG) signals have the potential to allow patients without total muscle controls to operate electronic or mechanical devices, such as a power wheelchair. A muscle contraction can be interpreted as a switching signal and its strength can determine the intended level. The purpose of this study is to implement an algorithm to accurately detect the strength of a muscle contraction. Muscle contraction strength can be increased by temporal or spatial recruitment. In this case, the graded muscle contraction is detected by the temporal recruitment, where the frequency of the EMG signal is evaluated. A nonlinear detection algorithm is used to define the duration of a contraction episode. The frequency of the spikes within the contraction episode is used to determine the contraction strength. The algorithm should be useful for designing myoelectrically controlled devices.
机译:肌电图(EMG)信号可能使没有完全肌肉控制能力的患者能够操作电动或机械设备,例如电动轮椅。肌肉收缩可以解释为转换信号,其强度可以确定预期的水平。这项研究的目的是实现一种算法,以准确检测肌肉收缩的强度。肌肉收缩强度可以通过时间或空间募集来增加。在这种情况下,通过临时募集可以检测到渐变的肌肉收缩,其中可以评估EMG信号的频率。非线性检测算法用于定义收缩发作的持续时间。收缩发作中尖峰的频率用于确定收缩强度。该算法对于设计肌电控制装置应该是有用的。

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