Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Spain.
J Neuroeng Rehabil. 2012 Dec 10;9:85. doi: 10.1186/1743-0003-9-85.
sEMG signal has been widely used in different applications in kinesiology and rehabilitation as well as in the control of human-machine interfaces. In general, the signals are recorded with bipolar electrodes located in different muscles. However, such configuration may disregard some aspects of the spatial distribution of the potentials like location of innervation zones and the manifestation of inhomogineties in the control of the muscular fibers. On the other hand, the spatial distribution of motor unit action potentials has recently been assessed with activation maps obtained from High Density EMG signals (HD-EMG), these lasts recorded with arrays of closely spaced electrodes. The main objective of this work is to analyze patterns in the activation maps, associating them with four movement directions at the elbow joint and with different strengths of those tasks. Although the activation pattern can be assessed with bipolar electrodes, HD-EMG maps could enable the extraction of features that depend on the spatial distribution of the potentials and on the load-sharing between muscles, in order to have a better differentiation between tasks and effort levels.
An experimental protocol consisting of isometric contractions at three levels of effort during flexion, extension, supination and pronation at the elbow joint was designed and HD-EMG signals were recorded with 2D electrode arrays on different upper-limb muscles. Techniques for the identification and interpolation of artifacts are explained, as well as a method for the segmentation of the activation areas. In addition, variables related to the intensity and spatial distribution of the maps were obtained, as well as variables associated to signal power of traditional single bipolar recordings. Finally, statistical tests were applied in order to assess differences between information extracted from single bipolar signals or from HD-EMG maps and to analyze differences due to type of task and effort level.
Significant differences were observed between EMG signal power obtained from single bipolar configuration and HD-EMG and better results regarding the identification of tasks and effort levels were obtained with the latter. Additionally, average maps for a population of 12 subjects were obtained and differences in the co-activation pattern of muscles were found not only from variables related to the intensity of the maps but also to their spatial distribution.
Intensity and spatial distribution of HD-EMG maps could be useful in applications where the identification of movement intention and its strength is needed, for example in robotic-aided therapies or for devices like powered- prostheses or orthoses. Finally, additional data transformations or other features are necessary in order to improve the performance of tasks identification.
表面肌电信号（sEMG）已广泛应用于运动学和康复领域的各种应用，以及人机接口的控制中。通常，信号是通过位于不同肌肉中的双极电极记录的。然而，这种配置可能会忽略电势的空间分布的某些方面，例如神经支配区的位置和肌肉纤维控制中的不均匀性的表现。另一方面，运动单位动作电位的空间分布最近已通过从高密度肌电图信号（HD-EMG）获得的激活图进行评估，这些信号是用紧密间隔的电极阵列记录的。这项工作的主要目的是分析激活图中的模式，将它们与肘关节的四个运动方向以及这些任务的不同强度相关联。尽管可以使用双极电极评估激活模式，但 HD-EMG 图谱可以提取与电势的空间分布和肌肉之间的负荷分配有关的特征，以便更好地区分任务和努力水平。
设计了一个包含三个努力水平的等长收缩的实验方案，在肘关节处进行屈曲、伸展、旋前和旋后运动，并使用二维电极阵列记录不同上肢肌肉的 HD-EMG 信号。解释了用于识别和插值伪影的技术，以及用于分割激活区域的方法。此外，获得了与图谱强度和空间分布相关的变量，以及与传统单双极记录信号功率相关的变量。最后，应用统计检验来评估从单双极信号或 HD-EMG 图谱中提取的信息之间的差异，并分析由于任务类型和努力水平而导致的差异。
从单双极配置和 HD-EMG 获得的肌电图信号功率之间观察到显著差异，并且后者在识别任务和努力水平方面取得了更好的结果。此外，获得了 12 名受试者的平均图谱，并发现肌肉的共激活模式不仅与图谱强度相关的变量而且与空间分布相关的变量存在差异。
HD-EMG 图谱的强度和空间分布可用于需要识别运动意图及其强度的应用，例如在机器人辅助治疗或动力假肢或矫形器等设备中。最后，需要进行额外的数据转换或其他特征改进任务识别的性能。
