Department of Mechatronics Engineering, Sakarya University of Applied Sciences, Esentepe Campus, Serdivan, Sakarya, Turkey.
Department of Electrical and Electronics Engineering, Sakarya University of Applied Sciences, Esentepe Campus, Serdivan, Sakarya, Turkey.
Biomed Tech (Berl). 2020 Oct 19;66(2):153-158. doi: 10.1515/bmt-2020-0082. Print 2021 Apr 27.
Earlier studies showed that external focusing enhances motor performance and reduces muscular activity compare to internal one. However, low activity is not always desired especially in case of Human-Machine Interface applications. This study is based on investigating the effects of attentional focusing preferences on EMG based control systems. For the EMG measurements via biceps brachii muscles, 35 subjects were asked to perform weight-lifting under control, external and internal focus conditions. The difference between external and internal focusing was found to be significant and internal focus enabled higher EMG activity. Besides, six statistical features, namely, RMS, maximum, minimum, mean, standard deviation, and variance were extracted from both time and frequency domains to be used as inputs for Artificial Neural Network classifiers. The results found to be 87.54% for ANN1 and 82.69% for ANN2, respectively. These findings showed that one's focus of attention would be predicted during the performance and unlike the literature, internal focusing could be also useful when it is used as an input for HMI studies. Therefore, attentional focusing might be an important strategy not only for performance improvement to human movement but also for advancing the study of EMG-based control mechanisms.
早期的研究表明，与内部聚焦相比，外部聚焦可以提高运动表现并减少肌肉活动。然而，在人机界面应用等情况下，低活动并不总是可取的。本研究基于研究注意焦点偏好对基于肌电图的控制系统的影响。对于肱二头肌的肌电图测量，要求 35 名受试者在控制、外部和内部焦点条件下进行举重。发现外部和内部焦点之间存在显著差异，内部焦点可实现更高的肌电图活动。此外，从时域和频域中提取了六个统计特征，即均方根值、最大值、最小值、平均值、标准差和方差，作为人工神经网络分类器的输入。结果对于 ANN1 为 87.54%，对于 ANN2 为 82.69%。这些发现表明，在执行过程中可以预测一个人的注意力焦点，与文献不同的是，当将内部焦点用作人机界面研究的输入时，它也可能是有用的。因此，注意力焦点不仅可能是提高人类运动表现的重要策略，而且可能是推进基于肌电图的控制机制研究的重要策略。
