Aranceta-Garza Alejandra, Conway Bernard Arthur
Department of Biomedical Engineering, University of Strathclyde, Glasgow, United Kingdom.
Front Bioeng Biotechnol. 2019 May 22;7:123. doi: 10.3389/fbioe.2019.00123. eCollection 2019.
Hand gesture and grip formations are produced by the muscle synergies arising between extrinsic and intrinsic hand muscles and many functional hand movements involve repositioning of the thumb relative to other digits. In this study we explored whether changes in thumb posture in able-body volunteers can be identified and classified from the modulation of forearm muscle surface-electromyography (sEMG) alone without reference to activity from the intrinsic musculature. In this proof-of-concept study, our goal was to determine if there is scope to develop prosthetic hand control systems that may incorporate myoelectric thumb-position control. Healthy volunteers performed a controlled-isometric grip task with their thumb held in four different opposing-postures. Grip force during task performance was maintained at 30% maximal-voluntary-force and sEMG signals from the forearm were recorded using 2D high-density sEMG (HD-sEMG arrays). Correlations between sEMG amplitude and root-mean squared estimates with variation in thumb-position were investigated using principal-component analysis and self-organizing feature maps. Results demonstrate that forearm muscle sEMG patterns possess classifiable parameters that correlate with variations in static thumb position (accuracy of 88.25 ± 0.5% anterior; 91.25 ± 2.5% posterior musculature of the forearm sites). Of importance, this suggests that in transradial amputees, despite the loss of access to the intrinsic muscles that control thumb action, an acceptable level of control over a thumb component within myoelectric devices may be achievable. Accordingly, further work exploring the potential to provide myoelectric control over the thumb within a prosthetic hand is warranted.
手部姿势和抓握形态是由手部外在肌和内在肌之间产生的肌肉协同作用所形成的,许多手部功能性动作都涉及拇指相对于其他手指的重新定位。在本研究中,我们探讨了能否仅从前臂肌肉表面肌电图(sEMG)的调制中识别并分类健全志愿者的拇指姿势变化,而无需参考内在肌肉组织的活动。在这项概念验证研究中,我们的目标是确定是否有开发可能包含肌电拇指位置控制的假肢手控制系统的空间。健康志愿者在拇指保持四种不同对立姿势的情况下执行了控制等长抓握任务。任务执行期间的握力保持在最大自主力的30%,并使用二维高密度sEMG(HD - sEMG阵列)记录前臂的sEMG信号。使用主成分分析和自组织特征映射研究了sEMG幅度和均方根估计值与拇指位置变化之间的相关性。结果表明,前臂肌肉sEMG模式具有可分类的参数,这些参数与静态拇指位置的变化相关(前臂部位前侧肌肉的准确率为88.25±0.5%;后侧肌肉为91.25±2.5%)。重要的是,这表明对于经桡骨截肢者,尽管无法获取控制拇指动作的内在肌肉,但在肌电设备内对拇指组件实现可接受水平的控制可能是可行的。因此,有必要进一步开展工作,探索在假肢手中提供对拇指的肌电控制的潜力。