Abstract
Objective: The objectives of this paper are to determine the optimal location for ultrasound transducer placement on the anterior forearm for imaging maximum muscle deformations during different hand motions and to investigate the effect of using a sparse set of ultrasound scanlines for motion classification for ultrasound-based muscle computer interfaces (MCIs). Methods: The optimal placement of the ultrasound transducer along the forearm is identified using freehand 3D reconstructions of the muscle thickness during rest and motion completion. From the ultrasound images acquired from the optimally placed transducer, we determine classification accuracy with equally spaced scanlines across the cross-sectional field-of-view (FOV). Furthermore, we investigated the unique contribution of each scanline to class discrimination using Fisher criteria (FC) and mutual information (MI) with respect to motion discriminability. Results: Experiments with 5 able-bodied subjects show that the maximum muscle deformation occurred between 30-50% of the forearm length for multiple degrees-of-freedom. The average classification accuracy was 94.6% with the entire 128 scanline image and 94.5% with 4 equally-spaced scanlines. However, no significant improvement in classification accuracy was observed with optimal scanline selection using FC and MI. Conclusion: For an optimally placed transducer, a small subset of ultrasound scanlines can be used instead of a full imaging array without sacrificing performance in terms of classification accuracy for multiple degrees-of-freedom. Significance: The selection of a small subset of transducer elements can enable the reduction of computation, and simplification of the instrumentation and power consumption of wearable sonomyographic MCIs particularly for rehabilitation and gesture recognition applications.
Abstract (translated)
目的：本文的目的是确定超声换能器放置在前臂上的最佳位置，以便在不同的手部运动中成像最大肌肉变形，并研究使用稀疏超声扫描线组对基于超声的运动分类的影响。肌肉计算机接口（MCI）。方法：使用在休息和运动完成期间肌肉厚度的徒手三维重建来识别超声换能器沿前臂的最佳放置。根据从最佳放置的换能器获取的超声图像，我们通过横截面视场（FOV）上的等间隔扫描线确定分类精度。此外，我们使用Fisher标准（FC）和互信息（MI）研究了每条扫描线对类别识别的独特贡献，以及运动可辨性。结果：5名健全受试者的实验表明，对于多个自由度，最大肌肉变形发生在前臂长度的30-50％之间。整个128扫描线图像的平均分类精度为94.6％，4个等间距扫描线的平均分类精度为94.5％。然而，使用FC和MI的最佳扫描线选择没有观察到分类准确性的显着改善。结论：对于最佳放置的换能器，可以使用一小部分超声扫描线代替完整的成像阵列，而不会牺牲多个自由度的分类精度方面的性能。意义：选择一小部分换能器元件可以减少计算量，简化可穿戴式超声检查MCI的仪器和功耗，特别是对于康复和手势识别应用。
URL
https://arxiv.org/abs/1809.01952
