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A Quantitative Evaluation of Drive Pattern Selection for Optimizing EIT-Based Stretchable Sensors

机译:基于EIT的可伸缩传感器优化驱动模式选择的定量评估

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Electrical Impedance Tomography (EIT) is a medical imaging technique that has been recently used to realize stretchable pressure sensors. In this method, voltage measurements are taken at electrodes placed at the boundary of the sensor and are used to reconstruct an image of the applied touch pressure points. The drawback with EIT-based sensors, however, is their low spatial resolution due to the ill-posed nature of the EIT reconstruction. In this paper, we show our performance evaluation of different EIT drive patterns, specifically strategies for electrode selection when performing current injection and voltage measurements. We compare voltage data with Signal-to-Noise Ratio (SNR) and Boundary Voltage Changes (BVC), and study image quality with Size Error (SE), Position Error (PE) and Ringing (RNG) parameters, in the case of one-point and two-point simultaneous contact locations. The study shows that, in order to improve the performance of EIT based sensors, the electrode selection strategies should dynamically change correspondingly to the location of the input stimuli. In fact, the selection of one drive pattern over another can improve the target size detection and position accuracy up to 4.7% and 18%, respectively.
机译:电阻抗断层扫描(EIT)是一种医学成像技术,最近已用于实现可拉伸的压力传感器。在这种方法中,在位于传感器边界的电极处进行电压测量,并用于重建施加的触摸压力点的图像。但是,基于EIT的传感器的缺点在于,由于EIT重建的不适定性,其空间分辨率较低。在本文中,我们展示了我们对不同EIT驱动模式的性能评估,特别是在执行电流注入和电压测量时选​​择电极的策略。我们将电压数据与信噪比(SNR)和边界电压变化(BVC)进行比较,并使用大小误差(SE),位置误差(PE)和振铃(RNG)参数研究图像质量(如果是一种情况)点和两点同时接触位置。研究表明,为了提高基于EIT的传感器的性能,电极选择策略应根据输入刺激的位置动态变化。实际上,一个驱动模式相对于另一个驱动模式的选择可以分别将目标尺寸检测和位置精度分别提高到4.7%和18%。

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