Design of Internal Wire-Based Impedance Matching of Helical Antennas Using an Equivalent Thin-Wire Model

We propose a novel design of internal impedance matching networks for axial-mode helical antennas. This network comprises a single wire attached to the helix. One of the main challenges when designing an internal matching network is its strong electromagnetic coupling with the antenna. The matching network must hence be designed in the presence of the antenna, which slows down the design process. To overcome this problem, we formulate an equivalent thin-wire model of the complete helix, including the matching wire (matching network) and the dielectric support. This computationally low-demanding model can be analyzed extremely rapidly, yielding accurate results, which are in excellent agreement with alternative numerical solutions and measurements

ON THE OPTIMAL DIMENSIONS OF HELICAL ANTENNA WITH TRUNCATED-CONE REFLECTOR

This paper presents optimization of a helical antenna with a truncated-cone reflector. We have found that the dimensions of the truncated-cone reflector and the dimensions of the helical antenna need to be optimized simultaneously to obtain the optimal design. Furthermore, we have found that the truncated-cone reflector can significantly increase the gain of the helical antenna compared to a circular or a square flat reflector. A set of diagrams is made to enable simple design of helical antennas with truncated-cone reflectors. Finally, the results are experimentally verified. 1

Quantification of Finger-Tapping Angle Based on Wearable Sensors

We propose a novel simple method for quantitative and qualitative finger-tapping assessment based on miniature inertial sensors (3D gyroscopes) placed on the thumb and index-finger. We propose a simplified description of the finger tapping by using a single angle, describing rotation around a dominant axis. The method was verified on twelve subjects, who performed various tapping tasks, mimicking impaired patterns. The obtained tapping angles were compared with results of a motion capture camera system, demonstrating excellent accuracy. The root-mean-square (RMS) error between the two sets of data is, on average, below 4°, and the intraclass correlation coefficient is, on average, greater than 0.972. Data obtained by the proposed method may be used together with scores from clinical tests to enable a better diagnostic. Along with hardware simplicity, this makes the proposed method a promising candidate for use in clinical practice. Furthermore, our definition of the tapping angle can be applied to all tapping assessment systems