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Optimization of a lensless digital holographic otoscope system for transient measurements of the human tympanic membrane

机译:用于人鼓膜瞬时测量的无镜头数字全息耳镜系统的优化

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摘要

In this paper, we propose a multi-pulsed double exposure (MPDE) acquisition method to quantify in full-field-of-view the transient (i.e., >10 kHz) acoustically induced nanometer scale displacements of the human tympanic membrane (TM or eardrum). The method takes advantage of the geometrical linearity and repeatability of the TM displacements to enable high-speed measurements with a conventional camera (i.e., <20 fps).The MPDE is implemented on a previously developed digital holographic system (DHS) to enhance its measurement capabilities, at a minimum cost, while avoiding constraints imposed by the spatial resolutions and dimensions of high-speed (i.e., >50 kfps) cameras. To our knowledge, there is currently no existing system to provide such capabilities for the study of the human TM.The combination of high temporal (i.e., >50 kHz) and spatial (i.e., >500k data points) resolutions enables measurements of the temporal and frequency response of all points across the surface of the TM simultaneously. The repeatability and accuracy of the MPDE method are verified against a Laser Doppler Vibrometer (LDV) on both artificial membranes and ex-vivo human TMs that are acoustically excited with a sharp (i.e., <100 μs duration) click.The measuring capabilities of the DHS, enhanced by the MPDE acquisition method, allow for quantification of spatially dependent motion parameters of the TM, such as modal frequencies, time constants, as well as inferring local material properties.
机译:在本文中,我们提出了一种多脉冲双曝光(MPDE)采集方法来量化全视场中人鼓膜(TM或鼓膜)的瞬态(即,> 10 kHz)声诱发的纳米尺度位移。 )。该方法利用TM位移的几何线性和可重复性,可以使用传统相机进行高速测量(即<20 fps)。MPDE在先前开发的数字全息系统(DHS)上实现,以增强其测量以最小的成本实现功能,同时避免了高速(即> 50 kfps)相机的空间分辨率和尺寸所施加的限制。据我们所知,目前尚不存在为人类TM研究提供此类功能的系统。高时间分辨率(即,> 50 kHz)和空间分辨率(即,> 500k数据点)的组合可以测量时间以及TM表面上所有点的频率响应。 MPDE方法的可重复性和准确性已通过激光多普勒振动计(LDV)在人造膜和离体人类TM上进行了验证,这些TM膜均以尖锐的咔嗒声(即持续时间小于100μs)被声激发。通过MPDE采集方法增强的DHS可以量化TM的空间相关运动参数,例如模态频率,时间常数,以及推断局部材料属性。

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