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Automated Gait Analysis In The Open-field Test For Laboratory Mice

机译:实验室小鼠野外试验中的自动化步态分析

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In this article, an automated and accurate mouse observation method, based on a conventional test for motor function evaluation, is outlined. The proposed measurement technique was integrated in a regular open-field test, where the trajectory and locomotion of a free-moving mouse were measured simultaneously. The system setup consisted of a transparent cage and a camera placed below it with its lens pointing upward, allowing for images to be captured from underneath the cage while the mouse was walking on the transparent cage floor. Thus, additional information was obtained about the position of the limbs of the mice for gait reconstruction. In a first step, the camera was calibrated as soon as it was fixed in place. A linear calibration factor, relating distances in image coordinates to real-world dimensions, was determined. In a second step, the mouse was located and its body contour segmented from the image by subtracting a previously taken "background" image of the empty cage from the camera image. In a third step, the movement of the mouse was analyzed and its speed estimated from its location in the past few images. If the speed was above a l-sec threshold, the mouse was recognized to be running, and the image was further processed for footprint recognition. In a fourth step, color filtering was applied within the recovered mouse region to measure the position of the mouse's paws, which were visible in the image as small pink spots. Paws that were detected at the same location in a number of subsequent images were kept as footprints-that is, paws in contact with the cage floor. The footprints were classified by their position relative to the mouse's outline as corresponding to the front left or right paw or the hind left or right paw. Finally, eight parameters were calculated from the footprint pattern to describe the locomotion of the mouse: right/left overlap, front/hind base, right/left front limb stride, and right/left hind limb stride. As an application, the system was tested using normal mice and mice displaying pentobarbital-induced ataxia. The footprint parameters measured using the proposed system showed differences of 10% to 20% between normal and ataxic mice.
机译:在本文中,概述了一种基于常规运动功能评估测试的自动且精确的鼠标观察方法。提议的测量技术已集成到常规的开放式测试中,该测试中同时测量了自由移动鼠标的轨迹和运动。系统设置包括一个透明的笼子和一个位于其下方的照相机,其镜头朝上,允许在鼠标在透明的笼子地板上行走时从笼子下面捕获图像。因此,获得了有关用于步态重建的小鼠四肢位置的其他信息。第一步,在将相机固定到位后立即对其进行校准。确定了将图像坐标中的距离与实际尺寸相关联的线性校准因子。在第二步骤中,通过从相机图像中减去先前拍摄的空笼子的“背景”图像,找到鼠标并从图像中分割出其身体轮廓。第三步,分析了鼠标的运动,并根据过去几幅图像中的位置估算了鼠标的速度。如果速度高于1秒的阈值,则将鼠标识别为正在运行,并对图像进行进一步处理以进行足迹识别。第四步,在恢复的鼠标区域内应用彩色过滤,以测量鼠标爪的位置,该爪在图像中可见为小的粉红色斑点。在许多后续图像中的相同位置检测到的爪子被保留为足迹,即与笼子地板接触的爪子。根据足迹相对于鼠标轮廓的位置,将足迹分为左前或右前爪或后左或右后爪。最后,根据足迹模式计算了八个参数来描述鼠标的运动:右/左重叠,前/后基,右/左前肢步幅和右/左后肢步幅。作为应用,使用正常小鼠和显示戊巴比妥诱发的共济失调的小鼠对系统进行了测试。使用建议的系统测量的足迹参数显示正常小鼠和共济失调小鼠之间的差异为10%至20%。

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