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Development of a Measurement and Evaluation System for Bed-Making Activity for Self-training

机译:开发自我训练床上活动的测量和评估系统

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This study proposes a method to automatically measure multiple objects by image processing for constructing a system for nursing trainees of self-training in the skill of bed making. In a previous study, we constructed a system to measure and evaluate trainee performance using three RGB-D (RGB color and depth) sensors. Our previous system had a problem with recognition of equipment such as the bed pad and the sheet because of color change by the light condition, the automatic color correction by the sensors and color variability in one object. In this paper, we used color reduction and cluster selection for equipment recognition. The system reduced the color in images by using k-means clustering and recognized the clusters as separate objects by predetermined thresholds. Compared with the previous method, the recognition accuracy was higher and the accuracy achieved was 70%.
机译:本研究提出了一种通过图像处理自动测量多个物体的方法,用于构建床制作技巧的自我训练的护理学员的护理学员的系统。在以前的一项研究中,我们构建了一种使用三个RGB-D(RGB颜色和深度)传感器来衡量和评估实习生性能的系统。我们以前的系统识别床垫等设备的问题,因为透明条件的颜色变化,传感器的自动色彩校正和一个物体的颜色变化。在本文中,我们使用了用于设备识别的颜色减少和聚类选择。通过使用K-Means群集,系统通过预定阈值将群集识别为单独对象的图像中的颜色。与先前的方法相比,识别精度较高,所以实现的精度为70%。

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