Sugiyama Naoki, Kai Yoshihiro, Koda Hitoshi, Morihara Toru, Kida Noriyuki
Department of Advanced Fibro-Science, Kyoto Institute of Technology, Hashikami-cho, Matsugasaki, Sakyo-ku, Kyoto 606-8585, Japan.
Department of Physical Therapy, Faculty of Health Sciences, Kyoto Tachibana University, 34 Yamada-cho, Oyake, Yamashina-ku, Kyoto 607-8175, Japan.
Geriatrics (Basel). 2024 Mar 22;9(2):40. doi: 10.3390/geriatrics9020040.
Postural assessment is one of the indicators of health status in older adults. Since the number of older adults is on the rise, it is essential to assess simpler methods and automated ones in the future. Therefore, we focused on a visual method (imaging method). The purpose of this study is to determine the degree of agreement between the imaging method and the palpation and visual methods (clinical method). In addition, the influence of differences in the information content of the sagittal plane images on the assessment was also investigated. In this experiment, 28 sagittal photographs of older adults whose posture had already been assessed using the clinical method were used. Furthermore, based on these photographs, 28 gray and silhouette images (G and S images) were generated, respectively. The G and S images were assessed by 28 physical therapists (PTs) using the imaging method. The assessment was based on the Kendall classification, with one of four categories selected for each image: ideal, kyphosis lordosis, sway back, and flat back. Cross-tabulation matrices of the assessments using the clinical method and imaging method were created. In this table, four categories and two categories of ideal and non-ideal (KL, SB, and FB) were created. The agreement was evaluated using the prevalence-adjusted bias-adjusted kappa (PABAK). In addition, sensitivity and specificity were calculated to confirm the reliability. When comparing the clinical and imaging methods in the four posture categories, the PABAK values were -0.14 and -0.29 for the S and G images, respectively. In the case of the two categories, the PABAK values were 0.57 and 0.5 for the S and G images, respectively. The sensitivity and specificity were 86% and 57% for the S images and 76% and 71% for the G images, respectively. The four categories show that the imaging method is difficult to assess regardless of the image processing. However, in the case of the two categories, the same assessment of the clinical method applied to the imaging method for both the S and G images. Therefore, no differences in image processing were observed, suggesting that PTs can identify posture using the visual method.
姿势评估是老年人健康状况的指标之一。由于老年人数量不断增加，未来评估更简单和自动化的方法至关重要。因此，我们专注于一种视觉方法（成像方法）。本研究的目的是确定成像方法与触诊和视觉方法（临床方法）之间的一致性程度。此外，还研究了矢状面图像信息内容差异对评估的影响。在本实验中，使用了28张已用临床方法评估过姿势的老年人矢状面照片。此外，基于这些照片分别生成了28张灰度和轮廓图像（G图像和S图像）。28名物理治疗师（PTs）使用成像方法对G图像和S图像进行评估。评估基于肯德尔分类法，为每张图像从四个类别中选择一个：理想、驼背前凸、 sway back和扁平背。创建了使用临床方法和成像方法进行评估的交叉列表矩阵。在该表中，创建了四个类别以及理想和非理想（驼背前凸、 sway back和扁平背）两个类别。使用患病率调整偏差调整kappa（PABAK）评估一致性。此外，计算敏感性和特异性以确认可靠性。在四个姿势类别中比较临床方法和成像方法时，S图像和G图像的PABAK值分别为-0.14和-0.29。在两个类别中，S图像和G图像的PABAK值分别为0.57和0.5。S图像的敏感性和特异性分别为86%和57%，G图像的敏感性和特异性分别为76%和71%。四个类别表明，无论图像处理如何，成像方法都难以评估。然而，在两个类别中，临床方法对S图像和G图像应用于成像方法时的评估相同。因此，未观察到图像处理方面的差异，这表明物理治疗师可以使用视觉方法识别姿势。
