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基于摄像的简短身体性能电池测试和计时起立行走测试在癌症老年患者中的应用。

Camera-Based Short Physical Performance Battery and Timed Up and Go Assessment for Older Adults With Cancer.

出版信息

IEEE Trans Biomed Eng. 2023 Sep;70(9):2529-2539. doi: 10.1109/TBME.2023.3253061. Epub 2023 Aug 30.

Abstract

This paper presents an automatic camera-based device to monitor and evaluate the gait speed, standing balance, and 5 times sit-stand (5TSS) tests of the Short Physical Performance Battery (SPPB) and the Timed Up and Go (TUG) test. The proposed design measures and calculates the parameters of the SPPB tests automatically. The SPPB data can be used for physical performance assessment of older patients under cancer treatment. This stand-alone device has a Raspberry Pi (RPi) computer, three cameras, and two DC motors. The left and right cameras are used for gait speed tests. The center camera is used for standing balance, 5TSS, and TUG tests and for angle positioning of the camera platform toward the subject using DC motors by turning the camera left/right and tilting it up/down. The key algorithm for operating the proposed system is developed using Channel and Spatial Reliability Tracking in the cv2 module in Python. Graphical User Interfaces (GUIs) in the RPi are developed to run tests and adjust cameras, controlled remotely via smartphone and its Wi-Fi hotspot. We have tested the implemented camera setup prototype and extracted all SPPB and TUG parameters by conducting several experiments on a human subject population of 8 volunteers (male and female, light and dark complexions) in 69 test runs. The measured data and calculated outputs of the system consist of tests of gait speed (0.041 to 1.92 m/s with average accuracy of >95%), and standing balance, 5TSS, TUG, all with average time accuracy of >97%.

摘要

本文提出了一种基于摄像头的自动设备,用于监测和评估短体适能电池(SPPB)和计时起立行走(TUG)测试的步速、站立平衡和 5 次坐站(5TSS)测试。该设计自动测量和计算 SPPB 测试的参数。SPPB 数据可用于评估癌症治疗中老年患者的身体表现。该独立设备使用 Raspberry Pi(RPi)计算机、三个摄像头和两个直流电机。左右摄像头用于测试步速。中央摄像头用于站立平衡、5TSS 和 TUG 测试,以及通过左右转动摄像头和上下倾斜摄像头平台来使用直流电机对摄像头平台的角度进行定位。使用 Python 中的 cv2 模块中的通道和空间可靠性跟踪开发了用于操作该系统的关键算法。RPi 中的图形用户界面(GUI)用于运行测试和调整摄像头,可以通过智能手机及其 Wi-Fi 热点远程控制。我们已经测试了实施的摄像头设置原型,并通过对 8 名志愿者(男女,肤色浅和深)的 69 次测试运行中的人类受试者群体进行了多次实验,提取了所有 SPPB 和 TUG 参数。系统的测量数据和计算输出包括步速测试(0.041 至 1.92m/s,平均准确率>95%)、站立平衡、5TSS、TUG,所有测试的平均时间准确率均>97%。

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