School of Electronic Engineering, Xidian University, Xi'an 710071, China.
Artificial Intelligence Engineering Department, Near East University, 99138 Nicosia, Mersin 10, Turkey.
Sensors (Basel). 2020 Feb 10;20(3):931. doi: 10.3390/s20030931.
Internet of multimedia things (IoMT) driving innovative product development in health care applications. IoMT requires delay-sensitive and higher bandwidth devices. Ultra-wideband (UWB) technology is a promising solution to improve communication between devices, tracking and monitoring of patients. In the future, this technology has the capability to expand the IoMT world with new capabilities and more devices can be integrated. At the present time, some people face different types of physiological problems because of the damage in different areas of the central nervous system. Thus, they lose their balance coordination. One of these types of coordination problems is named Ataxia, in which patients are unable to control their body movements. This kind of coordination disorder needs a proper supervision system for the caretaker. Previous Ataxia assessment methods are cumbersome and cannot handle regular monitoring and tracking of patients. One of the most challenging tasks is to detect different walking abnormalities of Ataxia patients. In our paper, we present a technique for monitoring and tracking of a patient with the help of UWB technology. This method expands the real-time location systems (RTLS) in the indoor environment by placing wearable receiving tags on the body of Ataxia patients. The location and four different walking movement data are collected by UWB transceiver for the classification and prediction in the two-dimensional path. For accurate classification, we use a support vector machine (SVM) algorithm to clarify the movement variations. Our proposed examined result successfully achieved and the accuracy is above 95%.
物联网(IoT)推动医疗应用中的创新产品开发。IoT 需要延迟敏感和更高带宽的设备。超宽带(UWB)技术是改善设备之间通信、跟踪和监测患者的一种有前途的解决方案。在未来,这项技术有能力通过新的功能扩展 IoT 世界,更多的设备可以集成。目前,由于中枢神经系统不同区域的损伤,有些人面临着不同类型的生理问题。因此,他们失去了平衡协调能力。这些协调问题之一是称为共济失调,患者无法控制自己的身体运动。这种协调障碍需要一个适当的监督系统。之前的共济失调评估方法繁琐,无法进行定期监测和跟踪患者。最具挑战性的任务之一是检测共济失调患者的不同异常步态。在本文中,我们提出了一种利用 UWB 技术对患者进行监测和跟踪的技术。该方法通过在共济失调患者的身体上放置可穿戴接收标签,扩展了室内环境中的实时定位系统(RTLS)。通过 UWB 收发器收集位置和四个不同的步行运动数据,用于二维路径中的分类和预测。为了进行准确的分类,我们使用支持向量机(SVM)算法来澄清运动变化。我们提出的检查结果成功实现,准确率超过 95%。