Department of Computer Science and Engineering, National Institute of Technology, Srinagar, India.
J Healthc Eng. 2023 Feb 13;2023:1066547. doi: 10.1155/2023/1066547. eCollection 2023.
The Internet of Things (IoT) has demonstrated over the past few decades to be a powerful tool for connecting various medical equipment with in-built sensors and healthcare professionals to deliver superior health services that also reach remote areas. In addition to reducing healthcare costs, increasing access to clinical services, and enhancing operational effectiveness in the healthcare industry, it has also enhanced patient health safety. Recent research has focused on using EEG to assist and comprehend brain changes in rehabilitation facilities. These technologies can spot fluctuations in EEG constraints during treatment, which could result in more effective therapy and better functional outcomes. As a result, we have tried to use an IoT-based system for real-time monitoring of the constraints. Another unknown patient who is suffering from acute ischemic stroke may experience stroke-in-evolution or an early worsening of neurological symptoms, which is frequently associated with poor clinical outcomes. Because of this, managing an acute stroke requires early detection of these indications. The present investigation work will act as a standard reference for academic researchers, medical professionals, and everyone else involved in the use of IoMT. This study aims to anticipate strokes sooner and prevent their consequences by early intervention using an Internet of Things (IoT)-based system. Also, this study proposes usage of wearable equipment that can monitor and analyze brain signals for improved treatment and the prevention of stroke-related complications.
物联网（IoT）在过去几十年中已经证明是连接内置传感器和医疗保健专业人员的各种医疗设备的强大工具，可提供优质的医疗服务，还可覆盖偏远地区。除了降低医疗成本、增加获得临床服务的机会以及提高医疗行业的运营效率外，它还增强了患者的健康安全性。最近的研究重点是使用脑电图（EEG）来帮助和理解康复设施中的大脑变化。这些技术可以发现治疗过程中 EEG 限制的波动，从而使治疗更加有效，功能结果更好。因此，我们尝试使用基于物联网的系统进行实时监测限制。另一位患有急性缺血性中风的未知患者可能会经历中风进展或神经症状的早期恶化，这通常与不良的临床结果相关。因此，管理急性中风需要早期发现这些迹象。本研究工作将作为学术研究人员、医疗专业人员以及其他参与 IoMT 使用的人员的标准参考。本研究旨在通过使用基于物联网（IoT）的系统进行早期干预，更早地预测中风并预防其后果。此外，本研究还提出使用可监测和分析大脑信号的可穿戴设备，以改善治疗和预防中风相关并发症。
