一种融合物联网应用和便携式脑电图的偏头痛检测和预防模型

Akhila Jagarlapudi, Amey Patil, D. Rathod
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引用次数: 1

摘要

随着使用物联网的应用程序的逐步发展,这是探索新功能和了解医疗保健困难的绝佳机会。由于这些进步,我们可以加速从神经科学和临床研究到现实生活和实践模块的过渡,以检测和体验偏头痛。本文将回顾和推断应用的重要性,如虚拟现实耳机,便携式脑电图传感器和使用智能手机检测偏头痛的新应用。在此基础上,我们提出的方法是这三个想法的完美结合,将导致最强大的医疗保健解决方案。提出的模型有助于确定偏头痛的主要诱因,并建议快速补救措施,以尽早处理手头的情况。不仅如此,该模型还可以在预测基础上预测任何可能的偏头痛发作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Proposed Model on Merging IoT Applications and Portable EEGs for Migraine Detection and Prevention
As the progressive development unfolds the utilization of applications using Internet of Things, this is a great opportunity to explore newer capabilities and understand the difficulties in healthcare. Because of these advancements, we can accelerate the transition from neuroscience and clinical research to real-life and hands-on modules to detect and experience migraine. This paper will review and extrapolate the importance of applications such as Virtual Reality Headsets, portable EEG sensors and novel applications available to detect migraine using smartphones. Post this groundwork, the approach we propose comprises a perfect blend of these three ideas that would lead to the most robust healthcare solutions. The proposed model helps identify the key migraine triggers and suggest quick remedies to deal with the situation at hand at the earliest. Not only this, the model will work on a predictive basis to foresee any migraine attacks possible.
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