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<p>The life of human beings gets unnecessarily troubled by fear of world war or some natural disaster like Covid-19 or earthquakes. Such disasters put huge consequences on mankind in the form of cognitive load, that may result in various psychiatric disorders. This research paper explores one of such unpleasant emotional states in the human brain that leads to bad eating habits. The eating-related disorders (ED) are a key originator of life-threatening obesity and depressive psychosis. Hence, identification of such neurological conditions may eliminate the severity of its repercussion with its timely diagnosis. The presented deep learning framework with convoluted layers of long short-term memory networks results in 93.75% accuracy, which confirms its effectiveness over the existing methods.</p>

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TFEQ-driven analysis of BED using spatial and temporal features of multichannel brainwaves

  • 期刊论文

  • 发表日期：

    2025年11月21日

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  • Shipra Swati,
  • Mukesh Kumar,
  • M. N. Hoda,
  • R. K. Mishra

摘要

The life of human beings gets unnecessarily troubled by fear of world war or some natural disaster like Covid-19 or earthquakes. Such disasters put huge consequences on mankind in the form of cognitive load, that may result in various psychiatric disorders. This research paper explores one of such unpleasant emotional states in the human brain that leads to bad eating habits. The eating-related disorders (ED) are a key originator of life-threatening obesity and depressive psychosis. Hence, identification of such neurological conditions may eliminate the severity of its repercussion with its timely diagnosis. The presented deep learning framework with convoluted layers of long short-term memory networks results in 93.75% accuracy, which confirms its effectiveness over the existing methods.