Radio-frequency (RF) sensing for deep awareness of human physical status - part II

The application of radar signal processing techniques, specifically with ultra-wideband (UWB) radar is investigated in this study. The intention is to non-invasively detect and classify human emotions using UWB radar. Features related to breathing and heart rate are extracted from the signal. Mac...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Kng, Yew Chian
مؤلفون آخرون: Luo Jun
التنسيق: Final Year Project
اللغة:English
منشور في: Nanyang Technological University 2024
الموضوعات:
الوصول للمادة أونلاين:https://hdl.handle.net/10356/175289
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الوصف
الملخص:The application of radar signal processing techniques, specifically with ultra-wideband (UWB) radar is investigated in this study. The intention is to non-invasively detect and classify human emotions using UWB radar. Features related to breathing and heart rate are extracted from the signal. Machine learning techniques are then applied to classify between emotions defined by the arousal-valence theory. The dataset was created by exposing subjects to different videos meant to incite different responses while being monitored by a UWB radar.