Evaluation of electrocardiogram: numerical vs. image data for emotion recognition system

Sharifah Noor Masidayu Sayed Ismail, Nor Azlina Ab. Aziz, Siti Zainab Ibrahim1, Sophan Wahyudi Nawawi, Salem Alelyani, Mohamed Mohana, Lee Chia Chun6
September, 2021
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Abstract

The electrocardiogram (ECG) is a physiological signal used to diagnose and monitor cardiovascular disease, usually using 2- D ECG. Numerous studies have proven that ECG can be used to detect human emotions using 1-D ECG; however, ECG is typically captured as 2-D images rather than as 1-D data. There is still no consensus on the effect of the ECG input format on the accuracy of the emotion recognition system (ERS). The ERS using 2-D ECG is still inadequately studied. Therefore, this study compared ERS performance using 1-D and 2-D ECG data to investigate the effect of the ECG input format on the ERS.

Type
Preprint
Publication
In F1000 Research
Emotion recognition electrocardiogram numerical ECG image ECG DREAMER
Mohamed Mohana
Mohamed Mohana
Head of Artificial Intelligence | Certified AI Scientist (CAIS™) | Machine Learning Expert

Senior Artificial Intelligence Engineer and Certified AI Scientist (CAIS™) specializing in Computer Vision, Machine Learning, Large Language Models (LLMs), RAG systems, Vector Databases, and AI for Environment. Head of AI Unit at King Khalid University with expertise in developing AI solutions for real-world applications.