A systematic review of emotion recognition using cardio-based signals

Sharifah Noor Masidayu Sayed Ismail, Nor Azlina Nor, Siti Zainab Ibrahim, Mohd Saberi Mohamad

Research output: Contribution to journalReview articlepeer-review


There is a growing demand for emotion recognition systems (ERS) to be adopted in everyday life from various fields, particularly automotive, education, and social security. Recently, the use of cardio-based physiological signals, electrocardiogram (ECG), and photoplethysmogram (PPG) in ERS has yielded promising results. Furthermore, the development of wearable devices equipped with cardio-based physiological sensors has significantly aided towards the adoption of ERS in daily life. This paper systematically reviews emotion recognition using cardio-based physiological signals, encompassing emotion models, emotion elicitation methods, and ERS development methods, emphasizing feature extraction, feature selection methods, feature dimension reduction methods, and classifiers. A summary and comparison of recent studies are presented to highlight existing studies’ gaps and suggest future research for better ERS especially using cardio-based signals.

Original languageEnglish
Pages (from-to)156-183
Number of pages28
JournalICT Express
Issue number1
Publication statusPublished - Feb 2024


  • Artificial intelligence
  • Electrocardiogram
  • Emotion recognition system
  • Features extraction
  • Machine learning
  • Photoplethysmogram

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence


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