Formulation of a novel HRV classification model as a surrogate fraudulence detection schema
| Autor: | Tengku Ahmad Iskandar Tengku Alang, Tan Jia Hou, Yii Cheng Tay, Arief R. Harris, Leo Bodey, Muhamad Firdaus Mohd Rafi, Leong Kah Meng, Matthias Tiong Foh Thye, Sameen Ahmed Malik, Kelvin Ling Chia Hiik, Tan Tian Swee, Joyce Sia Sin Yin, Mohammed Rafiq Abdul-Kadir, Azli Yahya |
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| Rok vydání: | 2020 |
| Předmět: |
Scheme (programming language)
Computer science business.industry General Mathematics General Physics and Astronomy Pattern recognition General Chemistry General Biochemistry Genetics and Molecular Biology Schema (genetic algorithms) Lie detection Heart rate variability Artificial intelligence General Agricultural and Biological Sciences business computer computer.programming_language |
| Zdroj: | Malaysian Journal of Fundamental and Applied Sciences. 16:121-127 |
| ISSN: | 2289-599X 2289-5981 |
| Popis: | Lie detection has been studied since a few decades ago, usually for the purpose of producing a scheme to assist in the investigation of identifying the culprit from a list of suspects. Heart Rate Variability (HRV) may be used as a method in lie detection due to its versatility and suitability. However, since its analysis is not instantaneous, a new experiment is described in this paper to overcome the problem. Additionally, a preliminary HRV classification model is designed to further enhance the classification model which is able to distinguish the lie from the truth for up to 80%. |
| Databáze: | OpenAIRE |
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