Profiling of pornography addiction among children using EEG signals: A systematic literature review
Nowadays human behavior has been affected with the advent of new digital technologies. Due to the rampant use of the Internet by children, many have been addicted to pornography. This addiction has negatively affected the behaviors of children including increased impulsiveness, learning ability to...
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| Format: | Article |
| Language: | English |
| Published: |
2020
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| Online Access: | http://irep.iium.edu.my/97040/1/kang2020.pdf http://irep.iium.edu.my/97040/ https://www.journals.elsevier.com/computers-in-biology-and-medicine https://doi.org/10.1016/j.compbiomed.2020.103970 |
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| Summary: | Nowadays human behavior has been affected with the advent of new digital technologies. Due to the rampant
use of the Internet by children, many have been addicted to pornography. This addiction has negatively affected
the behaviors of children including increased impulsiveness, learning ability to attention, poor decision-making,
memory problems, and deficit in emotion regulation. The children with porn addiction can be identified by
parents and medical practitioners as third-party observers. This systematic literature review (SLR) is conducted
to increase the understanding of porn addiction using electroencephalogram (EEG) signals. We have searched
five different databases namely IEEE, ACM, Science Direct, Springer and National Center for Biotechnology
Information (NCBI) using addiction, porn, and EEG as keywords along with ‘OR ‘operation in between the expressions. We have selected 46 studies in this work by screening 815,554 papers from five databases. Our results
show that it is possible to identify children with porn addiction using EEG signals. |
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