Taiwanese Researchers Develop EEG Model to Identify Internet Addiction

A research team from Taiwan has made significant strides in identifying Internet addiction through an innovative machine-learning model that analyzes electroencephalography (EEG) brain wave patterns. This model successfully distinguishes individuals with Internet addiction from healthy subjects with an impressive accuracy rate of 86 percent.

According to Huang Hsu-wen, an assistant investigator at the National Health Research Institutes and one of the study’s lead researchers, this accuracy surpasses that of traditional self-reported measures. The study, published in May 2023 in the journal Psychological Medicine, involved a sample size of 92 participants, including 42 diagnosed with Internet addiction and 50 healthy controls.

The researchers focused on the resting-state EEG functional connectivity of participants. They found that those with Internet addiction exhibited elevated levels of phase synchronization. Huang explained that these changes in brain activity could be attributed to disruptions in neural systems related to inhibition and reward pathways.

The early detection of these EEG pattern changes is particularly noteworthy, as they occur before the manifestation of addictive behaviors. This suggests that combining EEG testing with machine-learning classification models could serve as an efficient tool for identifying early risk signals. Such advancements could enable schools and medical institutions to intervene more effectively, addressing potential Internet addiction before it escalates.

Internet addiction is characterized by prolonged online engagement, an inability to limit internet use, and discomfort when disconnected from the internet. The implications of this research extend beyond academic interest; they raise awareness about the growing concern surrounding Internet addiction, which affects individuals across various demographics.

The research team included notable contributors such as Wu Shun-chi, a professor at National Tsing Hua University, and Huang Chih-mao, an associate professor in the Department of Psychology at the University of Hong Kong. Their collaborative efforts, along with contributions from various research institutions in Taiwan and abroad, underscore the collective commitment to understanding and addressing this pressing issue.

This groundbreaking model not only provides a scientific framework for identifying Internet addiction but also paves the way for future research aimed at developing targeted interventions. As technology continues to evolve, the need for effective strategies to combat Internet addiction becomes increasingly relevant.