Heart rate variability biofeedback increased alpha and beta1 EEG activity in adolescents with minimal or pronounced Internet addiction risk, while those with stable addiction showed least reactivity.
Cross-Sectional (n=100)
Does a short-term heart rate variability biofeedback session alter EEG and HRV parameters in adolescents with varying risks of Internet addiction?
Adolescents with a stable pattern of Internet addiction exhibit blunted neurophysiologic reactivity during heart rate variability biofeedback compared to those with lower addiction risks.
The aim of this study was to determine electroencephalogram (EEG) in a session of heart rate variability biofeedback (HRV BF) in adolescents with different Internet addiction (IA) risks. In total, 100 healthy adolescents aged 16–17 years with minimal risk of IA (Group I, 35%), pronounced risk of IA (Group II, 51%), and stable pattern of IA (Group III, 14%) using the Chen Internet Addiction Scale were examined. HRV and EEG parameters were determined at baseline (5 min), and then during the short-term HRV BF session (5 min), in order to increase the total power (TP, ms2) of the HRV spectrum. Against the background of an increase in the TP and a decrease in sympathetic activity, an increase in alpha EEG was revealed, especially in Groups I and II. The greatest increase in the power of beta1-activity of EEG in the frontal, central, and temporal brain regionswas found in Groups I and II. In adolescents with a pronounced risk of IA, HRV BF is accompanied by a severe activation of the brain systems, while in persons with a stable type of IA, the least brain reactivity is shown, especially in the beta1 EEG band.
Демин et al. (Sun,) conducted a cross-sectional in Internet addiction (n=100). Heart rate variability biofeedback (HRV BF) vs. Baseline and between different Internet addiction risk groups was evaluated on Electroencephalogram (EEG) and HRV parameters. Heart rate variability biofeedback increased alpha and beta1 EEG activity in adolescents with minimal or pronounced Internet addiction risk, while those with stable addiction showed least reactivity.
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