Sensorimotor rhythm neurofeedback training relieves anxiety in healthy people

Liu, Shuang; Hao, Xinyu; Liu, Xiaoya; He, Yuchen; Zhang, Ludan; An, Xingwei; Song, Xizi; Ming, Dong

doi:10.1007/s11571-021-09732-8

Cited by 3 publications

(2 citation statements)

References 84 publications

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“…Previous research has shown that BFB treatment can benefit disorders such as epilepsy [8], migraine [9], stroke [10], chronic insomnia [11,12], anxiety [13], attention-deficit/hyperactivity disorder [14,15], autism spectrum disorder [16], and major depression [17]. As a BFB method, neurofeedback training allows individuals to independently adjust specific brain activities, thereby changing their cognitive functions [18]. BFB is based on the idea that autonomic responses may be conditioned by instrumentation and includes biological monitors and sensors such as electromyography (EMG), EEG, electrodermal activity, skin temperature, HR, HRV, and end-tidal carbon dioxide [19].…”

Section: Introductionmentioning

confidence: 99%

EEG Biofeedback Decreases Theta and Beta Power While Increasing Alpha Power in Insomniacs: An Open-Label Study

Wang,

Hou,

Zhan

et al. 2023

Brain Sciences

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Insomnia, often associated with anxiety and depression, is a prevalent sleep disorder. Biofeedback (BFB) treatment can help patients gain voluntary control over physiological events such as by utilizing electroencephalography (EEG) and electromyography (EMG) power. Previous studies have rarely predicted biofeedback efficacy by measuring the changes in relative EEG power; therefore, we investigated the clinical efficacy of biofeedback for insomnia and its potential neural mechanisms. We administered biofeedback to 82 patients with insomnia, of whom 68 completed 10 sessions and 14 completed 20 sessions. The average age of the participants was 49.38 ± 12.78 years, with 26 men and 56 women. Each biofeedback session consisted of 5 min of EMG and 30 min of EEG feedback, with 2 min of data recorded before and after the session. Sessions were conducted every other day, and four scale measures were taken before the first, fifth, and tenth sessions and after the twentieth session. After 20 sessions of biofeedback treatment, scores on the Pittsburgh Sleep Quality Index (PSQI) were significantly reduced compared with those before treatment (−5.5 ± 1.43,t = −3.85, p = 0.006), and scores on the Beck Depression Inventory (BDI-II) (−7.15 ± 2.43, t = −2.94, p = 0.012) and the State-Trait Anxiety Inventory (STAI) (STAI-S: −12.36 ± 3.40, t = −3.63, p = 0.003; and STAI-T: −9.86 ± 2.38, t = −4.41, p = 0.001) were significantly lower after treatment than before treatment. Beta and theta power were significantly reduced after treatment, compared with before treatment (F = 6.25, p = 0.014; and F = 11.91, p = 0.001). Alpha power was increased after treatment, compared with before treatment, but the difference was not prominently significant (p > 0.05). EMG activity was significantly decreased after treatment, compared with before treatment (F = 2.11, p = 0.015). Our findings suggest that BFB treatment based on alpha power and prefrontal EMG relieves insomnia as well as anxiety and depression and may be associated with increased alpha power, decreased beta and theta power, and decreased EMG power.

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Section: Introductionmentioning

confidence: 99%

EEG Biofeedback Decreases Theta and Beta Power While Increasing Alpha Power in Insomniacs: An Open-Label Study

Wang,

Hou,

Zhan

et al. 2023

Brain Sciences

View full text Add to dashboard Cite

show abstract

“…Previous researches have found that Biofeedback training bene ts the interventions of several disorders: such as epilepsy [9], migraine [10], stroke [11], chronic insomnia [12,13], anxiety [14], attention de cit/hyperactivity disorder (ADHD) [15,16], autism spectrum disorder [17], major depression [18]. Neurofeedback training allows individuals to independently adjust their speci c brain activity, thereby changing their corresponding cognitive function [19]. Biofeedback is based on the idea that autonomic responses may be conditioned by instrumentation, and includes biological monitors and sensors such as electromyography, electroencephalography, electrodermal activity, skin temperature, heart rate (HR) and heart rate variability (HRV), and end-tidal carbon dioxide biofeedback [20].…”

Section: Introductionmentioning

confidence: 99%

Observe the therapeutic effect of EEG biofeedback on 82 patients with insomnia

Wang

Hou

Wang

et al. 2023

Preprint

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Objective: Insomniais the most prevalent clinical sleep disorder and is usually accompanied by some affective symptoms. To some extent, traditional interventions for insomnia remain some shortcomings. Hence, exploring potential novel interventions for insomnia is of great clinical significance. Recently, the biofeedback therapy (i.e. the electroencephalography EEG and electromyography EMG feedback) has been regarded as a new method for the treatment of insomnia following medication and physical therapy, where EEG information is fed back to the subject for the purpose of self-regulation of EEG activity. We aimed to explore the clinical efficacy of biofeedback for insomnia and its potential mechanisms. Methods: We recruited 82 patients with insomnia from the insomnia clinic of Xuanwu Hospital in this research. The EEG and EMG biofeedback training were conducted for 30 minutes. The EEG data of two minutes were also recorded each before and after the training section. The intervention was performed once every other day and included 10 times treatments in total. The Becker Depression Scale(BDI), state anxiety (S-STAI) and trait anxiety (T-STAI) of Spielberger State-Trait Anxiety Inventory (STAI), and Pittsburgh Sleep Quality Index(PQRI) scales were administered three times before treatment and after 1 treatment session, respectively. Results: Results showed that the scores of the PQRI scale after 1 trial of biofeedback treatmentwere significantly lower than those before treatment (p < 0.001). Furthermore, the score of the PQRI following 10 trials of biofeedback treatments were significantly lower than values following 5 trials of treatments (p < 0.001). More specifically, patients experienced a significant reduction in insomnia, an easier transition to natural sleep, a shorter time to fall asleep, fewer awakenings during sleep, and a much better quality of sleep. In addition, the scores of the BDI, S-STAI, and T-STAI scales after the treatments were significantly lower than those before the treatments (p<0.001), indicating that the patient's anxiety and depression were relieved. For the physiological results, compared with the baseline level, the patient's prefrontal EMG decreased, EEG alpha waves increased, and EEG beta and theta waves decreased after the biofeedback therapy. Conclusion: Our findings suggest that Biofeedback therapy is effective to relieve insomnia symptoms for insomnia patients. The potential mechanism of the biofeedback therapy might be that the therapy relaxes the patients’ mind (reflected by the alpha wave) and muscles (reflected by EMG), and reduces alertness states (reflected by Beta wave), which finally promotes the deep sleep (reflected by the Theta wave).

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The effect of EEG biofeedback on patients with insomnia: an open- label study

huicong,

Hou,

Wang

et al. 2023

Preprint

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Insomnia is the most prevalent clinical sleep disorder and is usually accompanied by some affective symptoms. As traditional interventions for insomnia have certain limitations, novel interventions such as biofeedback therapy can be of great clinical significance. Here, we aimed to explore the clinical efficacy of biofeedback for insomnia and its potential mechanisms of action. We recruited 82 patients with insomnia from the insomnia clinic at the Xuanwu Hospital. Electroencephalography (EEG) and electromyography (EMG) biofeedback training was conducted for 30 minutes. EEG data of two minutes were also recorded each before and after training. Intervention was performed once every alternate day and included 10 biofeedback treatments session and measured three times before, after fifth, and after tenth biofeedback treatment session. Scores on the Pittsburgh Sleep Quality Index (PSQI) scale after one trial of biofeedback treatment were significantly lower than those before treatment (p < 0.001) and continued to lower after subsequent trials (p < 0.001). Specifically, patients experienced a significant reduction in insomnia, an easier transition to natural sleep, a shorter time to fall asleep, fewer awakenings during sleep, and a much better quality of sleep. Additionally, the scores on the Beck Depression Inventory Scale (BDI) and State-Trait Anxiety Scale (S-STAI, and T-STAI) after treatment were significantly lower than those before treatment (p < 0.001). Our findings suggest that biofeedback therapy is effective in relieving insomnia symptoms for insomnia patients and biofeedback therapy likely relaxes the patients’ minds (reflected by the alpha wave) and muscles (reflected by frontal EMG) and reduces alertness states (reflected by beta waves), which finally promotes deep sleep (reflected by the theta wave).

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Sensorimotor rhythm neurofeedback training relieves anxiety in healthy people

Cited by 3 publications

References 84 publications

EEG Biofeedback Decreases Theta and Beta Power While Increasing Alpha Power in Insomniacs: An Open-Label Study

EEG Biofeedback Decreases Theta and Beta Power While Increasing Alpha Power in Insomniacs: An Open-Label Study

Observe the therapeutic effect of EEG biofeedback on 82 patients with insomnia

The effect of EEG biofeedback on patients with insomnia: an open- label study

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