Applied Psychophysiology and Biofeedback最新文献

Neurofeedback training is applied in the world of sports as a means to improve athletes' performance. Training sessions are usually organized on an individual basis, one at a time. Here we investigated if the training could also be organized in groups. Forty-one national-level football (soccer) players (26 females, 15 males) carried out training sessions simultaneously in groups of up to 13, using a wearable device with Bluetooth connection, during their regular training hours at the club. It was possible to obtain good EEG measurements using this setup, albeit with a somewhat higher data loss than usual in standard laboratory sessions. The brain's alpha activity was trained using music-based neurofeedback in a crossover design. A training session consisted of alternating periods of neurofeedback and execution of cognitive tasks. EEG alpha (8-12 Hz) activity was higher in the neurofeedback periods compared to the cognitive task periods, and the reverse was true for beta (13-30 Hz) activity. The training program resulted in an increase of 34% in alpha activity associated with the training, and improved the athletes' performance on task switching and mental rotation tasks. In addition, self-reported sleep duration, as well as scores on the Being in Shape questionnaire (Feeling of Control and Flow) also improved. This study shows that neurofeedback training is feasible in groups of athletes, which can stimulate its application in team sports.

Women who undergo cesarean delivery have reported experiencing mood distress related to the surgery and postoperative pain. Heart rate variability biofeedback (HRVB) training is known to have positive effects on mental health, but its effects on women undergoing cesarean delivery have not yet been determined. This study evaluated the effects of an HRVB training intervention on stress, anxiety, and depression in women undergoing cesarean delivery. We hypothesized that 10 sessions of HRVB training could cumulatively improve emotion regulation in participants. This study was designed as a double-blinded randomized controlled trial involving a total of 86 enrolled women who were then divided into two groups: intervention and control. During their hospitalization, the intervention group underwent HRVB training daily, while both groups received standard perinatal care. Heart rate variability (HRV) was assessed using root mean square of successive differences (RMSSD), standard deviation of normal-to-normal intervals (SDNN), high-frequency power (HF) and low-frequency power (LF). HRV parameters, stress, anxiety, and depression were evaluated at baseline and on the fifth day after childbirth. Intention-to-treat (ITT) analyses examined change over time between groups. Although no significant effects were found for the RMSSD and HF, a significant increase was observed in SDNN (F = 13.43, p = < 0.001, ƞ² = 0.14), and LF at post-assessment (F = 4.26, p = .04, ƞ² = 0.05) compared to the control group. Except for the depression variable, stress (F = 6.11, p = .02, ƞ² = 0.07) and anxiety (F = 8.78, p = .004, ƞ² = 0.10) significantly decreased compared to the control group on the fifth postpartum day. Furthermore, post-hoc analysis showed that HRVB was more effective in decreasing mild to severe depressive symptoms (F = 7.60, p = .001, ƞ² = 0.27). The intervention program successfully decreased self-perceived stress and anxiety in the postpartum period and relieved symptoms in more severely depressed participants. Our findings suggest that this program is suitable and beneficial for application in women during the early postpartum period following cesarean delivery.

To investigate the clinical efficacy of acupuncture combined with biofeedback electrical stimulation on female stress urinary incontinence. Ninety patients diagnosed in a hospital between January 2020 and January 2021 were randomly divided into three groups (A, B and C). Group A was treated with biofeedback electrical stimulation, 3 times a week for 30 min for 15 times. Group B used acupuncture treatment, including Guanyuan, Qihai, Zhongji, Zusanli, Sanyinjiao and Yinlingquan, once a day, Monday-Friday, 30 min each, for a total of 10 times. Group C was treated with acupuncture combined with biofeedback electrical stimulation. All three groups were combined with pelvic floor muscle training. Following treatment, the changes in class I and II muscle fibre strength, ICI-Q-SF score and urine leakage in the 1-hour pad test were compared. Prior to treatment, there was no significant difference in the general data of the three patient groups, as well as class I and II muscle fibre strength, ICI-Q-SF score and 1-hour urinary pad test (P > 0.05). Following treatment, class I and II muscle fibre strength in groups A and C improved compared with before, with statistical significance (P < 0.05); there was no significant difference in group B (P > 0.05). In the three groups, ICI-Q-SF scores and 1-hour urinary pad test results were lower compared with before (P < 0.05), with those in group C better than those in groups A and B (P < 0.05). The treatment efficiency of the three patient groups was 86.7%, 83.3% and 96.7%, respectively. Combined acupuncture and biofeedback electrical stimulation can improve pelvic floor muscle strength, urine leakage and quality of life, and can be superior to biofeedback and acupuncture treatment alone.

Various non-electrocardiogram (ECG) based methods are considered reliable sources of heart rate variability (HRV) measurement. However, the ultra-short recording of a femoral arterial waveform has never been validated against the gold-standard ECG-based 300s HRV and was the aim of this study.A validity study was conducted using a sample from the first follow-up of the longitudinal ADVANCE study UK. The participants were adult servicemen (n = 100); similar in age, rank, and deployment period (Afghanistan 2003-2014). The femoral arterial waveforms (14s) from the pulse wave velocity (PWV) assessment, and ECG (300s) were recorded at rest in the supine position using the Vicorder™ and Bittium Faros™ devices, respectively, in the same session. HRV analysis was performed using Kubios Premium. Resting heart rate (HR) and root mean square of successive differences (RMSSD) were reported. The Bland-Altman %plots were constructed to explore the PWV-ECG agreement in HRV measurement. A further exploratory analysis was conducted across methods and durations.The participants' mean age was 38.0 ± 5.3 years. Both PWV-derived HR (r = 0.85) and RMSSD (r_s=0.84) showed strong correlations with their 300s-ECG counterparts (p < 0.001). Mean HR was significantly higher with ECG than PWV (mean bias: -12.71 ± 7.73%, 95%CI: -14.25%, -11.18%). In contrast, the difference in RMSSD between the two methods was non-significant [mean bias: -2.90 ± 37.82% (95%CI: -10.40%, 4.60%)] indicating good agreement. An exploratory analysis of 14s ECG-vs-300s ECG measurement revealed strong agreement in both RMSSD and HR.The 14s PWV-derived RMSSD strongly agrees with the gold-standard (300s-ECG-based) RMSSD at rest. Conversely, HR appears method sensitive.

Effective emergency responses are crucial for preventing coal mine accidents and mitigating injuries. This paper aims to investigate the characteristics of emergency psychophysiological reactions to coal mine accidents and to explore the potential of key indicators for identifying emergency behavioral patterns. Initially, virtual reality technology facilitated a simulation experiment for emergency escape during coal mine accidents. Subsequently, the characteristics of emergency reactions were analyzed through correlation analysis, hypothesis testing, and analysis of variance. The significant changes in physiological indicators were then taken as input features and fed into the three classifiers of machine learning algorithms. These classifications ultimately led to the identification of behavioral patterns, including agility, defensiveness, panic, and rigidity, that individuals may exhibit during a coal mine accident emergency. The study results revealed an intricate relationship between the mental activities induced by accident stimuli and the resulting physiological changes and behavioral performances. During the virtual reality simulation of a coal mine accident, subjects were observed to experience significant physiological changes in electrodermal activity, heart rate variability, electromyogram, respiration, and skin temperature. The random forest classification model, based on SCR + RANGE + IBI + SDNN + LF/HF, outperformed all other models, achieving accuracies of up to 92%. These findings hold promising implications for early warning systems targeting abnormal psychophysiological and behavioral reactions to emergency accidents, potentially serving as a life-saving measure in perilous situations and fostering the sustainable growth of the coal mining industry.

Heart rate variability biofeedback (HRVBF) is a promising anxiety-reducing intervention that increases vagally-mediated heart rate variability (vmHRV) through slow-paced breathing and feedback of heart rhythm. Several studies have reported the anxiety-reducing effects of HRVBF; however, some studies have reported such training as ineffective. Furthermore, the effects of training and underlying brain activity changes remain unclear. This study examined the anxiety-reducing effects of HRVBF training and related brain activity changes by randomly assigning participants, employing an active control group, and measuring anxiety-related attentional bias using the emotional Stroop task and electroencephalography (EEG). Fifty-five healthy students with anxiety were randomly assigned to the HRVBF or control groups, and 21 in the HRVBF group and 19 in the control group were included in the analysis. Both groups performed 10 training sessions of 20 min each within 3 weeks. They were assessed using resting vmHRV, event-related potential (ERP), time-frequency EEG, attentional bias, and the State-Trait Anxiety Inventory-JYZ (STAI-JYZ) before and after training. The results demonstrated increased resting vmHRV in the HRVBF group compared to the control group after training. However, no differences were observed in ERP, time-frequency EEG, attentional bias, and STAI-JYZ. Participants with higher pre-training resting vmHRV achieved higher heart rhythm coherence in HRVBF training and had reduced attentional bias. This study suggests that individuals with higher resting vmHRV are more likely to be proficient in HRVBF training and benefit from its anxiety-reducing effects. The findings contribute to participant selection to benefit from HRVBF training and modification of the training protocols for non-responders.Clinical trial registrationOrganization: University Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR), JapanRegistration number: UMIN000047096Registration date: March 6, 2022.

This review describes the historical developement and rationale of clinically relevant research on neurophysiological "mind reading" paradims: Brain- Computer-Interfaces, detection of deception, brain stimulation and neurofeedback and the clinical applications in drug resistant epilepsy, chronic stroke, and communication with paralyzed locked-in persons. The emphasis lies on completely locked-in patients with amyotrophic lateral sclerosis using non-invasive and invasive brain computer interfaces and neurofeedback to restore verbal communication with the social environment. In the second part of the article we argue that success and failure of neurophysiological "mind reading" paradigms may be explained with a motor theory of thinking and emotion in combination with learning theory. The ethical implications of brain computer interface and neurofeedback approaches, particularly for severe chronic paralysis and loss of communication diseases and decisions on hastened death and euthanasia are discussed.

The frequently reported high theta/beta ratio (TBR) in the electroencephalograms (EEGs) of children with attention-deficit/hyperactivity disorder (ADHD) has been suggested to include at least two distinct neurophysiological subgroups, a subgroup with high TBR and one with slow alpha peak frequency, overlapping the theta range. We combined three large ADHD cohorts recorded under standardized procedures and used a meta-analytical approach to leverage the large sample size (N = 417; age range: 6-18 years), classify these EEG subtypes and investigate their behavioral correlates to clarify their brain-behavior relationships. To control for the fact that slow alpha might contribute to theta power, three distinct EEG subgroups (non-slow-alpha TBR (NSAT) subgroup, slow alpha peak frequency (SAF) subgroup, not applicable (NA) subgroup) were determined, based on a halfway cut-off in age- and sex-normalized theta and alpha, informed by previous literature. For the meta-analysis, Cohen's d was calculated to assess the differences between EEG subgroups for baseline effects, using means and standard deviations of baseline inattention and hyperactivity-impulsivity scores. Non-significant, small Grand Mean effect sizes (-0.212 < d < 0.218) were obtained when comparing baseline behavioral scores between the EEG subgroups. This study could not confirm any association of EEG subtype with behavioral traits. This confirms previous findings suggesting that TBR has no diagnostic value for ADHD. TBR could, however, serve as an aid to stratify patients between neurofeedback protocols based on baseline TBR. A free online tool was made available for clinicians to calculate age- and sex-corrected TBR decile scores (Brainmarker-IV) for stratification of neurofeedback protocols.