Test-retest reliability of a single-channel, wireless EEG system

A scoping review on the use of consumer-grade EEG devices for research

BACKGROUND

Commercial electroencephalography (EEG) devices have become increasingly available over the last decade. These devices have been used in a wide variety of fields ranging from engineering to cognitive neuroscience.

PURPOSE

The aim of this study was to chart peer-review articles that used consumer-grade EEG devices to collect neural data. We provide an overview of the research conducted with these relatively more affordable and user-friendly devices. We also inform future research by exploring the current and potential scope of consumer-grade EEG.

METHODS

We followed a five-stage methodological framework for a scoping review that included a systematic search using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines. We searched the following online databases: PsycINFO, MEDLINE, Embase, Web of Science, and IEEE Xplore. We charted study data according to application (BCI, experimental research, validation, signal processing, and clinical) and location of use as indexed by the first author's country.

RESULTS

We identified 916 studies that used data recorded with consumer-grade EEG: 531 were reported in journal articles and 385 in conference papers. Emotiv devices were used most, followed by the NeuroSky MindWave, OpenBCI, interaXon Muse, and MyndPlay Mindband. The most common usage was for brain-computer interfaces, followed by experimental research, signal processing, validation, and clinical purposes.

CONCLUSIONS

Consumer-grade EEG is a useful tool for neuroscientific research and will likely continue to be used well into the future. Our study provides a comprehensive review of their application, as well as future directions for researchers who plan to use these devices.

The effects of distraction on younger drivers: A neurophysiological perspective

Distracted driving remains a significant cause of traffic accidents globally, including in Australia. However, many younger drivers still admit to using a phone while driving. A simulated driving study investigated the neurophysiological effects of visual, auditory, and higher-order cognitive (i.e., requiring the use of executive functions) distraction on young drivers. In total, 24 young adults aged 18-25 years completed four 8 min simulated driving sessions while concurrently engaging in various distractor tasks. Neurophysiological arousal was measured via EEG. Additionally, subjective workload and objective driving performance were assessed. Frontal beta and gamma power exhibited their highest levels during tasks involving higher-order cognitive and visual demands. The higher-order cognitive condition was rated as the most mentally demanding. In comparison, the visual condition had the most significant impact on both the standard deviation of speed and standard deviation of lateral positioning. This study has significant implications for all road users, particularly those aged 18-25 years, and it reinforces the importance of not using a phone while driving.

Resting-state prefrontal EEG biomarker in correlation with postoperative delirium in elderly patients

Postoperative delirium (POD) is associated with adverse outcomes in elderly patients after surgery. Electroencephalography (EEG) can be used to develop a potential biomarker for degenerative cerebral dysfunctions, including mild cognitive impairment and dementia. This study aimed to explore the relationship between preoperative EEG and POD. We included 257 patients aged >70 years who underwent spinal surgery. We measured the median dominant frequency (MDF), which is a resting-state EEG biomarker involving intrinsic alpha oscillations that reflect an idle cortical state, from the prefrontal regions. Additionally, the mini-mental state examination and Montreal cognitive assessment (MoCA) were performed before surgery as well as 5 days after surgery. For long-term cognitive function follow up, the telephone interview for cognitive status™ (TICS) was performed 1 month and 1 year after surgery. Fifty-two (20.2%) patients were diagnosed with POD. A multivariable logistic regression analysis that included age, MoCA score, Charlson comorbidity index score, Mini Nutritional Assessment, and the MDF as variables revealed that the MDF had a significant odds ratio of 0.48 (95% confidence interval 0.27-0.85). Among the patients with POD, the postoperative neurocognitive disorders could last up to 1 year. Low MDF on preoperative EEG was associated with POD in elderly patients undergoing surgery. EEG could be a novel potential tool for identifying patients at a high risk of POD.

Wireless EEG: A survey of systems and studies

The popular brain monitoring method of electroencephalography (EEG) has seen a surge in commercial attention in recent years, focusing mostly on hardware miniaturization. This has led to a varied landscape of portable EEG devices with wireless capability, allowing them to be used by relatively unconstrained users in real-life conditions outside of the laboratory. The wide availability and relative affordability of these devices provide a low entry threshold for newcomers to the field of EEG research. The large device variety and the at times opaque communication from their manufacturers, however, can make it difficult to obtain an overview of this hardware landscape. Similarly, given the breadth of existing (wireless) EEG knowledge and research, it can be challenging to get started with novel ideas. Therefore, this paper first provides a list of 48 wireless EEG devices along with a number of important-sometimes difficult-to-obtain-features and characteristics to enable their side-by-side comparison, along with a brief introduction to each of these aspects and how they may influence one's decision. Secondly, we have surveyed previous literature and focused on 110 high-impact journal publications making use of wireless EEG, which we categorized by application and analyzed for device used, number of channels, sample size, and participant mobility. Together, these provide a basis for informed decision making with respect to hardware and experimental precedents when considering new, wireless EEG devices and research. At the same time, this paper provides background material and commentary about pitfalls and caveats regarding this increasingly accessible line of research.

Building a Low-Cost Wireless Biofeedback Solution: Applying Design Science Research Methodology

In recent years, affective computing has emerged as a promising approach to studying user experience, replacing subjective methods that rely on participants' self-evaluation. Affective computing uses biometrics to recognize people's emotional states as they interact with a product. However, the cost of medical-grade biofeedback systems is prohibitive for researchers with limited budgets. An alternative solution is to use consumer-grade devices, which are more affordable. However, these devices require proprietary software to collect data, complicating data processing, synchronization, and integration. Additionally, researchers need multiple computers to control the biofeedback system, increasing equipment costs and complexity. To address these challenges, we developed a low-cost biofeedback platform using inexpensive hardware and open-source libraries. Our software can serve as a system development kit for future studies. We conducted a simple experiment with one participant to validate the platform's effectiveness, using one baseline and two tasks that elicited distinct responses. Our low-cost biofeedback platform provides a reference architecture for researchers with limited budgets who wish to incorporate biometrics into their studies. This platform can be used to develop affective computing models in various domains, including ergonomics, human factors engineering, user experience, human behavioral studies, and human-robot interaction.

Circulant Singular Spectrum Analysis and Discrete Wavelet Transform for Automated Removal of EOG Artifacts from EEG Signals

Background: Portable electroencephalogram (EEG) systems are often used in health care applications to record brain signals because their ease of use. An electrooculogram (EOG) is a common, low frequency, high amplitude artifact of the eye blink signal that might confuse disease diagnosis. As a result, artifact removal approaches in single EEG portable devices are in high demand. Materials: Dataset 2a from the BCI Competition IV was employed. It contains the EEG data from nine subjects. To determine the EOG effect, each session starts with 5 min of EEG data. This recording lasted for two minutes with the eyes open, one minute with the eyes closed, and one minute with eye movements. Methodology: This article presents the automated removal of EOG artifacts from EEG signals. Circulant Singular Spectrum Analysis (CiSSA) was used to decompose the EOG contaminated EEG signals into intrinsic mode functions (IMFs). Next, we identified the artifact signal components using kurtosis and energy values and removed them using 4-level discrete wavelet transform (DWT). Results: The proposed approach was evaluated on synthetic and real EEG data and found to be effective in eliminating EOG artifacts while maintaining low frequency EEG information. CiSSA-DWT achieved the best signal to artifact ratio (SAR), mean absolute error (MAE), relative root mean square error (RRMSE), and correlation coefficient (CC) of 1.4525, 0.0801, 18.274, and 0.9883, respectively. Comparison: The developed technique outperforms existing artifact suppression techniques according to performance measures. Conclusions: This advancement is important for brain science and can contribute as an initial pre-processing step for research related to EEG signals.

What a Single Electroencephalographic (EEG) Channel Can Tell us About Alzheimer's Disease Patients With Mild Cognitive Impairment

Abnormalities in cortical sources of resting-state eyes closed electroencephalographic (rsEEG) rhythms recorded by hospital settings (10-20 montage) with 19 scalp electrodes characterized Alzheimer's disease (AD) from preclinical to dementia stages. An intriguing rsEEG application is the monitoring and evaluation of AD progression in large populations with few electrodes in low-cost devices. Here we evaluated whether the above-mentioned abnormalities can be observed from fewer scalp electrodes in patients with mild cognitive impairment due to AD (ADMCI). Clinical and rsEEG data acquired in hospital settings (10-20 montage) from 75 ADMCI participants and 70 age-, education-, and sex-matched normal elderly controls (Nold) were available in an Italian-Turkish archive (PDWAVES Consortium; www.pdwaves.eu). Standard spectral fast fourier transform (FFT) analysis of rsEEG data for individual delta, theta, and alpha frequency bands was computed from 6 monopolar scalp electrodes to derive bipolar C3-P3, C4-P4, P3-O1, and P4-O2 markers. The ADMCI group showed increased delta and decreased alpha power density at the C3-P3, C4-P4, P3-O1, and P4-O2 bipolar channels compared to the Nold group. Increased theta power density for ADMCI patients was observed only at the C3-P3 bipolar channel. Best classification accuracy between the ADMCI and Nold individuals reached 81% (area under the receiver operating characteristic curve) using Alpha2/Theta power density computed at the C3-P3 bipolar channel. Standard rsEEG power density computed from six posterior bipolar channels characterized ADMCI status. These results may pave the way toward diffuse clinical applications in health monitoring of dementia using low-cost EEG systems with a strict number of electrodes in lower- and middle-income countries.

Prefrontal EEG slowing, synchronization, and ERP peak latency in association with predementia stages of Alzheimer's disease

Background

Early screening of elderly individuals who are at risk of dementia allows timely medical interventions to prevent disease progression. The portable and low-cost electroencephalography (EEG) technique has the potential to serve it.

Objective

We examined prefrontal EEG and event-related potential (ERP) variables in association with the predementia stages of Alzheimer's disease (AD).

Methods

One hundred elderly individuals were recruited from the GARD cohort. The participants were classified into four groups according to their amyloid beta deposition (A+ or A-) and neurodegeneration status (N+ or N-): cognitively normal (CN; A-N-, n = 27), asymptomatic AD (aAD; A + N-, n = 15), mild cognitive impairment (MCI) with AD pathology (pAD; A+N+, n = 16), and MCI with non-AD pathology (MCI(-); A-N+, n = 42). Prefrontal resting-state eyes-closed EEG measurements were recorded for five minutes and auditory ERP measurements were recorded for 8 min. Three variables of median frequency (MDF), spectrum triangular index (STI), and positive-peak latency (PPL) were employed to reflect EEG slowing, temporal synchrony, and ERP latency, respectively.

Results

Decreasing prefrontal MDF and increasing PPL were observed in the MCI with AD pathology. Interestingly, after controlling for age, sex, and education, we found a significant negative association between MDF and the aAD and pAD stages with an odds ratio (OR) of 0.58. Similarly, PPL exhibited a significant positive association with these AD stages with an OR of 2.36. Additionally, compared with the MCI(-) group, significant negative associations were demonstrated by the aAD group with STI and those in the pAD group with MDF with ORs of 0.30 and 0.42, respectively.

Conclusion

Slow intrinsic EEG oscillation is associated with MCI due to AD, and a delayed ERP peak latency is likely associated with general cognitive impairment. MCI individuals without AD pathology exhibited better cortical temporal synchronization and faster EEG oscillations than those with aAD or pAD.

Significance

The EEG/ERP variables obtained from prefrontal EEG techniques are associated with early cognitive impairment due to AD and non-AD pathology. This result suggests that prefrontal EEG/ERP metrics may serve as useful indicators to screen elderly individuals' early stages on the AD continuum as well as overall cognitive impairment.

Comparison of the usability of an automatic sleep staging program via portable 1-channel electroencephalograph and manual sleep staging with traditional polysomnography

Automatic algorithms are a proposed alternative to manual assessment of polysomnography data for analyzing sleep structure; however, none are acceptably accurate for clinical use. We investigated the feasibility of an automated sleep stage scoring system called Sleep Scope, which is intended for use with portable 1-channel electroencephalograph, and compared it with the traditional polysomnography scoring method. Twenty-six outpatients and fourteen healthy volunteers underwent Sleep Scope and polysomnography assessments simultaneously. Polysomnography records were manually scored by three sleep experts. Sleep Scope records were scored using a dedicated auto-staging algorithm. Sleep parameters, including total sleep time, sleep latency, wake after sleep onset, and sleep efficiency, were calculated. The epoch-by-epoch pairwise concordance based on the classification of sleep into five stages (i.e., wake, rapid eye movement, N1, N2, and N3) was also evaluated after validating homogeneity and bias between Sleep Scope and polysomnography. Compared with polysomnography, Sleep Scope seemed to overestimate sleep latency by approximately 3 min, but there was no consistent tendency in bias in other sleep parameters. The Κ values ranged from 0.66 to 0.75 for experts' inter-rater polysomnography scores and from 0.62 to 0.67 for Sleep Scope versus polysomnography scores, which indicated sufficient agreement in the determination of sleep stages based on the Landis and Koch criteria. We observed sufficient concordance between Sleep Scope and polysomnography despite lower concordance in sleep disorder patients. Thus, this auto-staging system might serve as a novel clinical tool for reducing the time and expenses required of medical staff and patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41105-022-00421-5.

Developments in scalable strategies for detecting early markers of cognitive decline

Effective strategies for early detection of cognitive decline, if deployed on a large scale, would have individual and societal benefits. However, current detection methods are invasive or time-consuming and therefore not suitable for longitudinal monitoring of asymptomatic individuals. For example, biological markers of neuropathology associated with cognitive decline are typically collected via cerebral spinal fluid, cognitive functioning is evaluated from face-to-face assessments by experts and brain measures are obtained using expensive, non-portable equipment. Here, we describe scalable, repeatable, relatively non-invasive and comparatively inexpensive strategies for detecting the earliest markers of cognitive decline. These approaches are characterized by simple data collection protocols conducted in locations outside the laboratory: measurements are collected passively, by the participants themselves or by non-experts. The analysis of these data is, in contrast, often performed in a centralized location using sophisticated techniques. Recent developments allow neuropathology associated with potential cognitive decline to be accurately detected from peripheral blood samples. Advances in smartphone technology facilitate unobtrusive passive measurements of speech, fine motor movement and gait, that can be used to predict cognitive decline. Specific cognitive processes can be assayed using 'gamified' versions of standard laboratory cognitive tasks, which keep users engaged across multiple test sessions. High quality brain data can be regularly obtained, collected at-home by users themselves, using portable electroencephalography. Although these methods have great potential for addressing an important health challenge, there are barriers to be overcome. Technical obstacles include the need for standardization and interoperability across hardware and software. Societal challenges involve ensuring equity in access to new technologies, the cost of implementation and of any follow-up care, plus ethical issues.

Comparing the Efficacy of Two School-Based Approaches of Neurocognitive Training for Enhancing Executive Functions

Neurocognitive training has been shown to improve a range of cognitive/executive functions and behavior in children. Delivering this training in a school context may enhance its ecological validity and improve training outcomes. The current study examined the efficacy of two school-based neurocognitive training approaches for enhancing executive functions (EF) in typically developing children: neurocognitive training with no teacher positive feedback (NCT), and neurocognitive training with teacher positive feedback (NCT-TPF). Using a randomized control design, 45 children were randomly allocated to the no-training control, NCT, or NCT-TPF group and completed pre- and post-training assessments on the core executive function (EF) domains of inhibitory control, working memory, and task switching. Teachers' subjective acceptance of the two training protocols was investigated to explore potential ecological validity. The two training groups completed six sessions of training in a kindergarten over a 3-week period. The results showed significant post-training improvements in an untrained inhibitory control task for both training groups when compared with the control group. Different effects were found for each group for the untrained task switching task. While reduced reaction time (RT) in correct Color and Shape trials at Time 2 were reported for the NCT-TPF group, there was no difference compared to the control group for the NCT group. The NCT group showed increased RT in Switch trials but reduced Shape errors compared to controls at Time 2, while these effects were not significant for the NCT-TPF group. An unexpected outcome was that children in both training conditions did not show a significant improvement in an untrained working memory task. Teachers' subjective acceptance consistently supported including positive feedback as part of NCT. While further research is needed, these results support use of neurocognitive training and/or neurocognitive training with teacher positive feedback for typically developing children in a school context.

A test-retest resting, and cognitive state EEG dataset during multiple subject-driven states

Here we present a test-retest dataset of electroencephalogram (EEG) acquired at two resting (eyes open and eyes closed) and three subject-driven cognitive states (memory, music, subtraction) with both short-term (within 90 mins) and long-term (one-month apart) designs. 60 participants were recorded during three EEG sessions. Each session includes EEG and behavioral data along with rich samples of behavioral assessments testing demographic, sleep, emotion, mental health and the content of self-generated thoughts (mind wandering). This data enables the investigation of both intra- and inter-session variability not only limited to electrophysiological changes, but also including alterations in resting and cognitive states, at high temporal resolution. Also, this dataset is expected to add contributions to the reliability and validity of EEG measurements with open resource.

Measurement(s)	resting and cogntive state EEG
Technology Type(s)	electroencephalography (EEG)
Factor Type(s)	session
Sample Characteristic - Organism	human being

Association of Transcranial Direct Current Stimulation and Neurofeedback With Declarative Memory and Cerebral Arterial Flow in University Students: Protocol for a Double-blind Randomized Controlled Study

BACKGROUND

The performance of a task depends on ongoing brain activity, which can be influenced by attention, excitement, or motivation. Scientific studies have confirmed that mindfulness leads to better performance, health, and well-being. However, these cognitive efficiency modulating factors are nonspecific, can be difficult to control, and are not suitable to specifically facilitate neural processing.

OBJECTIVE

The aim of this study is to evaluate the effects of transcranial direct current stimulation associated with neurofeedback on declarative memory and cerebral blood flow in university students.

METHODS

In this study, we will use transcranial direct current stimulation, a low-cost physical resource that is easy to apply, has few adverse effects, and is associated with a neurofeedback resource. This, in turn, has been shown to be a training program capable of improving working memory function.

RESULTS

Participants will be recruited between July 2022 and December 2022. This study is expected to conclude in July 2023.

CONCLUSIONS

This study will provide preliminary results on the benefits of using the direct current neurostimulation and neurofeedback tools on the participants being analyzed.

TRIAL REGISTRATION

Brazilian Clinical Trials Registry RBR-7zs8b5; https://ensaiosclinicos.gov.br/rg/RBR-7zs8b5.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/36294.

Neuroscience from the comfort of your home: Repeated, self-administered wireless dry EEG measures brain function with high fidelity

Recent advances have enabled the creation of wireless, “dry” electroencephalography (EEG) recording systems, and easy-to-use engaging tasks, that can be operated repeatedly by naïve users, unsupervised in the home. Here, we evaluated the validity of dry-EEG, cognitive task gamification, and unsupervised home-based recordings used in combination. Two separate cohorts of participants—older and younger adults—collected data at home over several weeks using a wireless dry EEG system interfaced with a tablet for task presentation. Older adults (n = 50; 25 females; mean age = 67.8 years) collected data over a 6-week period. Younger male adults (n = 30; mean age = 25.6 years) collected data over a 4-week period. All participants were asked to complete gamified versions of a visual Oddball task and Flanker task 5–7 days per week. Usability of the EEG system was evaluated via participant adherence, percentage of sessions successfully completed, and quantitative feedback using the System Usability Scale. In total, 1,449 EEG sessions from older adults (mean = 28.9; SD = 6.64) and 684 sessions from younger adults (mean = 22.87; SD = 1.92) were collected. Older adults successfully completed 93% of sessions requested and reported a mean usability score of 84.5. Younger adults successfully completed 96% of sessions and reported a mean usability score of 88.3. Characteristic event-related potential (ERP) components—the P300 and error-related negativity—were observed in the Oddball and Flanker tasks, respectively. Using a conservative threshold for inclusion of artifact-free data, 50% of trials were rejected per at-home session. Aggregation of ERPs across sessions (2–4, depending on task) resulted in grand average signal quality with similar Standard Measurement Error values to those of single-session wet EEG data collected by experts in a laboratory setting from a young adult sample. Our results indicate that easy-to-use task-driven EEG can enable large-scale investigations in cognitive neuroscience. In future, this approach may be useful in clinical applications such as screening and tracking of treatment response.

Different Educational Interventions on Individual Cognition of Garbage Classification Based on EEG Monitoring

Improvement in an individuals’ cognition is the key to promote garbage classification. This study takes university students as the research subjects, through three educational interventions, including the self-learning, heuristic learning, and interactive learning ways, to seek the most effective intervention based upon event-related potentials (ERPs) that is beneficial to enhance cognition of garbage classification. The results show that the experimental subjects induced P300 and LPP components, representing attentional changes and cognitive conflicts in classification judgments. There are differences in the amplitudes and peak latency of the two components corresponding to different interventions, indicating that the three educational interventions are able to improve the individual’s cognition level of garbage classification within a certain period of time. The interactive-learning intervention triggers the largest amplitudes of P300 and LPP, as well as the smallest peak latency, indicating its effect is the best. Such results provide insight into the design for an appropriate strategy in garbage classification education. The study also shows that an EEG signal can be used as the endogenous neural indicator to measure the performance of garbage classification under different educational interventions.

A Single-Channel Wireless EEG Headset Enabled Neural Activities Analysis for Mental Healthcare Applications

Electroencephalography (EEG) is a technique of Electrophysiology used in a wide variety of scientific studies and applications. Inadequately, many commercial devices that are available and used worldwide for EEG monitoring are expensive that costs up to thousands of dollars. Over the past few years, because of advancements in technology, different cost-effective EEG recording devices have been made. One such device is a non-invasive single electrode commercial EEG headset called MindWave 002 (MW2), created by NeuroSky Inc that cost less than 100 USD. This work contributes in four distinct ways, first, how mental states such as a focused and relaxed can be identified based on EEG signals recorded by inexpensive MW2 is demonstrated for accurate information extraction. Second, MW2 is considered because apart from cost, the user's comfort level is enhanced due to non-invasive operation, low power consumption, portable small size, and a minimal number of detecting locations of MW2. Third, 2 situations were created to stimulate focus and relaxation states. Prior to analysis, the acquired brain signals were pre-processed to discard artefacts and noise, and band-pass filtering was performed for delta, theta, alpha, beta, and gamma wave extraction. Fourth, analysis of the shapes and nature of extracted waves was performed with power spectral density (PSD), mean amplitude values, and other parameters in LabVIEW. Finally, with comprehensive experiments, the mean values of the focused and relaxed signal EEG signals were found to be 30.23 µV and 15.330 µV respectively. Similarly, average PSD values showed an increase in theta wave value and a decrease in beta wave value related to the focus and relaxed state, respectively. We also analyzed the involuntary and intentional number of blinks recorded by the MW2 device. Our study can be used to check mental health wellness and could provide psychological treatment effects by training the mind to quickly enter a relaxed state and improve the person's ability to focus. In addition, this study can open new avenues for neurofeedback and brain control applications.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11277-022-09731-w.

A randomized controlled study of remote computerized cognitive, neurofeedback, and combined training in the treatment of children with attention-deficit/hyperactivity disorder

There is an increasing interest in non-pharmacological treatments for children with attention-deficit/hyperactivity disorder (AD/HD), especially digital techniques that can be remotely delivered, such as neurofeedback (NFT) and computerized cognitive training (CCT). In this study, a randomized controlled design was used to compare training outcomes between remotely delivered NFT, CCT, and combined NFT/CCT training approaches. A total of 121 children with AD/HD were randomly assigned to the NFT, CCT, or NFT/CCT training groups, with 80 children completing the training program. Pre- and post-training symptoms (primary outcome), executive and daily functions were measured using questionnaires as well as resting EEG during eyes-closed (EC) and eyes-open (EO) conditions. After 3 months of training, the inattentive and hyperactive/impulsive symptoms, inhibition, working memory, learning and life skills of the three groups of children were significantly improved. The objective EEG activity showed a consistent increase in the relative alpha power in the EO condition among the three training groups. Training differences were not observed between groups. There was a positive correlation between pre-training EO relative alpha power and symptom improvement scores of inattention and hyperactivity/impulsivity, as well as a negative correlation between pre-training inattention scores and change in EO relative alpha. This study verified the training effects of NFT, CCT, and combined NFT/CCT training in children with AD/HD and revealed an objective therapeutic role for individual relative alpha activity. The verified feasibility and effectiveness of home-based digital training support promotion and application of digital remote training.

Functional connectivity using high density EEG shows competitive reliability and agreement across test/retest sessions

BACKGROUND

Electrophysiological resting state functional connectivity using high density electroencephalography (hdEEG) is gaining momentum. The increased resolution offered by hdEEG, usually either 128 or 256 channels, permits source localization of EEG signals on the cortical surface. However, the number of methodological options for the acquisition and analysis of resting state hdEEG is extremely large. These include acquisition duration, eyes open/closed, channel density, source localization methods, and functional connectivity metric.

NEW METHODS

We undertake an extensive examination of the test-retest reliability and methodological agreement of all these options for regional measures of functional connectivity.

RESULTS

Power envelope connectivity shows larger test-retest reliability than imaginary coherence across all bands. While channel density doesn't strongly impact reliability or agreement, source localization methods produce systematically different functional connectivity, highlighting an important obstacle for replicating results in the literature. Most importantly, reliability and agreement often plateaus at or after 6 minutes of acquisition, well beyond the typical duration of 3 minutes. Finally, our study demonstrates that resting EEG can be as or more reliable than resting fMRI acquired in the same individuals.

CONCLUSIONS

The competitive reliability and agreement of power envelope connectivity greatly increases our confidence in measuring resting state connectivity using EEG and its capacity to find individual differences.

SSA with CWT and k-Means for Eye-Blink Artifact Removal from Single-Channel EEG Signals

Recently, the use of portable electroencephalogram (EEG) devices to record brain signals in both health care monitoring and in other applications, such as fatigue detection in drivers, has been increased due to its low cost and ease of use. However, the measured EEG signals always mix with the electrooculogram (EOG), which are results due to eyelid blinking or eye movements. The eye-blinking/movement is an uncontrollable activity that results in a high-amplitude slow-time varying component that is mixed in the measured EEG signal. The presence of these artifacts misled our understanding of the underlying brain state. As the portable EEG devices comprise few EEG channels or sometimes a single EEG channel, classical artifact removal techniques such as blind source separation methods cannot be used to remove these artifacts from a single-channel EEG signal. Hence, there is a demand for the development of new single-channel-based artifact removal techniques. Singular spectrum analysis (SSA) has been widely used as a single-channel-based eye-blink artifact removal technique. However, while removing the artifact, the low-frequency components from the non-artifact region of the EEG signal are also removed by SSA. To preserve these low-frequency components, in this paper, we have proposed a new methodology by integrating the SSA with continuous wavelet transform (CWT) and the k-means clustering algorithm that removes the eye-blink artifact from the single-channel EEG signals without altering the low frequencies of the EEG signal. The proposed method is evaluated on both synthetic and real EEG signals. The results also show the superiority of the proposed method over the existing methods.

Program for education and enrichment of relational skills (PEERS) training for social skills and depressed mood intervention in young adult with depression: Study protocol for a randomized controlled trial

INTRODUCTION

Depression is a common psychiatric disorder characterized by persistent low mood, reduced interest, and slowed thinking. Young adults are the main first-onset group for depression in all categories of the population. Program for education and enrichment of relational skills (PEERS) training, a program for the Education and Enrichment of Relational Skills, has been used in Europe and America for people with various types of social disorders with good results. A Chinese adaptation of the PEERS training program may be a new approach to help youth with depression return to society as soon as possible. This study aimed to construct and optimize a social skills training program for Chinese young adults with depression and to validate the impact of the program.

MATERIALS AND METHODS AND ANALYSIS

The aim of this trial protocol is to evaluate the efficacy of the localized PEERS training program on social competence, depressed mood in a Chinese young adult population with depression. The primary outcome will be a change in self-reported depressive symptoms from baseline to week 3 post-randomization to week 6 post-randomization measured using the Liebowitz social anxiety scale (LSAS). Secondary outcomes include the rate of decline in severe social anxiety, the Social Avoidance and Distress Scale (SAD), the Social Self-Efficacy Scale (PSSE), and the Hamilton Depression Scale (HAMD-17). Data for each assessment will be collected at baseline, week 3 of the trial, and week 6 of the trial.

ETHICS AND DISSEMINATION

Ethics approval was obtained from the Hospital Ethics Committee. Findings will be disseminated through scientific journals, conferences, and university courses.

TRIAL REGISTRATION NUMBER

[http://www.chictr.org.cn/], identifier [ChiCTR2100046050].

Acute response of prefrontal cortex in institutionalized older adults undergoing a single exergames session

Virtual reality-based exercise (exergames) improves cognition of the elderly but the neurophysiological effects are poorly understood. The hypothesis herein established is that an ultrafast neurophysiological adaptation occurs in prefrontal cortex of elderly after completion of a single exergames session. To reinforce the aforementioned hypothesis, individuals living in a Long-Term Care Home (LTCH) participated in the study and were randomly allocated into two groups (Virtual Reality Group, VRG, n = 5; and Active Control Group, ACG n = 5). VRG performed six exercises with exergames and ACG performed exercises with the same VRG movements but with no virtual reality. Assessment of frontal cortical activity at rest and during cognitive testing via electroencephalographic activity (EEG) was performed before and immediately after the intervention. Significant decrease in relative power of EEG (RP_EEG) Beta brainwave (−29 ± 18%) in the left prefrontal cortex of VRG compared to ACG (4 ± 9%) (p = 0.007). A slight improvement on semantic fluency in VRG (ES=0.21) was noted. An ultrafast prefrontal cortical adaptation may occur as an effect of a single exergames session, causing a small improvement on cognition of institutionalized elderly.

Effect of BCI-Controlled Pedaling Training System With Multiple Modalities of Feedback on Motor and Cognitive Function Rehabilitation of Early Subacute Stroke Patients

Brain-computer interfaces (BCIs) are currently integrated into traditional rehabilitation interventions after stroke. Although BCIs bring many benefits to the rehabilitation process, their effects are limited since many patients cannot concentrate during training. Despite this outcome post-stroke motor-attention dual-task training using BCIs has remained mostly unexplored. This study was a randomized placebo-controlled blinded-endpoint clinical trial to investigate the effects of a BCI-controlled pedaling training system (BCI-PT) on the motor and cognitive function of stroke patients during rehabilitation. A total of 30 early subacute ischemic stroke patients with hemiplegia and cognitive impairment were randomly assigned to the BCI-PT or traditional pedaling training. We used single-channel Fp1 to collect electroencephalography data and analyze the attention index. The BCI-PT system timely provided visual, auditory, and somatosensory feedback to enhance the patient's participation to pedaling based on the real-time attention index. After 24 training sessions, the attention index of the experimental group was significantly higher than that of the control group. The lower limbs motor function (FMA-L) increased by an average of 4.5 points in the BCI-PT group and 2.1 points in the control group (P = 0.022) after treatments. The difference was still significant after adjusting for the baseline indicators ( β = 2.41 , 95%CI: 0.48-4.34, P = 0.024). We found that BCI-PT significantly improved the patient's lower limb motor function by increasing the patient's participation. (clinicaltrials.gov: NCT04612426).

Revisión de electroencefalografía portable y su aplicabilidad en neurociencias

La electroencefalografía (EEG) es una técnica que permite registrar la actividad eléctrica del cerebro y ha sido estudiada durante los últimos cien años en diferentes ámbitos de la neurociencia. En los últimos años se ha investigado y desarrollado equipos de medición que sean portables y que permitan una buena calidad de la señal, por lo cual se realizó una revisión bibliográfica de las compañías fabricantes de algunos dispositivos de electroencefalografía portable disponibles en el mercado, se exponen sus características principales, algunos trabajos encontrados que fueron realizados con los dispositivos, comparaciones entre los mismos y una discusión acerca de las ventajas y desventajas de sus características. Finalmente se concluye que a la hora de comprar un dispositivo para electroencefalografía portable es necesario tener en cuenta el uso que se le va a dar y el costo-beneficio que tiene el equipo de acuerdo con sus características. Encephalography is a technique that allows the recording of electrical activity of the brain and has been studied during the last hundred years in different areas of neuroscience. For several years, measuring equipment that are portable and that allow a good signal quality to have been researched and developed, so a literature review of the manufacturing companies of some of portable electroencephalography devices available on the market was carried out: Its main features are exposed, as well as some of the work found that were made with those, comparisons between them and a discussion about the advantages and disadvantages of their features. It is concluded that, when a portable encephalography device is bought, it’s necessary to take into consideration the use that it will be having and the cost-benefit that the device has according to its features.

Neural Dynamics of a Single Human with Long-Term, High Temporal Density Electroencephalography

We undertake a longitudinal study with high temporal recording density, capturing daily electroencephalograms (EEG) of an individual in an in-situ setting for 370 consecutive days. Resting-state EEG retains a high level of stability over the course of the year, and inter-session variability remains unchanged, whether the sessions are one day, one week, or one month apart. On the other hand, EEG for certain cognitive tasks experience a steady decline in similarity over the same time period. Clustering analysis reveals that days with low similarity scores should not be considered as outliers, but instead are part of a cluster of days with a consistent alternate spectral signature. This has methodological and design implications for the selection of baseline references or templates in fields ranging from neurophysiology to brain-computer interfaces (BCI) and neurobiometrics.

Effect of Omega-3 Supplementation on Self-Regulation in Typically Developing Preschool-Aged Children: Results of the Omega Kid Pilot Study-A Randomised, Double-Blind, Placebo-Controlled Trial

Supplementation of omega-3 long chain polyunsaturated fatty acids (n-3 LCPUFA) may enhance self-regulation (SR) and executive functioning (EF) in children of preschool age. The aim of the Omega Kid Study was to investigate the effect of n-3 LCPUFA supplementation on SR and EF in typically developing preschool-aged children. A double-blind placebo-controlled pilot trial was undertaken, the intervention was 12 weeks and consisted of 1.6 g of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) per day compared to placebo. The HS-Omega-3 Index^® was assessed by capillary blood samples at baseline and post-intervention. Seventy-eight children were enrolled and randomised to either the n-3 LCPUFA treatment (n = 39) or placebo (n = 39) group. Post intervention, there was a significant three-fold increase in the HS-Omega-3 Index^® in the n-3 LCPUFA group (p < 0.001). There were no improvements in SR or EF outcome variables for the n-3 LCPUFA group post intervention compared to the placebo group determined by linear mixed models. At baseline, there were significant modest positive Spearman correlations found between the HS-Omega-3 index^® and both behavioural self-regulation and cognitive self-regulation (r = 0.287, p = 0.015 and r = 0.242, p = 0.015 respectively). Although no treatment effects were found in typically developing children, further research is required to target children with sub-optimal self-regulation who may benefit most from n-3 LCPUFA supplementation.

Measuring Correlates of Mental Workload During Simulated Driving Using cEEGrid Electrodes: A Test-Retest Reliability Analysis

The EEG reflects mental processes, especially modulations in the alpha and theta frequency bands are associated with attention and the allocation of mental resources. EEG has also been used to study mental processes while driving, both in real environments and in virtual reality. However, conventional EEG methods are of limited use outside of controlled laboratory settings. While modern EEG technologies offer hardly any restrictions for the user, they often still have limitations in measurement reliability. We recently showed that low-density EEG methods using film-based round the ear electrodes (cEEGrids) are well-suited to map mental processes while driving a car in a driving simulator. In the present follow-up study, we explored aspects of ecological and internal validity of the cEEGrid measurements. We analyzed longitudinal data of 127 adults, who drove the same driving course in a virtual environment twice at intervals of 12-15 months while the EEG was recorded. Modulations in the alpha and theta frequency bands as well as within behavioral parameters (driving speed and steering wheel angular velocity) which were highly consistent over the two measurement time points were found to reflect the complexity of the driving task. At the intraindividual level, small to moderate (albeit significant) correlations were observed in about 2/3 of the participants, while other participants showed significant deviations between the two measurements. Thus, the test-retest reliability at the intra-individual level was rather low and challenges the value of the application for diagnostic purposes. However, across all participants the reliability and ecological validity of cEEGrid electrodes were satisfactory in the context of driving-related parameters.

Change in Brain Oscillations as a Mechanism of Mindfulness-Meditation, Cognitive Therapy, and Mindfulness-Based Cognitive Therapy for Chronic Low Back Pain

OBJECTIVE

Psychological treatments for chronic low back pain (CLBP) are effective. However, limited research has investigated their neurophysiological mechanisms. This study examined electroencephalography- (EEG-) assessed brain oscillation changes as potential mechanisms of cognitive therapy (CT), mindfulness-meditation (MM), and mindfulness-based cognitive therapy (MBCT) for CLBP. The a priori bandwidths of interest were changes in theta, alpha and beta power, measured at pre- and post-treatment.

DESIGN

A secondary analysis of a clinical trial.

SETTING

University of Queensland Psychology Clinic.

SUBJECTS

Adults (N = 57) with CLBP who completed pre- and post-treatment EEG and pain outcome assessments.

METHODS

EEG data were examined for five regions of interest (ROIs); the primary outcome was pain intensity.

RESULTS

A significant reduction in theta (P=.015) and alpha (P=.006) power in the left frontal ROI across all treatments was found, although change in theta and alpha power in this region was not differentially associated with outcome across treatments. There were significant reductions in beta power in all five ROIs across all treatments (P≤.013). Beta power reduction in the central ROI showed a significant association with reduced pain intensity in MBCT only (P=.028). Changes in other regions were not statistically significant.

CONCLUSIONS

These findings provide support for the capacity of psychological CLBP treatments to induce changes in brain activity. The reduced beta power in all five ROIs indicated that all three treatments engendered a state of lowered cortical arousal. The growing body of research in this area could potentially inform novel directions towards remedying central nervous system abnormalities associated with CLBP.

Development of Frontal EEG Differences Between Eyes-Closed and Eyes-Open Resting Conditions in Children: Data From a Single-Channel Dry-Sensor Portable Device

Changes in EEG when moving from an eyes-closed to an eyes-open resting condition result from bottom-up sensory processing and have been referred to as activation. In children, activation is characterized by a global reduction in alpha, frontally present reductions for delta and theta, and a frontal increase for beta. The present study aimed to replicate frontal EEG activation effects using single-channel, dry-sensor EEG, and to extend current understanding by examining developmental change in children. Frontal EEG was recorded using a single-channel, dry-sensor EEG device while 182 children aged 7 to 12 years completed eyes-closed resting (EC), eyes-open resting (EO), and focus (FO) tasks. Results indicated that frontal delta, theta, and alpha power were reduced, and frontal beta power was increased, in the EO compared with the EC condition. Exploratory analysis of a form of top-down activation showed that frontal beta power was increased in the FO compared with to the EO condition, with no differences for other bands. The activation effects were robust at the individual level. The bottom-up activation effects reduced with age for frontal delta and theta, increased for frontal alpha, with no developmental change for top-down or bottom-up frontal beta activation. These findings contribute further to validation of the single-channel, dry-sensor, frontal EEG and provide support for use in a range of medical, therapeutic, and clinical domains.

Feasibility of Repeated Assessment of Cognitive Function in Older Adults Using a Wireless, Mobile, Dry-EEG Headset and Tablet-Based Games

Access to affordable, objective and scalable biomarkers of brain function is needed to transform the healthcare burden of neuropsychiatric and neurodegenerative disease. Electroencephalography (EEG) recordings, both resting and in combination with targeted cognitive tasks, have demonstrated utility in tracking disease state and therapy response in a range of conditions from schizophrenia to Alzheimer's disease. But conventional methods of recording this data involve burdensome clinic visits, and behavioural tasks that are not effective in frequent repeated use. This paper aims to evaluate the technical and human-factors feasibility of gathering large-scale EEG using novel technology in the home environment with healthy adult users. In a large field study, 89 healthy adults aged 40-79 years volunteered to use the system at home for 12 weeks, 5 times/week, for 30 min/session. A 16-channel, dry-sensor, portable wireless headset recorded EEG while users played gamified cognitive and passive tasks through a tablet application, including tests of decision making, executive function and memory. Data was uploaded to cloud servers and remotely monitored via web-based dashboards. Seventy-eight participants completed the study, and high levels of adherence were maintained throughout across all age groups, with mean compliance over the 12-week period of 82% (4.1 sessions per week). Reported ease of use was also high with mean System Usability Scale scores of 78.7. Behavioural response measures (reaction time and accuracy) and EEG components elicited by gamified stimuli (P300, ERN, Pe and changes in power spectral density) were extracted from the data collected in home, across a wide range of ages, including older adult participants. Findings replicated well-known patterns of age-related change and demonstrated the feasibility of using low-burden, large-scale, longitudinal EEG measurement in community-based cohorts. This technology enables clinically relevant data to be recorded outside the lab/clinic, from which metrics underlying cognitive ageing could be extracted, opening the door to potential new ways of developing digital cognitive biomarkers for disorders affecting the brain.

Single-channel electroencephalography and its associations with anxiety and pain during oral surgery: a preliminary report

Background

This study aimed to assess the course of anxiety and pain during lower third molar (LTMo) surgery and explore the role of mobile and single-channel electroencephalography under clinical and surgical conditions.

Methods

The State-Trait Anxiety Inventory (STAI), Corah's Dental Anxiety Scale (DAS), and Interval Scale of Anxiety Response (ISAR) were used. The patient self-rated anxiety (PSA), the pain felt during and after surgery, EEG, heart rate (HR), and blood pressure (BP) were assessed.

Results

The Attention (ATT) and Meditation (MED) algorithms and indicators evaluated in this study showed several associations. ATT showed interactions and an association with STAI-S, pain during surgery, PSA level, HR, and surgical duration. MED showed an interaction and association with DAS, STAI-S, and pain due to anesthesia. Preclinical anxiety parameters may influence clinical perceptions and biological parameters during LTMo surgeries. High STAI-Trait and PSA scores were associated with postoperative pain, whereas high STAI-State scores were associated with more pain during anesthesia and surgery, as well as DAS, which was also associated with patient interference during surgery due to anxiety.

Conclusions

The findings suggest that single-channel EEG is promising for evaluating brain responses associated with systemic reactions related to anxiety, surgical stress, and pain during oral surgery.

Aiding diagnosis of childhood attention-deficit/hyperactivity disorder of the inattentive presentation: Discriminant function analysis of multi-domain measures including EEG

INTRODUCTION

We developed a neurocognitive assessment tool (NCAT) in consultation with mental health professionals working with children with AD/HD as a diagnostic aid and screening tool. This study examines the predictive utility of NCAT in the classification of children with AD/HD Inattentive presentation.

METHOD

Fifty three children with AD/HD Inattentive presentation and 161 typically-developing children completed an NCAT assessment. Discriminant function analyses examined group membership prediction for separate components of NCAT and for the components combined.

RESULTS

The combined model correctly classified 93.4 % of participants, with 91.4 % sensitivity and 93.9 % specificity. Contributions to classification were from SNAP-IV, psychological needs satisfaction, self-regulation, executive function performance, and EEG. The combined model resulted in a 9.3 % increase in specificity and 5.9 % increase in sensitivity compared to SNAP-IV alone.

CONCLUSIONS

NCAT provides good discrimination between children with and without AD/HD of the Inattentive presentation, and further investigation including other subtypes and comorbidities is warranted.

Mobile Neurofeedback for Pain Management in Veterans with TBI and PTSD

OBJECTIVE

Chronic pain is common in military veterans with traumatic brain injury (TBI) and post-traumatic stress disorder (PTSD). Neurofeedback, or electroencephalograph (EEG) biofeedback, has been associated with lower pain but requires frequent travel to a clinic. The current study examined feasibility and explored effectiveness of neurofeedback delivered with a portable EEG headset linked to an application on a mobile device.

DESIGN

Open-label, single-arm clinical trial.

SETTING

Home, outside of clinic.

SUBJECTS

N = 41 veterans with chronic pain, TBI, and PTSD.

METHOD

Veterans were instructed to perform "mobile neurofeedback" on their own for three months. Clinical research staff conducted two home visits and two phone calls to provide technical assistance and troubleshoot difficulties.

RESULTS

N = 36 veterans returned for follow-up at three months (88% retention). During this time, subjects completed a mean of 33.09 neurofeedback sessions (10 minutes each). Analyses revealed that veterans reported lower pain intensity, pain interference, depression, PTSD symptoms, anger, sleep disturbance, and suicidal ideation after the three-month intervention compared with baseline. Comparing pain ratings before and after individual neurofeedback sessions, veterans reported reduced pain intensity 67% of the time immediately following mobile neurofeedback. There were no serious adverse events reported.

CONCLUSIONS

This preliminary study found that veterans with chronic pain, TBI, and PTSD were able to use neurofeedback with mobile devices independently after modest training and support. While a double-blind randomized controlled trial is needed for confirmation, the results show promise of a portable, technology-based neuromodulatory approach for pain management with minimal side effects.

Effect of Neurocognitive Training for Children With ADHD at Improving Academic Engagement in Two Learning Settings

Objective: This preliminary study investigated effectiveness of neurocognitive training on academic engagement (AET) for children with ADHD. The training approach targeted working memory, inhibitory control, and attention/relaxation (via brain electrical activity). Method: A reversal design with a 2-week follow-up was used to assess the effectiveness of the treatment on two children with diagnosed ADHD in two learning settings. Direct observation was used to collect academic-related behavior. Results: Improvements in on-task expected behavior (ONT-EX) and general AET, as well as reductions in off-task motor activity (OFF-MA) and off-task passive behavior (OFF-PB) were observed for both students over baselines and across the settings. Moreover, differences in behavioral change were found between participants and settings. Conclusion: These findings support using the treatment for improving academic performance of children with ADHD. Future studies may investigate influences of contextual differences, nontreatment variables, or adult's feedback during the training session on treatment effectiveness.

The Feasibility of the "Omega Kid" Study Protocol: A Double-Blind, Randomised, Placebo-Controlled Trial Investigating the Effect of Omega-3 Supplementation on Self-Regulation in Preschool-Aged Children

Self-regulation, the regulation of behaviour in early childhood, impacts children's success at school and is a predictor of health, wealth, and criminal outcomes in adulthood. Self-regulation may be optimised by dietary supplementation of omega-3 long-chain polyunsaturated fatty acids (n-3 LCPUFAs). The aim of the "Omega Kid" study is to investigate the feasibility of a protocol to investigate whether n-3 LCPUFA supplementation enhances self-regulation in preschool-aged children. The protocol assessed involved a double-blind, randomised, placebo-controlled trial of 12 weeks duration, with an intervention of 1.6 g of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) per day (0.3 g EPA and 1.3 g DHA) in a microencapsulated powder compared to placebo. Children (n = 78; 40 boys and 38 girls) aged 3-5 years old were recruited and randomly allocated to the treatment (n = 39) or placebo group (n = 39). The HS-Omega-3 Index^® served as a manipulation check on the delivery of either active (n-3 LCPUFAs) or placebo powders. Fifty-eight children (76%) completed the intervention (28-30 per group). Compliance to the study protocol was high, with 92% of children providing a finger-prick blood sample at baseline and high reported-adherence to the study intervention (88%). Results indicate that the protocol is feasible and may be employed in an adequately powered clinical trial to test the hypothesis that n-3 LCPUFA supplementation will improve the self-regulation of preschool-aged children.

Acute effects of 2D exergame on cognitive functions and frontal cortical activity

ABSTRACT This study aims to evaluate the effect of an exercise with a 2D virtual reality session on the cognition and cortical activity of young males. This is a randomized controlled trial with ten men aged 18 to 23 years. They were randomly assigned under two conditions: 1) exercise session with 2D virtual reality games and 2) control, which consisted of watching a two-episode video of a comic TV show. Cognition and frontal cortical activity were assessed immediately before and after the intervention, using the Mindset, performing the Digit Span Test, semantic verbal fluency, and executive function. Executive function improved with the exergame session (p=0.025). Exergames partially promote an immediate increase in the executive function of young people.

Long-term stability of resting state EEG-based linear and nonlinear measures

This preliminary study is aimed to evaluate the stability of various linear and nonlinear EEG measures over three years on healthy adults. The linear measures, relative powers of EEG frequency bands, interhemispheric (IHAS) and spectral (SASI) asymmetries plus nonlinear Higuchi's fractal dimension (HFD) and detrended fluctuation analyses (DFA), have been calculated from the resting state eyes closed EEG of 17 participants during two sessions separated over three years. Our results indicate that the stability is highest for the nonlinear (HFD and DFA) and the linear (relative powers of EEG frequency bands) EEG measures that use the signal from a single EEG channel and frequency band, followed by the SASI employing signals from a single channel and two frequency bands and lowest for the IHAS employing signals from two channels. The result support the prospect of using EEG-based measures in clinical practice.

Improved Activity Recognition Combining Inertial Motion Sensors and Electroencephalogram Signals

Human activity recognition and neural activity analysis are the basis for human computational neureoethology research dealing with the simultaneous analysis of behavioral ethogram descriptions and neural activity measurements. Wireless electroencephalography (EEG) and wireless inertial measurement units (IMU) allow the realization of experimental data recording with improved ecological validity where the subjects can be carrying out natural activities while data recording is minimally invasive. Specifically, we aim to show that EEG and IMU data fusion allows improved human activity recognition in a natural setting. We have defined an experimental protocol composed of natural sitting, standing and walking activities, and we have recruited subjects in two sites: in-house ([Formula: see text]) and out-house ([Formula: see text]) populations with different demographics. Experimental protocol data capture was carried out with validated commercial systems. Classifier model training and validation were carried out with scikit-learn open source machine learning python package. EEG features consist of the amplitude of the standard EEG frequency bands. Inertial features were the instantaneous position of the body tracked points after a moving average smoothing to remove noise. We carry out three validation processes: a 10-fold cross-validation process per experimental protocol repetition, (b) the inference of the ethograms, and (c) the transfer learning from each experimental protocol repetition to the remaining repetitions. The in-house accuracy results were lower and much more variable than the out-house sessions results. In general, random forest was the best performing classifier model. Best cross-validation results, ethogram accuracy, and transfer learning were achieved from the fusion of EEG and IMUs data. Transfer learning behaved poorly compared to classification on the same protocol repetition, but it has accuracy still greater than 0.75 on average for the out-house data sessions. Transfer leaning accuracy among repetitions of the same subject was above 0.88 on average. Ethogram prediction accuracy was above 0.96 on average. Therefore, we conclude that wireless EEG and IMUs allow for the definition of natural experimental designs with high ecological validity toward human computational neuroethology research. The fusion of both EEG and IMUs signals improves activity and ethogram recognition.

Assessing the Retest Reliability of Prefrontal EEG Markers of Brain Rhythm Slowing in the Eyes-Closed Resting State

Objective. We examined whether prefrontal lobe EEG markers of slower brain rhythms, which are correlated with functional brain aging, can reliably reflect those of other brain lobes, as measured by a multichannel device. Methods. EEG measurements were taken of 112 healthy individuals aged 20 to 69 years in the eyes-closed resting state. A 5-minute measurement was taken at 8 regions (Fp1, Fp2, F3, F4, T3, T4, O1, O2). Indices (median frequency [MDF], peak frequency [PF]) that quantitatively reflect the characteristics of EEG slowing, and traditional commonly used spectral indices (absolute powers as delta, theta, alpha, beta, and relative power as alpha-to-theta ratio [ATR]), were extracted from the EEG signals. For these indices, the differences between the prefrontal lobe and other areas were analyzed and the test-retest reproducibility was investigated. Results. The EEG slowing indicators showed high conformity over all brain lobes and stable reproducibility. On the other hand, the typical EEG spectral indicators delta, theta, alpha, beta, and ATR differed between brain regions. Conclusion. It was found that EEG slowing markers, which were used for assessing the aging or degeneration of brain functions, could be reliably extracted from a prefrontal EEG alone. Significance. These findings suggest that EEG prefrontal markers may reflect markers of other brain regions when a multi-channel device is used. Thus, this method may constitute a low-cost, wearable, wireless, easily accessible, and noninvasive tool for neurological assessment that could be used in the early detection of cognitive decline and in the prevention of dementia.

Negative effect of methyl bromide fumigation work on the central nervous system

Methyl bromide (MB) is a fumigant that has been widely used for killing pests on plants in trade, soils, and structures worldwide due to its excellent permeability and insecticidal effect; however, MB should be replaced because it is an ozone-depleting substance. It is well-known that MB is highly toxic and hazardous to workers, but the effects of exposure in asymptomatic workers have not been explored. The purpose of this study is to investigate the impact of MB fumigation on the health of fumigators at a sensitive level. The electroencephalogram (EEG) and urinary bromide ion levels of 44 fumigators (the study group) and 20 inspectors (the control) were measured before and after fumigation work from February to August 2019 in Busan, Korea. The mean post-work concentration of bromide ion (18.311 μg/mg CRE) in the fumigators was significantly increased from the pre-work level (7.390 μg/mg CRE) (P<0.001). The fumigator post-work median frequencies (MDF) and alpha-to-theta ratios (ATR) of EEG index were significantly decreased compared to the pre-work values (P<0.05 for all indices). In contrast, there were no significant differences in inspector EEG indices and urinary bromide ion. The urinary bromide ion levels in all the subjects were negatively correlated with MDF (P = 0.032). In conclusion, fumigators’ EEG indices and urinary bromide ion suggested that occupational exposure to MB negatively affected the health of workers, although the workers were asymptomatic.

Shoes and Insoles: The Influence on Motor Tasks Related to Walking Gait Variability and Stability

The rhythmic control of the lower limb muscles influences the cycle-to-cycle variability during a walking task. The benefits of insoles, commonly used to improve the walking gait, have been little studied. Therefore, the aim of this study was to assess the walking gait variability and stability on different walking conditions (without shoes, WTS, with shoes, WS, with shoes and insoles, WSI) related to brain activity. Twelve participants randomly (WTS/WS/WSI) walked on a treadmill at 4 km/h for 10 min. Kinematic analysis (i.e., footstep and gait variability), brain activation (beta wave signal), rating of perceived exertion (RPE, CR-10 scale), and time domain measures of walking variability were assessed. The maximum Lyapunov exponent (LyE) on the stride cycle period's datasets was also calculated. Stride length and cycle calculated for all walking conditions were 61.59 ± 2.53/63.38 ± 1.43/64.09 ± 2.40 cm and 1.11 ± 0.03/1.14 ± 0.03/1.15 ± 0.04 s (F_1,10 = 4.941/p = 0.01, F_1,10 = 4.938/p = 0.012) for WTS, WS, WSI, respectively. Beta wave (F_1,10 = 564.201/p = 0.0001) was higher in WTS compared to WS and WSI. Analysis of variance's (ANOVA) LyE showed a F_1,10 = 3.209/p = 0.056, while post hoc analysis showed a significant effect between WS and WSI with p = 0.023, and nonsignificant effects between WTS and WS/WSI (p = 0.070/0.607), respectively. Small perturbations of the foot can influence the control of gait rhythmicity by increasing the variability in a dissipative deterministic regimen.

Predicting functional outcomes after stroke: an observational study of acute single-channel EEG

Background: Early and objective prediction of functional outcome after stroke is an important issue in rehabilitation. Electroencephalography (EEG) has long been utilized to describe and monitor brain function following neuro-trauma, and technological advances have improved usability in the acute setting. However, skepticism persists whether EEG can provide the same prognostic value as neurological examination.Objective: The current cohort study examined the relationship between acute single-channel EEG and functional outcomes after stroke.Methods: Resting-state EEG recorded at a single left pre-frontal EEG channel (FP1) was obtained from 16 adults within 72 h of first stroke. At 30 and 90 days, measures of disability (modified Rankin Scale; mRS) and involvement in daily activities (modified Barthel Index; mBI) were obtained. Acute EEG measures were correlated with functional outcomes and compared to an early neurological examination of stroke severity using the National Institute of Health Stroke Scale (NIHSS). Classification of good outcomes (mRS ≤1 or mBI ≥95) was also examined using Receiver Operator Curve analyses.Results: One-third to one-half of participants experienced incomplete post-stroke recovery, depending on the time point and measure. Functional outcomes correlated with acute theta values (r_s 0.45-0.60), with the strength of associations equivalent to previously reported values obtained from conventional multi-channel systems. Acute theta values ≥0.25 were associated with good outcomes, with positive (67-83%) and negative predictive values (70-90%) comparable to those obtained using the NIHSS.Conclusions: Acute, single-channel EEG can provide unique, non-overlapping clinical information, which may facilitate objective prediction of functional outcome after stroke.

A comparative evaluation of signal quality between a research-grade and a wireless dry-electrode mobile EEG system

OBJECTIVE

Electroencephalography (EEG) is widely used by clinicians, scientists, engineers and other professionals worldwide, with an increasing number of low-cost, commercially-oriented EEG systems that have become available in recent years. One such system is the Cognionics Quick-20 (Cognionics Inc., San Diego, USA), which uses dry electrodes and offers the convenience of portability thanks to its built-in amplifier and wireless connection. Because of such characteristics, this system has been used in several applications for both clinical and basic research studies. However, an investigation of the quality of the signals that are recorded using this system has not yet been reported.

APPROACH

To bridge this gap, here we conducted a systematic comparison of signal quality between the Cognionics Quick-20 system and the Brain Products actiCAP/actiCHamp (Brain Products GmbH, Munich, Germany), a state-of-the-art, wet-electrode, research-oriented EEG system. Resting-state EEG data were recorded from twelve human participants at rest in eyes open and eyes closed conditions. For both systems we evaluated the similarity of mean recorded power spectral density, and detection of alpha suppression associated with eyes open relative to eyes closed.

MAIN RESULTS

Power spectral densities were highly correlated across systems, with only minor topographical variability across the scalp. Both systems recorded alpha suppression during eyes open relative to eyes closed conditions.

SIGNIFICANCE

These results attest to the robustness and reliability of the dry-electrode Cognionics system relatively to the widely used Brain Products laboratory EEG system, and thus validate its utility for clinical and basic research purposes, at least in studies in which participants do not move.

Analysis of Prefrontal Single-Channel EEG Data for Portable Auditory ERP-Based Brain-Computer Interfaces

An electroencephalogram (EEG)-based brain-computer interface (BCI) is a tool to non-invasively control computers by translating the electrical activity of the brain. This technology has the potential to provide patients who have severe generalized myopathy, such as those suffering from amyotrophic lateral sclerosis (ALS), with the ability to communicate. Recently, auditory oddball paradigms have been developed to implement more practical event-related potential (ERP)-based BCIs because they can operate without ocular activities. These paradigms generally make use of clinical (over 16-channel) EEG devices and natural sound stimuli to maintain the user's motivation during the BCI operation; however, most ALS patients who have taken part in auditory ERP-based BCIs tend to complain about the following factors: (i) total device cost and (ii) setup time. The development of a portable auditory ERP-based BCI could overcome considerable obstacles that prevent the use of this technology in communication in everyday life. To address this issue, we analyzed prefrontal single-channel EEG data acquired from a consumer-grade single-channel EEG device using a natural sound-based auditory oddball paradigm. In our experiments, EEG data was gathered from nine healthy subjects and one ALS patient. The performance of auditory ERP-based BCI was quantified under an offline condition and two online conditions. The offline analysis indicated that our paradigm maintained a high level of detection accuracy (%) and ITR (bits/min) across all subjects through a cross-validation procedure (for five commands: 70.0 ± 16.1 and 1.29 ± 0.93, for four commands: 73.8 ± 14.2 and 1.16 ± 0.78, for three commands: 78.7 ± 11.8 and 0.95 ± 0.61, and for two commands: 85.7 ± 8.6 and 0.63 ± 0.38). Furthermore, the first online analysis demonstrated that our paradigm also achieved high performance for new data in an online data acquisition stream (for three commands: 80.0 ± 19.4 and 1.16 ± 0.83). The second online analysis measured online performances on the different day of offline and first online analyses on a different day (for three commands: 62.5 ± 14.3 and 0.43 ± 0.36). These results indicate that prefrontal single-channel EEGs have the potential to contribute to the development of a user-friendly portable auditory ERP-based BCI.

Resting-state prefrontal EEG biomarkers in correlation with MMSE scores in elderly individuals

We investigated whether cognitive decline could be explained by resting-state electroencephalography (EEG) biomarkers measured in prefrontal regions that reflect the slowing of intrinsic EEG oscillations. In an aged population dwelling in a rural community (total = 496, males = 165, females = 331), we estimated the global cognitive decline using the Mini-Mental State Examination (MMSE) and measured resting-state EEG parameters at the prefrontal regions of Fp1 and Fp2 in an eyes-closed state. Using a tertile split method, the subjects were classified as T3 (MMSE 28-30, N = 162), T2 (MMSE 25-27, N = 179), or T1 (MMSE ≤ 24, N = 155). The EEG slowing biomarkers of the median frequency, peak frequency and alpha-to-theta ratio decreased as the MMSE scores decreased from T2 to T1 for both sexes (-5.19 ≤ t-value ≤ -3.41 for males and -7.24 ≤ t-value ≤ -4.43 for females) after adjusting for age and education level. Using a double cross-validation procedure, we developed a prediction model for the MMSE scores using the EEG slowing biomarkers and demographic covariates of sex, age and education level. The maximum intraclass correlation coefficient between the MMSE scores and model-predicted values was 0.757 with RMSE = 2.685. The resting-state EEG biomarkers showed significant changes in people with early cognitive decline and correlated well with the MMSE scores. Resting-state EEG slowing measured in the prefrontal regions may be useful for the screening and follow-up of global cognitive decline in elderly individuals.

Validation of Electroencephalographic Recordings Obtained with a Consumer-Grade, Single Dry Electrode, Low-Cost Device: A Comparative Study

The functional validity of the signal obtained with low-cost electroencephalography (EEG) devices is still under debate. Here, we have conducted an in-depth comparison of the EEG-recordings obtained with a medical-grade golden-cup electrodes ambulatory device, the SOMNOwatch + EEG-6, vs those obtained with a consumer-grade, single dry electrode low-cost device, the NeuroSky MindWave, one of the most affordable devices currently available. We recorded EEG signals at Fp1 using the two different devices simultaneously on 21 participants who underwent two experimental phases: a 12-minute resting state task (alternating two cycles of closed/open eyes periods), followed by 60-minute virtual-driving task. We evaluated the EEG recording quality by comparing the similarity between the temporal data series, their spectra, their signal-to-noise ratio, the reliability of EEG measurements (comparing the closed eyes periods), as well as their blink detection rate. We found substantial agreement between signals: whereas, qualitatively, the NeuroSky MindWave presented higher levels of noise and a biphasic shape of blinks, the similarity metric indicated that signals from both recording devices were significantly correlated. While the NeuroSky MindWave was less reliable, both devices had a similar blink detection rate. Overall, the NeuroSky MindWave is noise-limited, but provides stable recordings even through long periods of time. Furthermore, its data would be of adequate quality compared to that of conventional wet electrode EEG devices, except for a potential calibration error and spectral differences at low frequencies.