scholarly journals Cost-efficient and Custom Electrode-holder Assembly Infrastructure for EEG Recordings

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4273 ◽  
Author(s):  
Yuan-Pin Lin ◽  
Ting-Yu Chen ◽  
Wei-Jen Chen
Keyword(s):  
Fused Deposition Modeling ◽  
Brain Activity ◽  
Event Related Potential ◽  
Fundamental Study ◽  
Electrode Holder ◽  
Fused Deposition ◽  
Fixed Design ◽  
Eeg Recordings ◽  
Cost Efficient ◽  
The Brain

Mobile electroencephalogram (EEG)-sensing technologies have rapidly progressed and made the access of neuroelectrical brain activity outside the laboratory in everyday life more realistic. However, most existing EEG headsets exhibit a fixed design, whereby its immobile montage in terms of electrode density and coverage inevitably poses a great challenge with applicability and generalizability to the fundamental study and application of the brain-computer interface (BCI). In this study, a cost-efficient, custom EEG-electrode holder infrastructure was designed through the assembly of primary components, including the sensor-positioning ring, inter-ring bridge, and bridge shield. It allows a user to (re)assemble a compact holder grid to accommodate a desired number of electrodes only to the regions of interest of the brain and iteratively adapt it to a given head size for optimal electrode-scalp contact and signal quality. This study empirically demonstrated its easy-to-fabricate nature by a low-end fused deposition modeling (FDM) 3D printer and proved its practicability of capturing event-related potential (ERP) and steady-state visual-evoked potential (SSVEP) signatures over 15 subjects. This paper highlights the possibilities for a cost-efficient electrode-holder assembly infrastructure with replaceable montage, flexibly retrofitted in an unlimited fashion, for an individual for distinctive fundamental EEG studies and BCI applications.

scholarly journals Conditional Entropy: A Potential Digital Marker for Stress

Entropy ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. 286
Author(s):  
Soheil Keshmiri
Keyword(s):  
Resting State ◽  
Nearest Neighbor ◽  
Brain Activity ◽  
Solution Concept ◽  
Conditional Entropy ◽  
K Nearest Neighbor ◽  
Brain Response ◽  
Substantial Progress ◽  
Eeg Recordings ◽  
The Brain

Recent decades have witnessed a substantial progress in the utilization of brain activity for the identification of stress digital markers. In particular, the success of entropic measures for this purpose is very appealing, considering (1) their suitability for capturing both linear and non-linear characteristics of brain activity recordings and (2) their direct association with the brain signal variability. These findings rely on external stimuli to induce the brain stress response. On the other hand, research suggests that the use of different types of experimentally induced psychological and physical stressors could potentially yield differential impacts on the brain response to stress and therefore should be dissociated from more general patterns. The present study takes a step toward addressing this issue by introducing conditional entropy (CE) as a potential electroencephalography (EEG)-based resting-state digital marker of stress. For this purpose, we use the resting-state multi-channel EEG recordings of 20 individuals whose responses to stress-related questionnaires show significantly higher and lower level of stress. Through the application of representational similarity analysis (RSA) and K-nearest-neighbor (KNN) classification, we verify the potential that the use of CE can offer to the solution concept of finding an effective digital marker for stress.

scholarly journals The ecological cocktail party: Measuring brain activity during an auditory oddball task with background noise

2018 ◽  
Author(s):  
Joanna E. M. Scanlon ◽  
Danielle L. Cormier ◽  
Kimberley A. Townsend ◽  
Jonathan W.P. Kuziek ◽  
Kyle E. Mathewson
Keyword(s):  
White Noise ◽  
New Technologies ◽  
Brain Activity ◽  
Real Life ◽  
Auditory Oddball ◽  
Oddball Task ◽  
Eeg Recordings ◽  
Auditory Oddball Task ◽  
The Brain ◽  
Sound Condition

AbstractMost experiments using EEG recordings take place in highly isolated and restricted environments, limiting their applicability to real-life scenarios. New technologies for mobile EEG are changing this by allowing EEG recording to take place outside of the laboratory. However, before results from experiments performed outside the laboratory can be fully understood, the effects of ecological stimuli on brain activity during cognitive tasks must be examined. In this experiment, participants performed an auditory oddball task while also listening to concurrent background noises of silence, white noise and outdoor ecological sounds, as well as a condition in which the tones themselves were at a low volume. We found a significantly increased N1 and decreased P2 when participants performed the task with outdoor sounds and white noise in the background, with the largest differences in the outdoor sound condition. This modulation in the N1 and P2 replicates what we have previously found outside while people ride bicycles (Scanlon et al., 2017b). No behavioural differences were found in response to the target tones. We interpret these modulations in early ERPs as indicative of sensory filtering of background sounds, and that ecologically valid sounds require more filtering than synthetic sounds. Our results reveal that much of what we understand about the brain will need to be updated as we step outside the lab.

scholarly journals Assessment of changes in the electrical activity of the brain during general anesthesia using portable electroencephalography

2020 ◽  
Vol 49 (2) ◽  
Author(s):  
Verónica Gaviria García ◽  
Daniel Loaiza López ◽  
Carolina Serna Rojas ◽  
Sara Ríos Arismendy ◽  
Eduardo Montoya Guevara ◽  
...  
Keyword(s):  
Electrical Activity ◽  
General Anesthesia ◽  
Brain Activity ◽  
Low Cost ◽  
Conscious State ◽  
Depth Of Anesthesia ◽  
Cross Sectional ◽  
Eyes Closed ◽  
Eeg Recordings ◽  
The Brain

Introduction: The analysis of the electrical activity of the brain using scalp electrodes with electroencephalography (EEG) could reveal the depth of anesthesia of a patient during surgery. However, conventional EEG equipment, due to its price and size, are not a practical option for the operating room and the commercial units used in surgery do not provide access to the electrical activity. The availability of low-cost portable technologies could provide for further research on the brain activity under general anesthesia and facilitate our quest for new markers of depth of anesthesia. Objective: To assess the capabilities of a portable EEG technology to capture brain rhythms associated with the state of consciousness and the general anesthesia status of surgical patients anesthetized with propofol. Methods: Observational, cross-sectional trial that reviewed 10 EEG recordings captured using OpenBCI portable low-cost technology, in female patients undergoing general anesthesia with propofol. The signal from the frontal electrodes was analyzed with spectral analysis and the results were compared against the reports in the literature. Results: The signal captured with frontal electrodes, particularly α rhythm, enabled the distinction between resting with eyes closed and with eyes opened in a conscious state, and sustained anesthesia during surgery. Conclusions: It is possible to differentiate a resting state from sustained anesthesia, replicating previous findings with conventional technologies. These results pave the way to the use of portable technologies such as the OpenBCI tool, to explore the brain dynamics during anesthesia.

scholarly journals Insights into Early Word Comprehension: Tracking the Neural Representations of Word Semantics in Infants.

2021 ◽  
Author(s):  
Rohan Saha ◽  
Jennifer Campbell ◽  
Janet F. Werker ◽  
Alona Fyshe
Keyword(s):  
Brain Activity ◽  
Word Meaning ◽  
Age Groups ◽  
Event Related Potential ◽  
Neural Representation ◽  
Machine Learning Techniques ◽  
Semantic Representations ◽  
Word Comprehension ◽  
Neural Representations ◽  
The Brain

Infants start developing rudimentary language skills and can start understanding simple words well before their first birthday. This development has also been shown primarily using Event Related Potential (ERP) techniques to find evidence of word comprehension in the infant brain. While these works validate the presence of semantic representations of words (word meaning) in infants, they do not tell us about the mental processes involved in the manifestation of these semantic representations or the content of the representations. To this end, we use a decoding approach where we employ machine learning techniques on Electroencephalography (EEG) data to predict the semantic representations of words found in the brain activity of infants. We perform multiple analyses to explore word semantic representations in two groups of infants (9-month-old and 12-month-old). Our analyses show significantly above chance decodability of overall word semantics, word animacy, and word phonetics. As we analyze brain activity, we observe that participants in both age groups show signs of word comprehension immediately after word onset, marked by our model's significantly above chance word prediction accuracy. We also observed strong neural representations of word phonetics in the brain data for both age groups, some likely correlated to word decoding accuracy and others not. Lastly, we discover that the neural representations of word semantics are similar in both infant age groups. Our results on word semantics, phonetics, and animacy decodability, give us insights into the evolution of neural representation of word meaning in infants.

Absolute Pitch and the P300 Component of the Event-Related Potential: An Exploration of Variables That May Account for Individual Differences

2003 ◽  
Vol 20 (4) ◽  
pp. 357-382 ◽  
Author(s):  
Laura Bischoff Renninger ◽  
Roni I. Granot ◽  
Emanuel Donchin
Keyword(s):  
Brain Activity ◽  
Memory Task ◽  
Absolute Pitch ◽  
Memory System ◽  
Event Related Potential ◽  
Auditory Task ◽  
Relative Pitch ◽  
P300 Component ◽  
Auditory Tasks ◽  
The Brain

Our primary goal has been to elucidate a model of pitch memory by examining the brain activity of musicians with and without absolute pitch during listening tasks. Subjects, screened for both absolute and relative pitch abilities, were presented with two auditory tasks and one visual task that served as a control. In the first auditory task (pitch memory task), subjects were asked to differentiate between diatonic and nondiatonic tones within a tonal framework. In the second auditory task (contour task), subjects were presented with the same pitch sequences but instead asked to differentiate between tones moving upward or downward. For the visual control task, subjects were presented again with the same pitch sequences and asked to determine whether each pitch was diatonic or nondiatonic, only this time the note names appeared visually on the computer screen. Our findings strongly suggest that there are various levels of absolute pitch ability. Some absolute pitch subjects have, in addition to this skill, strong relative pitch abilities, and these differences are reflected quite consistently by the behavior of the P300 component of the event-related potential. Our research also strengthens the idea that the memory system for pitch and interval distances is distinct from the memory system for contour (W. J. Dowling, 1978). Our results are discussed within the context of the current absolute pitch literature.

scholarly journals A fundamental study of parameter adjustable additive manufacturing process based on FDM process

2018 ◽  
Vol 189 ◽  
pp. 05001
Author(s):  
Qia Wan ◽  
Youjian Xu ◽  
Can Lu
Keyword(s):  
Fused Deposition Modeling ◽  
High Quality ◽  
Fundamental Study ◽  
High Productivity ◽  
Fused Deposition ◽  
Part Geometry ◽  
Build Time ◽  
Deposition Modeling ◽  
Quality Of Products

In Fused deposition modeling (FDM) process, there has been a confliction between high productivity and high quality of products. The product resolution is proportional to the flow rate of heated material extrusion, which directly affects the build time. To reduce the build time with acceptable resolution, the idea of parameter adjustable printing process has been introduced. The controllable extruder was modified and two types of diameter changeable nozzle have been designed. This work realizes different resolution building based on the part geometry during FDM process, which can efficiently assure the quality of products and improve the productivity at the same time.

Visual Imagery Classification Using Shapelets of EEG Signals

2012 ◽  
Author(s):  
Stewart Contreras ◽  
V. Sundararajan
Keyword(s):  
Time Series ◽  
Classification Scheme ◽  
Signal To Noise Ratio ◽  
Event Related Potential ◽  
Eeg Signals ◽  
Classification Rate ◽  
Average Classification Accuracy ◽  
Eeg Recordings ◽  
Electroencephalogram Eeg ◽  
The Brain

The goal of this paper is to reconstruct three primitive shapes — rectangular cube, cone and cylinder — by analyzing electrical signals which are emitted by the brain. Three participants are asked to visualize these shapes. During visualization, a 14-channel neuroheadset is used to record electroencephalogram (EEG) signals along the scalp. The EEG recordings are then averaged to increase the signal to noise ratio which is referred to as an event related potential (ERP). Every possible subsequence of each ERP signal is analyzed in an attempt to determine a time series which is maximally representative of a particular class. These time series are referred to as shapelets and form the basis of our classification scheme. After implementing a voting technique for classification, an average classification accuracy of 60% is achieved. Compared to naive classification rate of 33%, we determine that the shapelets are in fact capturing features that are unique in the ERP representation of a unique class.

EEG Derived Brain Activity Reflects Treatment Response from Vagus Nerve Stimulation in Patients with Epilepsy

2017 ◽  
Vol 27 (04) ◽  
pp. 1650048 ◽  
Author(s):  
Simon Wostyn ◽  
Willeke Staljanssens ◽  
Leen De Taeye ◽  
Gregor Strobbe ◽  
Stefanie Gadeyne ◽  
...  
Keyword(s):  
Vagus Nerve ◽  
Seizure Frequency ◽  
Mechanism Of Action ◽  
Nerve Stimulation ◽  
Vagus Nerve Stimulation ◽  
Brain Activity ◽  
P300 Amplitude ◽  
Eeg Recordings ◽  
Patients With Epilepsy ◽  
The Brain

The mechanism of action of vagus nerve stimulation (VNS) is yet to be elucidated. To that end, the effects of VNS on the brain of epileptic patients were studied. Both when VNS was switched “On” and “Off”, the brain activity of responders (R, seizure frequency reduction of over 50%) was compared to the brain activity of nonresponders (NR, seizure frequency reduction of less than 50%). Using EEG recordings, a significant increase in P300 amplitude for R and a significant decrease in P300 amplitude for NR were found. We found biomarkers for checking the efficacy of VNS with accuracy up to 94%. The results show that P300 features recorded in nonmidline electrodes are better P300 biomarkers for VNS efficacy than P300 features recorded in midline electrodes. Using source localization and connectivity analyses, the activity of the limbic system, insula and orbitofrontal cortex was found to be dependent on VNS switched “On” versus “Off” or patient group (R versus NR). The results suggest an important role for these areas in the mechanism of action of VNS, although a larger patient study should be done to confirm the findings.

scholarly journals Low Cost with Vibration Controlled Efficient Fused Deposition Modeling

2019 ◽  
Vol 8 (6) ◽  
pp. 1690-1694
Keyword(s):  
Fused Deposition Modeling ◽  
Low Cost ◽  
Fused Deposition Modelling ◽  
3D Printer ◽  
Body Parts ◽  
Fused Deposition ◽  
Rigid Frame ◽  
Innovative System ◽  
Industrial Unit ◽  
Cost Efficient

Fused Deposition Modelling (FDM) is an innovative system that can create necessary items and are significant to generate distinctive styles of articles, in unusual supplies, completely from the uniform system. FDM machine can build fair model everything from stoneware to synthetic dolls, iron machine parts, decorative chocolate cakes or regular human body parts. FDM can supersede conventional factory industrial unit with only machinery, simply like printing press swapped by bottles of ink. Nowadays these machines are available at higher costs and are used only in industrial areas. With technology available and the material used in these machines proposes a system that sparks upon making a low cost-efficient machine and materials by designing a rigid frame for the 3D printer. The result shows low cost 3D printer prototype of FDM machine and the vibration analysis with various speed at various stages for the product outcome

Research on Curved Layer Fused Deposition Modeling (CLFDM) With Variable Extruded Filament (VEF)

2018 ◽  
Author(s):  
Donghua Zhao ◽  
Weizhong Guo
Keyword(s):  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Solid Freeform Fabrication ◽  
Low Cost ◽  
Theoretical Point ◽  
Fundamental Study ◽  
Strength Performance ◽  
Longitudinal Tensile Strength ◽  
Fused Deposition ◽  
Deposition Modeling

Fused Deposition Modeling (FDM), an Additive Manufacturing (AM) technique, is widely used due to its low-cost and open source. Geometry accuracy and strength performance of the printed parts are closely related to inter-layer bonding between adjacent layers and inter-road bonding in the layer. Because of the limit of layer-based AM, the longitudinal tensile strength of the filaments is much higher than the bonding strength between adjacent filaments, which brings anisotropy of the printed part. While CLFDM is devoted to solve this problem and obtain better geometry accuracy and meanwhile decrease build time by virtue of high continuity of filament, reduced stair-step effect, and lesser number of layers, especially when manufacturing thin and curved parts (shells). However, to the best of our knowledge in the aspects of process modeling of CLFDM, available researches focus mainly on simple curved layer, instead of more intricate ones possessing tiny features, which are more common in manufacturing. Therefore, to realize Solid Freeform Fabrication (SFF), this paper researches CLFDM with VEF (simultaneously changing the direction and the dimension of extruded filament according to manufacturing demand of the curved layer), which would be a fundamental study and a foundation for Advanced Design for Additive Manufacturing (ADFAM), slicing and path planning (extruder path generation) in 3D space. To realize slicing and printing with homogeneous and inhomogeneous extruded filament between consecutive layers and within the layer (flat or curved), models of flat layer FDM and CLFDM with VEF are respectively established. Then, the relationships among key process parameters are analyzed. Finally, graphical simulation of the proposed strategy based on a vase is provided to verify its effectiveness and advantages from a theoretical point of view. In general, variable direction of extruded filament along tangential directions of part surface imparts smoother surfaces, instead of rough exterior appearance resulting from stair-step effects. And variable dimension of extruded filament maximizes material extruded to increase build speed wherever allowed and minimizes deposition size for resolution whenever needed, resulting in curved layer surfaces with uneven layer thickness and having tiny features.

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