Development of a Smart Helmet for Strategical BCI Applications

Conducting electrophysiological measurements from human brain function provides a medium for sending commands and messages to the external world, as known as a brain–computer interface (BCI). In this study, we proposed a smart helmet which integrated the novel hygroscopic sponge electrodes and a combat helmet for BCI applications; with the smart helmet, soldiers can carry out extra tasks according to their intentions, i.e., through BCI techniques. There are several existing BCI methods which are distinct from each other; however, mutual issues exist regarding comfort and user acceptability when utilizing such BCI techniques in practical applications; one of the main challenges is the trade-off between using wet and dry electroencephalographic (EEG) electrodes. Recently, several dry EEG electrodes without the necessity of conductive gel have been developed for EEG data collection. Although the gel was claimed to be unnecessary, high contact impedance and low signal-to-noise ratio of dry EEG electrodes have turned out to be the main limitations. In this study, a smart helmet with novel hygroscopic sponge electrodes is developed and investigated for long-term usage of EEG data collection. The existing electrodes and EEG equipment regarding BCI applications were adopted to examine the proposed electrode. In the impedance test of a variety of electrodes, the sponge electrode showed performance averaging 118 kΩ, which was comparable with the best one among existing dry electrodes, which averaged 123 kΩ. The signals acquired from the sponge electrodes and the classic wet electrodes were analyzed with correlation analysis to study the effectiveness. The results indicated that the signals were similar to each other with an average correlation of 90.03% and 82.56% in two-second and ten-second temporal resolutions, respectively, and 97.18% in frequency responses. Furthermore, by applying the proposed differentiable power algorithm to the system, the average accuracy of 21 subjects can reach 91.11% in the steady-state visually evoked potential (SSVEP)-based BCI application regarding a simulated military mission. To sum up, the smart helmet is capable of assisting the soldiers to execute instructions with SSVEP-based BCI when their hands are not available and is a reliable piece of equipment for strategical applications.

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A Comparison of Conventional and Tri-Polar EEG Electrodes for Decoding Real and Imaginary Finger Movements from One Hand

International Journal of Neural Systems ◽

10.1142/s0129065721500362 ◽

2021 ◽

pp. 2150036

Author(s):

Saleh I. Alzahrani ◽

Charles W. Anderson

Keyword(s):

Spatial Resolution ◽

Spectral Power ◽

Signal To Noise Ratio ◽

Finger Movements ◽

Low Snr ◽

Average Accuracy ◽

Eeg Data ◽

Related Potentials ◽

Good Signal ◽

Disc Electrodes

The representations of different fingers in the sensorimotor cortex are largely overlapped, which necessitate a good signal-to-noise ratio (SNR) and high spatial resolution to classify individual finger movements from one hand. Electroencephalography (EEG) recorded with disc electrodes has low SNR and poor spatial resolution. The surface Laplacian has been applied to EEG to improve the spatial resolution and selectivity of the surface electrical activity recording. Tri-polar concentric ring electrodes (TCREs) were shown to estimate the Laplacian automatically with better spatial resolution than disc electrodes. For this work, movement-related potentials (MRPs) were recorded from four TCREs and disc electrodes while 13 subjects performed real and imaginary finger movements. The MRP signals recorded with the TCREs have significantly less mutual information and coherence between neighboring locations compared to disc electrodes. The results also show that signals from TCREs generated higher accuracy compared to disc electrodes. It further shows that TCREs using temporal EEG data as features yield an average accuracy of [Formula: see text]% and [Formula: see text]% for real and imaginary finger movements, respectively, which is significantly higher than utilizing EEG spectral power changes in [Formula: see text] and [Formula: see text] bands as features. Similarly, with the disc electrodes, it achieved highest accuracy of [Formula: see text]% and [Formula: see text]% for real and imaginary finger movements, respectively, with temporal EEG data feature.

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SIMBOLISASI DALAM NOVEL SANG ALKEMIS KARYA PAULO QUELHO

SASTRANESIA Jurnal Program Studi Pendidikan Bahasa dan Sastra Indonesia ◽

10.32682/sastranesia.v7i4.1301 ◽

2019 ◽

Vol 7 (4) ◽

pp. 79

Author(s):

Endang Maruti

Keyword(s):

Content Analysis ◽

Data Collection ◽

Old Age ◽

Qualitative Approach ◽

Data Sources ◽

The Novel ◽

Note Taking ◽

Literature Study ◽

Collection Method ◽

Data Collection Method

The research aims to uncover the symbols in the novel The Alchemist and to gain knowledge about the moral teachings in the symbol. This research is descriptive qualitative approach. Data sources in this study are words, phrases or sentences in the novel Alchemist. Data collection method is a literature study method with note taking technique. Data were analyzed using description and content analysis methods. The results showed that the novel The Alchemist contained many symbols. These symbols include: (1) wise parents, who symbolize both negative and positive things. From his appearance, parents can symbolize something bad, but behind his old age he symbolizes a knowledge that is very much and wise; (2) stones that symbolize something hard, not easily broken, and can provide clues to something; and (3) deserts or deserts which can be interpreted as symbols of drought, aridity, unattractiveness, emptiness, despair, determination for ignorance, and also as symbols of devotion.

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Application of Novel Low Current OBIRCH Amplifier and Nanoprobing to Identify Subtle Leakages in Advanced Node Technologies

10.31399/asm.cp.istfa2018p0303 ◽

2018 ◽

Author(s):

Satish Kodali ◽

Liangshan Chen ◽

Yuting Wei ◽

Tanya Schaeffer ◽

Chong Khiam Oh

Keyword(s):

Signal To Noise Ratio ◽

Semiconductor Industry ◽

Fault Isolation ◽

Ring Oscillator ◽

High Signal ◽

The Novel ◽

Resistance Change ◽

Three Samples ◽

Relative Threshold ◽

First Time

Abstract Optical beam induced resistance change (OBIRCH) is a very well-adapted technique for static fault isolation in the semiconductor industry. Novel low current OBIRCH amplifier is used to facilitate safe test condition requirements for advanced nodes. This paper shows the differences between the earlier and novel generation OBIRCH amplifiers. Ring oscillator high standby leakage samples are analyzed using the novel generation amplifier. High signal to noise ratio at applied low bias and current levels on device under test are shown on various samples. Further, a metric to demonstrate the SNR to device performance is also discussed. OBIRCH analysis is performed on all the three samples for nanoprobing of, and physical characterization on, the leakage. The resulting spots were calibrated and classified. It is noted that the calibration metric can be successfully used for the first time to estimate the relative threshold voltage of individual transistors in advanced process nodes.

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Textile Electrodes: Influence of Knitting Construction and Pressure on the Contact Impedance

Sensors ◽

10.3390/s21051578 ◽

2021 ◽

Vol 21 (5) ◽

pp. 1578

Author(s):

Luisa Euler ◽

Li Guo ◽

Nils-Krister Persson

Keyword(s):

Smooth Surface ◽

Research Field ◽

Uneven Surface ◽

Contact Impedance ◽

Dry Electrodes ◽

Textile Electrodes ◽

Human Forearm ◽

Wet Condition ◽

Electrode Contact ◽

Influencing Parameters

Textile electrodes, also called textrodes, for biosignal monitoring as well as electrostimulation are central for the emerging research field of smart textiles. However, so far, only the general suitability of textrodes for those areas was investigated, while the influencing parameters on the contact impedance related to the electrode construction and external factors remain rather unknown. Therefore, in this work, six different knitted electrodes, applied both wet and dry, were compared regarding the influence of specific knitting construction parameters on the three-electrode contact impedance measured on a human forearm. Additionally, the influence of applying pressure was investigated in a two-electrode setup using a water-based agar dummy. Further, simulation of an equivalent circuit was used for quantitative evaluation. Indications were found that the preferred electrode construction to achieve the lowest contact impedance includes a square shaped electrode, knitted with a high yarn density and, in the case of dry electrodes, an uneven surface topography consisting of loops, while in wet condition a smooth surface is favorable. Wet electrodes are showing a greatly reduced contact impedance and are therefore to be preferred over dry ones; however, opportunities are seen for improving the electrode performance of dry electrodes by applying pressure to the system, thereby avoiding disadvantages of wet electrodes with fluid administration, drying-out of the electrolyte, and discomfort arising from a “wet feeling”.

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A Novel Approach to EEG Speech Activity Detection with Visual Stimuli and Mobile BCI

Applied Sciences ◽

10.3390/app11020674 ◽

2021 ◽

Vol 11 (2) ◽

pp. 674

Author(s):

Marianna Koctúrová ◽

Jozef Juhár

Keyword(s):

Visual Stimuli ◽

Computer Interface ◽

Single Subject ◽

Detection Accuracy ◽

The Novel ◽

Activity Detection ◽

Speech Activity ◽

Novel Approach ◽

Eeg Data ◽

Speech Activity Detection

With the ever-progressing development in the field of computational and analytical science the last decade has seen a big improvement in the accuracy of electroencephalography (EEG) technology. Studies try to examine possibilities to use high dimensional EEG data as a source for Brain to Computer Interface. Applications of EEG Brain to computer interface vary from emotion recognition, simple computer/device control, speech recognition up to Intelligent Prosthesis. Our research presented in this paper was focused on the study of the problematic speech activity detection using EEG data. The novel approach used in this research involved the use visual stimuli, such as reading and colour naming, and signals of speech activity detectable by EEG technology. Our proposed solution is based on a shallow Feed-Forward Artificial Neural Network with only 100 hidden neurons. Standard features such as signal energy, standard deviation, RMS, skewness, kurtosis were calculated from the original signal from 16 EEG electrodes. The novel approach in the field of Brain to computer interface applications was utilised to calculated additional set of features from the minimum phase signal. Our experimental results demonstrated F1 score of 86.80% and 83.69% speech detection accuracy based on the analysis of EEG signal from single subject and cross-subject models respectively. The importance of these results lies in the novel utilisation of the mobile device to record the nerve signals which can serve as the stepping stone for the transfer of Brain to computer interface technology from technology from a controlled environment to the real-life conditions.

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Locating and Imaging through Scattering Medium in a Large Depth

Sensors ◽

10.3390/s21010090 ◽

2020 ◽

Vol 21 (1) ◽

pp. 90

Author(s):

Shuo Zhu ◽

Enlai Guo ◽

Qianying Cui ◽

Lianfa Bai ◽

Jing Han ◽

...

Keyword(s):

Phase Space ◽

Signal To Noise Ratio ◽

Speckle Pattern ◽

Heuristic Method ◽

Scattering Medium ◽

Scattering Media ◽

Signal To Noise ◽

Practical Applications ◽

Large Depth ◽

Strong Scattering

Scattering medium brings great difficulties to locate and reconstruct objects especially when the objects are distributed in different positions. In this paper, a novel physics and learning-heuristic method is presented to locate and image the object through a strong scattering medium. A novel physics-informed framework, named DINet, is constructed to predict the depth and the image of the hidden object from the captured speckle pattern. With the phase-space constraint and the efficient network structure, the proposed method enables to locate the object with a depth mean error less than 0.05 mm, and image the object with an average peak signal-to-noise ratio (PSNR) above 24 dB, ranging from 350 mm to 1150 mm. The constructed DINet firstly solves the problem of quantitative locating and imaging via a single speckle pattern in a large depth. Comparing with the traditional methods, it paves the way to the practical applications requiring multi-physics through scattering media.

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Microparticles, Microspheres, and Microcapsules for Advanced Drug Delivery

Scientia Pharmaceutica ◽

10.3390/scipharm87030020 ◽

2019 ◽

Vol 87 (3) ◽

pp. 20 ◽

Cited By ~ 35

Author(s):

Miléna Lengyel ◽

Nikolett Kállai-Szabó ◽

Vince Antal ◽

András József Laki ◽

István Antal

Keyword(s):

Drug Delivery ◽

Drug Delivery Systems ◽

Freeze Drying ◽

Delivery Systems ◽

The Novel ◽

Practical Applications ◽

Inhaled Insulin ◽

Formulation Factors ◽

Novel Drug ◽

Significant Production

Microparticles, microspheres, and microcapsules are widely used constituents of multiparticulate drug delivery systems, offering both therapeutic and technological advantages. Microparticles are generally in the 1–1000 µm size range, serve as multiunit drug delivery systems with well-defined physiological and pharmacokinetic benefits in order to improve the effectiveness, tolerability, and patient compliance. This paper reviews their evolution, significance, and formulation factors (excipients and procedures), as well as their most important practical applications (inhaled insulin, liposomal preparations). The article presents the most important structures of microparticles (microspheres, microcapsules, coated pellets, etc.), interpreted with microscopic images too. The most significant production processes (spray drying, extrusion, coacervation, freeze-drying, microfluidics), the drug release mechanisms, and the commonly used excipients, the characterization, and the novel drug delivery systems (microbubbles, microsponges), as well as the preparations used in therapy are discussed in detail.

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Automatic Detection Technology of Sonar Image Target Based on the Three-Dimensional Imaging

Journal of Sensors ◽

10.1155/2017/8231314 ◽

2017 ◽

Vol 2017 ◽

pp. 1-8 ◽

Cited By ~ 3

Author(s):

Wanzeng Kong ◽

Jinshuai Yu ◽

Ying Cheng ◽

Weihua Cong ◽

Huanhuan Xue

Keyword(s):

Data Storage ◽

3D Imaging ◽

Signal To Noise Ratio ◽

Three Dimensional ◽

Automatic Detection ◽

Classification Model ◽

Image Detection ◽

Practical Applications ◽

Sonar Image ◽

Detection Technology

With 3D imaging of the multisonar beam and serious interference of image noise, detecting objects based only on manual operation is inefficient and also not conducive to data storage and maintenance. In this paper, a set of sonar image automatic detection technologies based on 3D imaging is developed to satisfy the actual requirements in sonar image detection. Firstly, preprocessing was conducted to alleviate the noise and then the approximate position of object was obtained by calculating the signal-to-noise ratio of each target. Secondly, the separation of water bodies and strata is realized by maximum variance between clusters (OTSU) since there exist obvious differences between these two areas. Thus image segmentation can be easily implemented on both. Finally, the feature extraction is carried out, and the multidimensional Bayesian classification model is established to do classification. Experimental results show that the sonar-image-detection technology can effectively detect the target and meet the requirements of practical applications.

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Event-Locked Time-Resolved Fourier Spectroscopy

Applied Spectroscopy ◽

10.1366/0003702971941917 ◽

1997 ◽

Vol 51 (8) ◽

pp. 1106-1112 ◽

Cited By ~ 20

Author(s):

H. Weidner ◽

R. E. Peale

Keyword(s):

Signal To Noise Ratio ◽

Low Cost ◽

Michelson Interferometer ◽

Far Infrared ◽

Time Base ◽

The Novel ◽

Time Resolved ◽

Mathematical Algorithm ◽

Scan Time ◽

Recorded Data

A low-cost method of adding time-resolving capability to commercial Fourier transform spectrometers with a continuously scanning Michelson interferometer has been developed. This method is specifically designed to eliminate noise and artifacts caused by mirror-speed variations in the interferometer. The method exists of two parts: (1) a novel timing scheme for synchronizing the transient events under study and the digitizing of the interferogram and (2) a mathematical algorithm for extracting the spectral information from the recorded data. The novel timing scheme is a modification of the well-known interleaved, or stroboscopic, method. It achieves the same timing accuracy, signal-to-noise ratio, and freedom from artifacts as step-scan time-resolving Fourier spectrometers by locking the sampling of the interferogram to a stable time base rather than to the occurrences of the HeNe fringes. The necessary pathlength-difference information at which samples are taken is obtained from a record of the mirror speed. The resulting interferograms with uneven pathlength-difference spacings are transformed into wavenumber space by least-squares fits of periodic functions. Spectra from the far-infrared to the upper visible at resolutions up to 0.2 cm−1 are used to demonstrate the utility of this method.

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Novel dry electrode EEG headbands for home use: Comparing performance and comfort

Current Directions in Biomedical Engineering ◽

10.1515/cdbme-2020-3036 ◽

2020 ◽

Vol 6 (3) ◽

pp. 139-142

Author(s):

Jens Haueisen ◽

Patrique Fiedler ◽

Anna Bernhardt ◽

Ricardo Gonçalves ◽

Carlos Fonseca

Keyword(s):

Brain Activity ◽

Skin Impedance ◽

Signal Quality ◽

The Novel ◽

Application Time ◽

Dry Electrodes ◽

Power Spectral ◽

Dry Electrode ◽

Increasing Trend ◽

Eeg Recordings

AbstractMonitoring brain activity at home using electroencephalography (EEG) is an increasing trend for both medical and non-medical applications. Gel-based electrodes are not suitable due to the gel application requiring extensive preparation and cleaning support for the patient or user. Dry electrodes can be applied without prior preparation by the patient or user. We investigate and compare two dry electrode headbands for EEG acquisition: a novel hybrid dual-textile headband comprising multipin and multiwave electrodes and a neoprene-based headband comprising hydrogel and spidershaped electrodes. We compare the headbands and electrodes in terms of electrode-skin impedance, comfort, electrode offset potential and EEG signal quality. We did not observe considerable differences in the power spectral density of EEG recordings. However, the hydrogel electrodes showed considerably increased impedances and offset potentials, limiting their compatibility with many EEG amplifiers. The hydrogel and spider-shaped electrodes required increased adduction, resulting in a lower wearing comfort throughout the application time compared to the novel headband comprising multipin and multiwave electrodes.

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