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1

EEG based cortical investigation for the limit of stability analysis in transfemoral amputees: A comparison with able-bodied individuals

Khajuria Aayushi, Joshi Deepak

Biocybernetics and Biomedical Engineering

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2022

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Vol. 42, no. 1

362--374

EN

Background: The evidences for demonstrating the contributions of the cerebral cortex in human postural control is increasing. However, there remain little insights about the cortical correlates of balance control in lower-limb amputees. The present study aimed to investigate the cortical activity and balance performance of transfemoral amputees in comparison to healthy individuals during a continuous balance task (CBT). Methods: The postural stability of the participants was defined with limit of stability parameter. Electroencephalography (EEG) data were recorded in synchronization with the center of pressure (CoP) data from eighteen individuals (including eight unilateral transfemoral amputees). We anticipated that, due to the limb loss, the postural demand of transfemoral amputees increases which significantly modulates the spectral power of intrinsic cortical oscillations. Findings: Using the independent components from the sensorimotor areas and supplementary motor area (SMA), our results present a well-pronounced drop of alpha spectral power at sensorimotor area contralateral to sound limb of amputees in comparison to SMA and the sensorimotor area contralateral to prosthetic limb. Following this, we found significantly higher (p < 0.05) limit of stability (LOS) at their sound limb than at the prosthetic limb. Healthy individuals have similar contribution from both the limbs and the EEG alpha spectral power was similar across the three regions of the cortex during the balance control task as expected. Overall, a decent correlation was found between the LOS and alpha spectral power in both amputee and healthy individuals (Pearson’s correlation coefficient > 0.5). Interpretation: By externally stimulating the highlighted cortical regions, neuroplasticity might be promoted which helps to reduce the training time for the efficient rehabilitation of amputees. Additionally, this new knowledge might benefit in the designing and development of innovative interventions to prevent falls due to lower limb amputation.

2

Detection of eye closing/opening from EOG and its application in robotic arm control

Sharma Kamal, Jain Neeraj, Pal Prabir K.

Biocybernetics and Biomedical Engineering

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2020

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Vol. 40, no. 1

173--186

EN

Detection of eye closing/opening from alpha-blocking in the EEG of occipital region has been used to build human-machine interfaces. This paper presents an alternative method for detection of eye closing/opening from EOG signals in an online setting. The accuracies for correct detection of eye closing and opening operations with the proposed techniques were found to be 95.6% and 91.9% respectively for 8 healthy subjects. These techniques were then combined with the detection of eye blinks, the accuracy of which turned out to be 96.9%. This was then used to build an interface for robotic arm control for a pick and place task. The same task was also carried out using a haptic device as a master. The speed and accuracy for these two methods were then compared to assess quantitatively the ease of using this interface. It appears that the proposed interface will be very useful for persons with neurodegenerative disorders who can perform eye closing/opening and eye blinks.

3

Comparison of different feature extraction methods for EEG-based emotion recognition

Nawaz Rab, Cheah Kit Hwa, Nisar Humaira, Yap Vooi Voon

Biocybernetics and Biomedical Engineering

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2020

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Vol. 40, no. 3

910--926

EN

EEG-based emotion recognition is a challenging and active research area in affective computing. We used three-dimensional (arousal, valence and dominance) model of emotion to recognize the emotions induced by music videos. The participants watched a video (1 min long) while their EEG was recorded. The main objective of the study is to identify the features that can best discriminate the emotions. Power, entropy, fractal dimension, statistical features and wavelet energy are extracted from the EEG signals. The effects of these features are investigated and the best features are identified. The performance of the two feature selection methods, Relief based algorithm and principle component analysis (PCA), is compared. PCA is adopted because of its improved performance and the efficacies of the features are validated using support vector machine, K-nearest neighbors and decision tree classifiers. Our system achieves an overall best classification accuracy of 77.62%, 78.96% and 77.60% for valence, arousal and dominance respectively. Our results demonstrated that time-domain statistical characteristics of EEG signals can efficiently discriminate different emotional states. Also, the use of three-dimensional emotion model is able to classify similar emotions that were not correctly classified by two-dimensional model (e.g. anger and fear). The results of this study can be used to support the development of real-time EEG-based emotion recognition systems.

4

Improved robust weighted averaging for event-related potentials in EEG

Kotowski Krzysztof, Stapor Katarzyna, Leski Jacek

Biocybernetics and Biomedical Engineering

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2019

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Vol. 39, no. 4

1036--1046

EN

The aim of this study was to improve the robust weighted averaging based on criterion function minimization and assess its effectiveness for extracting event-related brain potentials (ERP) from electroencephalographic (EEG) recordings. The areas of improvement include significantly lower averaging error (45% lower RMSE and 37% lower maximum difference than for original implementation) and increased robustness to local minima, strong outliers and corrupted epochs common to real-life EEG signals, especially from low-cost devices. Our proposed procedure was tested on two datasets, one artificially generated for purposes of this study (including different noise sources) and one real-life dataset collected with Emotiv EPOCþ. The lower error results mainly from more effective rejection (lowering the weights) of corrupted epochs by integrating the correlation-based weighting. The advantages of our method over pure correlation-based weighting are lower RMSE (up to two times) and robustness to the algorithm initialization and strong outliers. The performance of the methods was measured using bootstrap testing to avoid dependency of results on data. It shows that our improvements lead to significantly lower error, especially when the EEG signal is not filtered. The values of the parameters were adjusted for EEG signals but they can easily be incorporated in other repetitive electrophysiological measurement techniques.

5

Validation of Emotiv EPOC+ for extracting ERP correlates of emotional face processing

Kotowski K., Stapor K., Leski J., Kotas M.

Biocybernetics and Biomedical Engineering

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2018

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Vol. 38, no. 4

773--781

EN

The article presents our proposed adaptation of the commercially available Emotiv EPOC+ EEG headset for neuroscience research based on event-related brain potentials (ERP). It solves Emotiv EPOC+ synchronization problems (common to most low-cost systems) by applying our proposed stimuli marking circuit. The second goal was to check the capabilities of our modification in neuroscience experiments on emotional face processing. Results of our experiment show the possibility of measuring small differences in the early posterior negativity (EPN) component between neutral and emotional (angry/happy) stimuli consistently with previous works using research-grade EEG systems.

6

The ADHD effect on the actions obtained from the EEG signals

Yaghoobi Karimui R., Azadi S., Keshavarzi P.

Biocybernetics and Biomedical Engineering

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2018

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Vol. 38, no. 2

425--437

EN

Attention-deficit/hyperactivity disorder (ADHD) is an important challenge in studies of children's ethology that unbalances the opposite behaviors for creating inattention along with or without hyperactivity. Nevertheless, most studies on the ADHD children, which employed the EEG signals for analyzing the ADHD influence on the brain activities, consid- ered the EEG signals as a random or chaotic process without considering the role of these opposites in the brain activities. In this study, we considered the EEG signals as a biotic process according to these opposites and examined the ADHD effect on the brain activity by defining the dual sets of transitions between states in the complement plots of quantized EEG segments. The results of this study generally indicated that the complement plots of quantized EEG signal have a surprising regularity similar to the Mandala patterns compared to the chaotic processes. These results also indicated that the probability of occurrence of dual sets in the complement plots of ADHD children was averagely different ( p < 0.01) from that of healthy children, so that the SVM classifier developed by these probabilities could significantly separate the ADHD from healthy children (99.37% and 98.25% for training and testing sets, respectively). Therefore, the complement plots of quantized EEG signals rele-vant to the ADHD children not only can quantify informational opposition caused by inattention, hyperactivity and impulsivity, but also these plots can provide remarkable information for developing new diagnostic and therapeutic techniques.

7

Monitoring CFM and brain diagnostics of premature infants

Niedbalski P., Ogniewski P., Karpiński Ł., Filipowicz S. F.

Przegląd Elektrotechniczny

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2015

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R. 91, nr 7

5-7

EN

The paper presents the application of the transforming EEG signal into highly compressed CFM record in clinical useful. A lot of information created by EEG record (hundreds of samples per second per each channel) and which require interpreting with specialist knowledge are transformed into time compressed. This paper presents monitoring and brain diagnostics of premature infants. Is described a general principle CFM methods and mechanisms used for therapy.

PL

W pracy przedstawiono zastosowania wysokiej kompresji sygnałów EEG po transformacji w postaci impedancyjnej w badaniach przewietrzania klatki piersiowej. Określono podstawowe parametry obrazów medycznych uzyskiwanych metodą tomografii impedancyjnej. Podano preferowane metody rozwiązania zagadnienia odwrotnego oparte o algorytmy liniowe wykorzystujące aproksymację badanych obiektów przy zastosowaniu metody elementów skończonych.

8

Zastosowanie klasteryzacji do automatycznej detekcji artefaktów mrugania oczami w sygnale EEG

Kołodziej M., Majkowski A., Rak R.J.

Przegląd Elektrotechniczny

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2014

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R. 90, nr 8

175-177

PL

W artykule zaprezentowano autorską metodę detekcji krótkich fragmentów sygnału EEG, które zawierają artefakty mrugania oczami. Autorzy, do automatycznego wskazania fragmentów sygnału EEG zawierającego artefakty mrugania oczami wykorzystali uczenie bez nadzoru (algorytm K-means) oraz cechy sygnału takie jak amplituda i statystyki wyższych rzędów. Wyniki działania algorytmu są bardzo zadowalające. Trafność detekcji wynosi 98%. Algorytm pozwala wykluczyć zaznaczone fragmenty sygnału i nie poddawać ich dalszej analizie. Takie podejście zdaniem autorów przysłuży się do efektywniejszego wykorzystania sygnałów EEG.

EN

The paper presents an original method for the detection of short fragments of the EEG signal, which contain eye blinking artifacts. The authors, to automatically identify fragments the EEG signal containing eye blinking artifacts, used unsupervised learning (K-means algorithm) and the signal features such as amplitude and higher-order statistics. The obtained results are very satisfactory. Accuracy of detection is 98%. The algorithm enables to exclude selected fragments of the signal and not analyze them further. Such an approach, according to the authors, enable more efficient use of EEG signals.

9

The application of electroencephalographic signals in the aspect of controlling a mobile robot for measurements of partial discharges

Paszkiel Sz., Błachowicz A.

Przegląd Elektrotechniczny

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2010

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R. 86, nr 8

303-306

EN

The article presents applications of modern computer devices in the aspect of controlling a mobile robot for measurements of partial discharges. Direct controlling of differerent devices by means of thoughts is becoming more and more popular nowadays. An appropriate filtration of disruptive artefacts, which accompany an environment close to the place where measurements of partial discharges appear, is necessary.

PL

Artykuł przedstawia problem zastosowania nowoczesnych narzędzi informatycznych w aspekcie sterowania robotem mobilnym do pomiaru wyładowań niezupełnych. Bezpośrednie sterowanie różnymi urządzeniami za pomocą myśli staje się w obecnej rzeczywistości coraz bardziej popularne. Konieczna jest odpowiednia filtracja artefaktów zakłócających towarzyszącym środowisku w pobliżu, jakiego następuje pomiar wyładowań niezupełnych.

10

Układ elektroencefalografu przenośnego do lokalizacji aktywności elektrycznej

Nita K., Filipowicz S.

Przegląd Elektrotechniczny

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2007

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R. 83, nr 12

112-113

PL

W pracy przedstawiono zbudowany przenośny wielopunktowy układ pomiarowy w oparciu o projekt OpenEEG z zastosowaniem do elektroencefalografii. Do budowy wykorzystano przetworniki analogowo-cyfrowe o rozdzielczości 0,5 uV. Wykonano pomiary aktywności obiektu o kształcie odpowiadającym rzeczywistej głowie człowieka dokonując następnie lokalizacji źródła.

EN

The portable multichanel measuring system which was build basing on the project OpenEEG was presented. This system was used to electroencephalography. To construction of this system the analog to digital converter was used with 0,5 uV resolution.