Аналіз електроенцефалограм людини, отриманих під час емоційних стимулів

Об’єктом розгляду є електрична активність головного мозку людини. Предмет роботи – методи аналізу електроенцефалограм під час дії різноманітних стимулів. Метою роботи є вивчення природи виникнення електричних сигналів мозку, методи їх реєстрації та аналізу для дослідження реакції на візуальні емоційнонавантажені стимули. У першому розділі описуються загальні поняття про природу виникнення електричного сигналу мозку людини, а також нейрофізіологічні ознаки присутності різних частотних складових сигналу за певних станів людини. У другому розділі наведено принципи реєстрації сигналів електроенцефалограми (ЕЕГ) та описано пристрої, що здатні це виконувати. Також розглянуто опис основної системи накладання сенсорів (електродів) на голову людини. В кінці розділу наведено приклад компактного 8-канального енцефалографа власної розробки, що здатен реєструвати сигнали ЕЕГ та передавати їх по бездротовому зв’язку на мобільні прилади (смартфон, планшет). Третій розділ описує основні математичні методи аналізу ЕЕГ сигналів. Основними є методи спектрального та вейвлет-аналізу та аналіз детрендових коливань, за допомогою яких можна отримати детальне представлення про роботу мозку, шляхом виявлення різноманітних патернів в частотних діапазонах. У четвертому розділі описується практичне застосування методів спектрального та Detrended Moving Average аналізів на експериментальній базі даних ЕЕГ для 48 здорових волонтерів, запис ЕЕГ для яких проводився під час демонстрації певних емоційнонавантажених візуальних стимулів. Також в цьому розділі наведені результати виконаного аналізу разом з їх нейрофізіологічним тлумаченням.An important place in the study of brain activity is occupied by the study of its electrical potentials. Electroencephalography (EEG) is a method of graphical recording of brain biopotentials, which allows analyzing its physiological maturity and condition, the presence of focal lesions, general brain disorders and their nature. It consists of recording and analyzing the total bioelectric activity of the brain — an electroencephalogram (EEG). EEG can be taken from the scalp, from the surface of the brain, as well as from deep brain structures. As a rule, an electroencephalogram is understood as a surface recording, that is, made from the intact head surface. EEG is most often used to diagnose epilepsy, which causes EEG disorders. It is also used to diagnose sleep disorders, deep anesthesia, coma, encephalopathy, and brain death. EEG was used as the main method for diagnosing tumors, stroke, and other focal brain diseases, but when it became possible to obtain high-resolution anatomical images using magnetic resonance imaging (MRI) and computed tomography (CT) techniques, the use of EEG declined. Despite its limited resolution, the EEG continues to be a valuable tool for research and diagnosis. The object of consideration is the electrical activity of the human brain. The subject of the work is methods of analyzing electroencephalograms during the action of various stimuli. The aim of the work is to study the nature of the occurrence of electrical signals of the brain, methods of their registration and analysis to study the response to visual emotional stimuli. The first chapter describes general concepts about the nature of the occurrence of an electrical signal in the human brain, as well as neurophysiological signs of the presence of various frequency components of the signal in certain human states. The second chapter describes the principles of recording electroencephalogram signals and describes devices that can perform this. The description of the main system for applying sensors (electrodes) to the human head is also considered. At the end of the section, an example of a compact 8-channel encephalograph of our own design is given, which is able to register EEG signals and transmit them wirelessly to mobile devices (smartphone, tablet). The third section describes the basic mathematical methods for analyzing EEG signals. The main methods are spectral and wavelet analysis and detrended oscillation analysis, which can be used to get a detailed picture of brain function by identifying various patterns in frequency ranges. The fourth section describes the practical application of spectral and Detrended Moving Average analysis methods on an experimental EEG database. Here, initially the EEG records were made for 48 healthy volunteers whose EEG recording was performed while demonstrating certain emotionally loaded visual stimuli. Stimuli were selected from the International Affective Pictures System (IAPS) based on their average emotional valence values. In order to assess the induced changes of the brain’s electrical activity, the EEG-bands were subdivided in a following way: 1 [3.5, 5.8], 2 [5.9, 7.4], 1 [7.5, 9.4], 2 [9.5, 10.7], 3 [10.8, 13.5], 1 [13.6, 25], 2 [25.1, 40] Hz. As a result, Power Spectral Density (PSD) were visualized as a map on the schematic figure of the head used to render the statistical significance test, demonstrating that variations in powers for our signals were caused by non-identical forms of visual effect rather than being an accident. These details were also shown in the heads charts. The study of changes in power spectrum density showed neurodynamics triggered by visual stimulation experience. However, when comparing PSD values obtained during the presentation of the first and second neutral series, it was discovered that when processing neutral images followed by negative stimuli, a well-defined activation focus developed in the left parietal region of the cortex in the 2 subband. The DMA algorithm revealed statistically important variations in the left temporal and frontal regions of the cortex, which were marked by more pronounced activation during the perception of neutral faces in the presence of positive images. This may be the start of a new path of improved inner focus and meaningful emotional experiences. As a result, the sex-related aspects of the emotional valence effect on neutral face perception were discovered by analyzing EEG-based brain neurodynamics in the mechanism in perception in human faces of various modalities. The stimulation of two large cognitive networks in the brain: mental or theta-network and cognitive beta- network, was the key distinction

Algoritmi per la reiezione dei disturbi nei sistemi di acquisizione dei segnali EEG basati sulla tecnica del Compressed Sensing

Il Compressed Sensing è emerso recentemente come un strumento che simultaneamente acquisisce e comprime segnali analogici su dispositivi a basso consumo. Rispetto alla sua caratterizzazione classica (CS), il sistema di acquisizione può essere adattato alla classe di segnali in ingresso (R-CS) ed è inoltre possibile garantire una buona reiezione dei disturbi (R-CSd). Quest’ultimo modello si basa sulla risoluzione di due problemi di ottimizzazione con un numero di variabili potenzialmente elevato. Il primo dei quali ha una risoluzione analitica, il secondo necessita di un risolutore software che, per un numero elevato di variabili, potrebbe non arrivare ad una soluzione in tempi ragionevoli. Il lavoro che viene presentato supera questo problema con un algoritmo scritto ad hoc che sfrutta l’applicazione del metodo del Gradiente Proiettato Discendente con Proiezioni Alternate, attraverso il quale si riesce a ridurre drasticamente il tempo richiesto dalla CPU per ottenere una soluzione, anche per un numero elevato di variabili. A conclusione del lavoro si è applicato questo metodo alla classe di segnali EEG con l’intento di attuare una reiezione dei disturbi a bassissima frequenza direttamente nello stadio di compressione. Il lavoro mostra la catena di elaborazione per il CS, il R-CS e per R-CSd. I casi analizzati sono: adattamento sulla classe di segnali EEG, adattamento sul singolo canale e divisione dei canali in due distinti cluster. Quello che si dimostra è che l’algoritmo R-CSd mostra le stesse performance di R-CS in tutti e tre i casi, facendo a meno dell’utilizzo di un filtro passa alto. La ricostruzione dei canali con la caratterizzazione dell’intera classe di segnali o con l’uso dei due cluster non si discosta troppo da quanto osservato per l’adattamento sul singolo canale con una conseguente semplificazione del sistema di acquisizione proposto

A Novel Power-Efficient Wireless Multi-channel Recording System for the Telemonitoring of Electroencephalography (EEG)

This research introduces the development of a novel EEG recording system that is modular, batteryless, and wireless (untethered) with the supporting theoretical foundation in wireless communications and related design elements and circuitry. Its modular construct overcomes the EEG scaling problem and makes it easier for reconfiguring the hardware design in terms of the number and placement of electrodes and type of standard EEG system contemplated for use. In this development, portability, lightweight, and applicability to other clinical applications that rely on EEG data are sought. Due to printer tolerance, the 3D printed cap consists of 61 electrode placements. This recording capacity can however extend from 21 (as in the international 10-20 systems) up to 61 EEG channels at sample rates ranging from 250 to 1000 Hz and the transfer of the raw EEG signal using a standard allocated frequency as a data carrier. The main objectives of this dissertation are to (1) eliminate the need for heavy mounted batteries, (2) overcome the requirement for bulky power systems, and (3) avoid the use of data cables to untether the EEG system from the subject for a more practical and less restrictive setting. Unpredictability and temporal variations of the EEG input make developing a battery-free and cable-free EEG reading device challenging. Professional high-quality and high-resolution analog front ends are required to capture non-stationary EEG signals at microvolt levels. The primary components of the proposed setup are the wireless power transmission unit, which consists of a power amplifier, highly efficient resonant-inductive link, rectification, regulation, and power management units, as well as the analog front end, which consists of an analog to digital converter, pre-amplification unit, filtering unit, host microprocessor, and the wireless communication unit. These must all be compatible with the rest of the system and must use the least amount of power possible while minimizing the presence of noise and the attenuation of the recorded signal A highly efficient resonant-inductive coupling link is developed to decrease power transmission dissipation. Magnetized materials were utilized to steer electromagnetic flux and decrease route and medium loss while transmitting the required energy with low dissipation. Signal pre-amplification is handled by the front-end active electrodes. Standard bio-amplifier design approaches are combined to accomplish this purpose, and a thorough investigation of the optimum ADC, microcontroller, and transceiver units has been carried out. We can minimize overall system weight and power consumption by employing battery-less and cable-free EEG readout system designs, consequently giving patients more comfort and freedom of movement. Similarly, the solutions are designed to match the performance of medical-grade equipment. The captured electrical impulses using the proposed setup can be stored for various uses, including classification, prediction, 3D source localization, and for monitoring and diagnosing different brain disorders. All the proposed designs and supporting mathematical derivations were validated through empirical and software-simulated experiments. Many of the proposed designs, including the 3D head cap, the wireless power transmission unit, and the pre-amplification unit, are already fabricated, and the schematic circuits and simulation results were based on Spice, Altium, and high-frequency structure simulator (HFSS) software. The fully integrated head cap to be fabricated would require embedding the active electrodes into the 3D headset and applying current technological advances to miniaturize some of the design elements developed in this dissertation

Low cost mobile EEG for characterization of cortical auditory responses

We report a low cost mobile EEG system for characterizing cortical auditory responses. The system is built using commercial off-the-shelf components and each unit costs less than $200. It measures seven EEG channels plus one audio channel (envelope only), and communicates the data to external devices via Bluetooth. A novel implementation was pursued in order to support local signal compression using compressed sensing. At the same time, it provides a low cost solution that is useful for recording cortical auditory responses and extracting clinically relevant features of the waveform. This system has been designed with the eventual goal of long term monitoring of the brain activity of schizophrenic patients outside a clinical setting, in order to better understand auditory hallucinations and manage their ongoing treatment. In this preliminary study we obtained simultaneous audio and cortical recordings of evoked auditory responses from normal healthy subjects wearing the EEG for several hours in duration. We report evoked auditory responses for 2 Hz and 40 Hz click trains. We also report alpha wave responses, demonstrating stable and high quality recordings over a five hour period

Low cost mobile EEG for characterization of cortical auditory responses

We report a low cost mobile EEG system for characterizing cortical auditory responses. The system is built using commercial off-the-shelf components and each unit costs less than $200. It measures seven EEG channels plus one audio channel (envelope only), and communicates the data to external devices via Bluetooth. A novel implementation was pursued in order to support local signal compression using compressed sensing. At the same time, it provides a low cost solution that is useful for recording cortical auditory responses and extracting clinically relevant features of the waveform. This system has been designed with the eventual goal of long term monitoring of the brain activity of schizophrenic patients outside a clinical setting, in order to better understand auditory hallucinations and manage their ongoing treatment. In this preliminary study we obtained simultaneous audio and cortical recordings of evoked auditory responses from normal healthy subjects wearing the EEG for several hours in duration. We report evoked auditory responses for 2 Hz and 40 Hz click trains. We also report alpha wave responses, demonstrating stable and high quality recordings over a five hour period