National Conference on Electrical and Computer Engineering

The objective of the present study was to investigate the possible relationship between bispectral parameters extracted from surface EMG (sEMG) signals and muscle force and fatigue. Our hypothesis was that changes in motor unit recruitment during muscle contraction and fatigue, affect sEMG distribution and the degree of complexity and irregularity in the muscle. Thus, four features based on higher order spectra and cumulants were extracted from sEMG signal, recorded from biceps brachii muscle of a healthy female volunteer during rest, sustained (fatiguing) 50% MVC, 100% MVC and recovery. Results obtained from weighted center of bispectrum (WCOB) analysis showed that the values of f1m and f2m were higher during rest and recovery states, while they decreased during MVCs. However, when fatigue occurred, these parameters increased slightly, again. Moreover, entropy features, namely NBE and NBSE decreased with contraction compared to rest and recovery states, indicating less complexity of time series during MVCs. However, the changes were not significant during fatigue and during changes in MVC levels from 50% to 100%. On the other hand, test of non-Gaussianity based on negentropy showed the reverse pattern of WCOB, NBE and NBSE. In addition, contour maps of bispectrum enabled us to visually differentiate each trial. </p

Cerebral Synchrony Assessment Tutorial: A General Review on Cerebral Signals' Synchronization Estimation Concepts and Methods

The human brain is ultimately responsible for all thoughts and movements that the body produces. This allows humans to successfully interact with their environment. If the brain is not functioning properly many abilities of human can be damaged. The goal of cerebral signal analysis is to learn about brain function. The idea that distinct areas of the brain are responsible for specific tasks, the functional segregation, is a key aspect of brain function. Functional integration is an important feature of brain function, it is the concordance of multiple segregated brain areas to produce a unified response. There is an amplified feedback mechanism in the brain called reentry which requires specific timing relations. This specific timing requires neurons within an assembly to synchronize their firing rates. This has led to increased interest and use of phase variables, particularly their synchronization, to measure connectivity in cerebral signals. Herein, we propose a comprehensive review on concepts and methods previously presented for assessing cerebral synchrony, with focus on phase synchronization, as a tool for brain connectivity evaluation

Application of Higher-Order Statistics and Subspace-Based Techniques to the Analysis and Diagnosis of Electrocardiogram Signals

The first and main contribution of this research work is the higher-order statistics (HOS)-based non-linear analysis and subsequent diagnosis of abnormal electrocardiogram (ECG) signals, particularly myocardial ischaemia. In the time domain; the second-, third-, and the fourth-order cumulants have been used in the analysis. In the frequency domain; up to the tenth-order polyspectra have been exploited. This HOS-based analysis of normal and ischaemic electrocardiogram signals has led to the identification of certain key discriminant features for the two physiological states of the heart. These features are then fed to different backpropagation-based multiple layer perceptrons for classification. The second contribution is a proposed new methodology to discriminate patients with angina pectoris or with old myocardial infarction (MI) during the first 60 seconds of stress test (or in some cases using rest ECG). It is based on the pseudo-spectral Multiple Signal Classification (MUSIC) and has the potential of being highly sensitive diagnostic signal processing tool. The third contribution is the development of a novel higher-order statistics, high-resolution estimator for quadratically coupled frequencies based on subspace spectral estimation. Extensive studies of cumulants, bispectra and bicoherence-squared of normal and ischaemic ECG signals collected from MIT and ST-T European databases has enabled us to see key discriminant features in both the third- and fourth-order cumulant domains. In the frequency domain, the polyspectral study has been extended to the lOth-order poly spectra. By calculating one-dimensional polyspectrum slices using an algorithm developed by Zhou and Giannakis (1995) a considerable reduction in the CPU time has been achieved. Furthermore, Zhou’s algorithm has been further extended to estimate the polycoherency slices which are used to characterise non-linearities in normal and ischaemic ECG signals. An important finding in this thesis is the decrease of the order of non-linearity representing the electrocardiogram signals of ischaemic patients. This thesis also includes the results of a pilot study involving eighteen healthy subjects (MIT database) and confirmed that the ECG signal is non-Gaussian, cyclostationary and quasi periodic. Combined spectral and bispectral analysis of the signal revealed that there are unique harmonic characteristics for the P-wave, QRS complex and T-wave and other frequencies due to harmonic interactions. In this work three linear and one non-linear adaptive filtering/predictions techniques have been applied to noisy ECG signals and their respective performances appraised. It is shown that the Kalman filter gives the best mean-square error MSE error but its comparatively long execution time and problems arising from ill-conditioning of the state-error covariance matrix render it of limited use in ECG applications. It is also shown that the LMS-based quadratic and cubic Volterra filters are the most superior for the ECG signal prediction. For ECG classifications; three multi-layer perceptrons employing back-propagation and modified back-propagation algorithms, and using two sets from the higher-order most discriminant features as their inputs, have yielded fairly high classification rates

Brain Computer Interfaces and Emotional Involvement: Theory, Research, and Applications

This reprint is dedicated to the study of brain activity related to emotional and attentional involvement as measured by Brain–computer interface (BCI) systems designed for different purposes. A BCI system can translate brain signals (e.g., electric or hemodynamic brain activity indicators) into a command to execute an action in the BCI application (e.g., a wheelchair, the cursor on the screen, a spelling device or a game). These tools have the advantage of having real-time access to the ongoing brain activity of the individual, which can provide insight into the user’s emotional and attentional states by training a classification algorithm to recognize mental states. The success of BCI systems in contemporary neuroscientific research relies on the fact that they allow one to “think outside the lab”. The integration of technological solutions, artificial intelligence and cognitive science allowed and will allow researchers to envision more and more applications for the future. The clinical and everyday uses are described with the aim to invite readers to open their minds to imagine potential further developments

AN INVESTIGATION OF ELECTROMYOGRAPHIC (EMG) CONTROL OF DEXTROUS HAND PROSTHESES FOR TRANSRADIAL AMPUTEES

In reference to IEEE copyrighted material which is used with permission in this thesis, the IEEE does not endorse any of Plymouth University's products or services.There are many amputees around the world who have lost a limb through conflict, disease or an accident. Upper-limb prostheses controlled using surface Electromyography (sEMG) offer a solution to help the amputees; however, their functionality is limited by the small number of movements they can perform and their slow reaction times. Pattern recognition (PR)-based EMG control has been proposed to improve the functional performance of prostheses. It is a very promising approach, offering intuitive control, fast reaction times and the ability to control a large number of degrees of freedom (DOF). However, prostheses controlled with PR systems are not available for everyday use by amputees, because there are many major challenges and practical problems that need to be addressed before clinical implementation is possible. These include lack of individual finger control, an impractically large number of EMG electrodes, and the lack of deployment protocols for EMG electrodes site selection and movement optimisation. Moreover, the inability of PR systems to handle multiple forces is a further practical problem that needs to be addressed. The main aim of this project is to investigate the research challenges mentioned above via non-invasive EMG signal acquisition, and to propose practical solutions to help amputees. In a series of experiments, the PR systems presented here were tested with EMG signals acquired from seven transradial amputees, which is unique to this project. Previous studies have been conducted using non-amputees. In this work, the challenges described are addressed and a new protocol is proposed that delivers a fast clinical deployment of multi-functional upper limb prostheses controlled by PR systems. Controlling finger movement is a step towards the restoration of lost human capabilities, and is psychologically important, as well as physically. A central thread running through this work is the assertion that no two amputees are the same, each suffering different injuries and retaining differing nerve and muscle structures. This work is very much about individualised healthcare, and aims to provide the best possible solution for each affected individual on a case-by-case basis. Therefore, the approach has been to optimise the solution (in terms of function and reliability) for each individual, as opposed to developing a generic solution, where performance is optimised against a test population. This work is unique, in that it contributes to improving the quality of life for each individual amputee by optimising function and reliability. The main four contributions of the thesis are as follows: 1- Individual finger control was achieved with high accuracy for a large number of finger movements, using six optimally placed sEMG channels. This was validated on EMG signals for ten non-amputee and six amputee subjects. Thumb movements were classified successfully with high accuracy for the first time. The outcome of this investigation will help to add more movements to the prosthesis, and reduce hardware and computational complexity. 2- A new subject-specific protocol for sEMG site selection and reliable movement subset optimisation, based on the amputee’s needs, has been proposed and validated on seven amputees. This protocol will help clinicians to perform an efficient and fast deployment of prostheses, by finding the optimal number and locations of EMG channels. It will also find a reliable subset of movements that can be achieved with high performance. 3- The relationship between the force of contraction and the statistics of EMG signals has been investigated, utilising an experimental design where visual feedback from a Myoelectric Control Interface (MCI) helped the participants to produce the correct level of force. Kurtosis values were found to decrease monotonically when the contraction level increased, thus indicating that kurtosis can be used to distinguish different forces of contractions. 4- The real practical problem of the degradation of classification performance as a result of the variation of force levels during daily use of the prosthesis has been investigated, and solved by proposing a training approach and the use of a robust feature extraction method, based on the spectrum. The recommendations of this investigation improve the practical robustness of prostheses controlled with PR systems and progress a step further towards clinical implementation and improving the quality of life of amputees. The project showed that PR systems achieved a reliable performance for a large number of amputees, taking into account real life issues such as individual finger control for high dexterity, the effect of force level variation, and optimisation of the movements and EMG channels for each individual amputee. The findings of this thesis showed that the PR systems need to be appropriately tuned before usage, such as training with multiple forces to help to reduce the effect of force variation, aiming to improve practical robustness, and also finding the optimal EMG channel for each amputee, to improve the PR system’s performance. The outcome of this research enables the implementation of PR systems in real prostheses that can be used by amputees.Ministry of Higher Education and Scientific Research and Baghdad University- Baghdad/Ira

Evaluation of EEG-based depth of anaesthesia monitoring

In 2001 a University of Bristol team patented a novel data reduction method of the EEG for characterising categorical changes in consciousness. After pre-whitening the EEG signal with Gaussian white noise a parametric spectral estimation technique was applied. Two frequency domain indices were then proposed: the relative power found between 8Hz to 12Hz and 0.5Hz to 32Hz termed the 'alpha index', and the relative power between 0.5Hz to 4Hz and 0.5Hz to 32Hz termed the 'delta index'. The research and development of a precision EEG monitoring device designed to embody the novel algorithm is described in this thesis. The efficacy of the technique was evaluated using simulated and real EEG data recorded during Propofol anaesthesia. The simulated data showed improvements could be made to the patented method. Real EEG data collected whilst patients were wakeful and data from patients unresponsive to noxious stimuli were cleaned of obvious artefacts and analysed using the proposed algorithm. A Bayesian diagnostic test showed the alpha index had 65% sensitivity and selectivity to patient state. The delta index showed 72% sensitivity and selectivity. Taking a pragmatic approach, the literature is reviewed in this thesis to evaluate the use of EEG in depth of anaesthesia monitoring. Pertinent aspects of the sciences are profiled to identify physiological links to the characteristics of the EEG signal. Methods of data reduction are also reviewed to identify useful features and possible sources of error. In conclusion it is shown that the proposed indices do not provide a robust measure of depth of anaesthesia. An approach for further research is proposed based on the review work.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Studies on the assessment of the adequacy of anesthesia

Several hypnosis monitoring systems based on the processed electroencephalogram (EEG) have been developed for use during general anesthesia. The assessment of the analgesic component (antinociception) of general anesthesia is an emerging field of research. This study investigated the interaction of hypnosis and antinociception, the association of several physiological variables with the degree of intraoperative nociception, and aspects of EEG Bispectral Index Scale (BIS) monitoring during general anesthesia. In addition, EEG features and heart rate (HR) responses during desflurane and sevoflurane anesthesia were compared. A propofol bolus of 0.7 mg/kg was more effective than an alfentanil bolus of 0.5 mg in preventing the recurrence of movement responses during uterine dilatation and curettage (D C) after a propofol-alfentanil induction, combined with nitrous oxide (N2O). HR and several HR variability-, frontal electromyography (fEMG)-, pulse plethysmography (PPG)-, and EEG-derived variables were associated with surgery-induced movement responses. Movers were discriminated from non-movers mostly by the post-stimulus values per se or normalized with respect to the pre-stimulus values. In logistic regression analysis, the best classification performance was achieved with the combination of normalized fEMG power and HR during D C (overall accuracy 81%, sensitivity 53%, specificity 95%), and with the combination of normalized fEMG-related response entropy, electrocardiography (ECG) R-to-R interval (RRI), and PPG dicrotic notch amplitude during sevoflurane anesthesia (overall accuracy 96%, sensitivity 90%, specificity 100%). ECG electrode impedances after alcohol swab skin pretreatment alone were higher than impedances of designated EEG electrodes. The BIS values registered with ECG electrodes were higher than those registered simultaneously with EEG electrodes. No significant difference in the time to home-readiness after isoflurane-N2O or sevoflurane-N2O anesthesia was found, when the administration of the volatile agent was guided by BIS monitoring. All other early and intermediate recovery parameters were also similar. Transient epileptiform EEG activity was detected in eight of 15 sevoflurane patients during a rapid increase in the inspired volatile concentration, and in none of the 16 desflurane patients. The observed transient EEG changes did not adversely affect the recovery of the patients. Following the rapid increase in the inhaled desflurane concentration, HR increased transiently, reaching its maximum in two minutes. In the sevoflurane group, the increase was slower and more subtle. In conclusion, desflurane may be a safer volatile agent than sevoflurane in patients with a lowered seizure threshold. The tachycardia induced by a rapid increase in the inspired desflurane concentration may present a risk for patients with heart disease. Designated EEG electrodes may be superior to ECG electrodes in EEG BIS monitoring. When the administration of isoflurane or sevoflurane is adjusted to maintain BIS values at 50-60 in healthy ambulatory surgery patients, the speed and quality of recovery are similar after both isoflurane-N2O and sevoflurane-N2O anesthesia. When anesthesia is maintained by the inhalation of N2O and bolus doses of propofol and alfentanil in healthy unparalyzed patients, movement responses may be best avoided by ensuring a relatively deep hypnotic level with propofol. HR/RRI, fEMG, and PPG dicrotic notch amplitude are potential indicators of nociception during anesthesia, but their performance needs to be validated in future studies. Combining information from different sources may improve the discrimination of the level of nociception.Useita aivosähkökäyrään (EEG) perustuvia unen syvyyden valvontamenetelmiä on kehitetty yleisanestesian aikana käytettäväksi. Kudosvaurion aiheuttamia ärsykkeitä vaimentavan yleisanestesian osan arviointimenetelmien tutkimus on alkamassa. Tässä väitöskirjatyössä tutkittiin unen syvyyden ja kudosvaurion aiheuttamien ärsykkeiden vaimennuksen vuorovaikutusta, useiden elimistön toimintaa kuvaavien muuttujien ja kudosvaurion aiheuttaman ärsytyksen suhdetta sekä EEG:n bispektraali-indeksin (BIS) käyttöä yleisanestesian valvonnassa. Lisäksi verrattiin desfluraani- ja sevofluraanianestesiaan liittyviä EEG-muutoksia ja sykevasteita. Kun anestesia oli aloitettu propofolilla, alfentaniililla ja typpioksiduulilla (N2O), propofoliannos 0.7 mg/kg esti liikevasteiden toistumista kohdun kaavinnan aikana tehokkaammin kuin alfentaniiliannos 0.5 mg. Sydämen syke ja useat sykevaihtelusta, otsalihastoiminnasta, pulssiaallon mittauksesta ja EEG:sta johdetut muuttujat olivat yhteydessä leikkauksen aiheuttamiin liikevasteisiin. Pääsääntöisesti ärsykkeen jälkeen mitatut arvot sellaisenaan tai suhteutettuna ärsykettä edeltäviin arvoihin (normalisoituna) erottelivat liikkuvat potilaat liikkumattomista potilaista. Paras luokittelu saavutettiin kohdun kaavinnan aikana yhdistämällä tieto normalisoidusta otsalihastoiminnasta ja sykkeestä (herkkyys 53%, tarkkuus 95%), ja sevofluraanianestesian aikana yhdistämällä tieto normalisoidusta (otsalihastoimintaan liittyvästä) vaste-entropiasta, sykkeestä ja pulssiaallon muodosta (herkkyys 90%, tarkkuus 100%). Kun iho valmisteltiin vain pyyhkäisemällä alkoholilla, sydänsähkökäyrän (EKG) mittaukseen tarkoitettujen elektrodien sähköinen vastus oli suurempi kuin EEG:n mittaukseen tarkoitettujen elektrodien. EKG-elektrodeilla mitatut BIS-arvot olivat korkeampia kuin samanaikaisesti EEG-elektrodeilla mitatut BIS-arvot. Kun höyrystyviä anestesia-aineita annosteltiin BIS-arvojen mukaan, toipuminen oli yhtä nopeaa isofluraani-N2O-anestesian jälkeen kuin sevofluraani-N2O-anestesian jälkeen. Kun höyrystyvän anestesia-aineen pitoisuutta nostettiin nopeasti viiden minuutin ajaksi, ohimenevää epileptistä aivosähkötoimintaa havaittiin kahdeksalla viidestätoista sevofluraanipotilaasta, mutta ei yhdelläkään kuudestatoista desfluraanipotilaasta. Havaitut ohimenevät EEG-muutokset eivät vaikuttaneet haitallisesti potilaiden toipumiseen. Desfluraanipitoisuuden nopean noston jälkeen syke kiihtyi ohimenevästi ja saavutti huippunsa kahdessa minuutissa. Sevofluraaniryhmässä sykenousu oli hitaampi ja lievempi. Tulosten perusteella voidaan todeta, että desfluraani saattaa olla sevofluraania turvallisempi anestesia-aine potilailla joiden kouristuskynnys on alentunut. Nopeaan desfluraanipitoisuuden nostoon liittyvä sykenousu voi olla haitallinen sydänsairaille potilaille. EEG-elektrodit ovat BIS-mittauksessa parempia kuin halvemmat EKG-elektrodit. Kun höyrystyvä anestesia-aine annostellaan siten että BIS-arvo pysyy välillä 50-60, toipuminen on samankaltainen sekä isofluraani-N2O- että sevofluraani-N2O-anestesian jälkeen terveillä päiväkirurgisilla potilailla. Kun anestesiaa ylläpidetään N2O:lla sekä propofoli- ja alfentaniiliannoksilla terveillä potilailla, joiden lihastoimintaa ei ole lamattu, liikevasteita estetään mahdollisesti parhaiten pitämällä uni verrattain syvänä propofolin avulla. Sydämen syke, otsalihastoiminta ja pulssiaallon muoto saattavat soveltua kudosvaurion aiheut-taman ärsytyksen valvontaan anestesian aikana, mutta lisätutkimuksia aiheesta tarvitaan. Kudosvaurion aiheuttaman ärsytyksen arviointia voidaan mahdollisesti tarkentaa yhdistämällä tietoa useista elimistön toimintaa kuvaavista muuttujista