Continuous assessment of electrical epileptic activity in acute stroke.

OBJECTIVE: To determine the incidence and risk factors of electrical seizures and other electrical epileptic activity using continuous EEG (cEEG) in patients with acute stroke. METHODS: One hundred consecutive patients with acute stroke admitted to our stroke unit underwent cEEG using 10 electrodes. In addition to electrical seizures, repetitive focal sharp waves (RSHWs), repetitive focal spikes (RSPs), and periodic lateralized epileptic discharges (PLEDs) were recorded. RESULTS: In the 100 patients, cEEG was recorded for a mean duration of 17 hours 34 minutes (range 1 hour 12 minutes to 37 hours 10 minutes). Epileptic activity occurred in 17 patients and consisted of RSHWs in seven, RSPs in seven, and PLEDs in three. Electrical seizures occurred in two patients. On univariate Cox regression analysis, predictors for electrical epileptic activity were stroke severity (high score on the National Institutes of Health Stroke Scale) (hazard ratio [HR] 1.12; p = 0.002), cortical involvement (HR 5.71; p = 0.021), and thrombolysis (HR 3.27; p = 0.040). Age, sex, stroke type, use of EEG-modifying medication, and cardiovascular risk factors were not predictors of electrical epileptic activity. On multivariate analysis, stroke severity was the only independent predictor (HR 1.09; p = 0.016). CONCLUSION: In patients with acute stroke, electrical epileptic activity occurs more frequently than previously suspected.

On the inclusion of channel's time dependence in a hidden Markov model for blind channel estimation

In this paper, the theory of hidden Markov models (HMM) isapplied to the problem of blind (without training sequences) channel estimationand data detection. Within a HMM framework, the Baum–Welch(BW) identification algorithm is frequently used to find out maximum-likelihood (ML) estimates of the corresponding model. However, such a procedureassumes the model (i.e., the channel response) to be static throughoutthe observation sequence. By means of introducing a parametric model fortime-varying channel responses, a version of the algorithm, which is moreappropriate for mobile channels [time-dependent Baum-Welch (TDBW)] isderived. Aiming to compare algorithm behavior, a set of computer simulationsfor a GSM scenario is provided. Results indicate that, in comparisonto other Baum–Welch (BW) versions of the algorithm, the TDBW approachattains a remarkable enhancement in performance. For that purpose, onlya moderate increase in computational complexity is needed.

Blind channel estimation and data detection using hidden Markov models theory

In this correspondence, we propose applying the hiddenMarkov models (HMM) theory to the problem of blind channel estimationand data detection. The Baum–Welch (BW) algorithm, which is able toestimate all the parameters of the model, is enriched by introducingsome linear constraints emerging from a linear FIR hypothesis on thechannel. Additionally, a version of the algorithm that is suitable for timevaryingchannels is also presented. Performance is analyzed in a GSMenvironment using standard test channels and is found to be close to thatobtained with a nonblind receiver.

Asymptotic equivalence between the unconditional maximum likelihood and the square-law nonlinearity symbol timing estimation

This paper provides a systematic approach to theproblem of nondata aided symbol-timing estimation for linearmodulations. The study is performed under the unconditionalmaximum likelihood framework where the carrier-frequencyerror is included as a nuisance parameter in the mathematicalderivation. The second-order moments of the received signal arefound to be the sufficient statistics for the problem at hand and theyallow the provision of a robust performance in the presence of acarrier-frequency error uncertainty. We particularly focus on theexploitation of the cyclostationary property of linear modulations.This enables us to derive simple and closed-form symbol-timingestimators which are found to be based on the well-known squaretiming recovery method by Oerder and Meyr. Finally, we generalizethe OM method to the case of linear modulations withoffset formats. In this case, the square-law nonlinearity is foundto provide not only the symbol-timing but also the carrier-phaseerror.

System identification using a linear combination of cumulant slices

In this paper we develop a new linear approach to identify the parameters of a moving average (MA) model from the statistics of the output. First, we show that, under some constraints, the impulse response of the system can be expressed as a linear combination of cumulant slices. Then, thisresult is used to obtain a new well-conditioned linear methodto estimate the MA parameters of a non-Gaussian process. Theproposed method presents several important differences withexisting linear approaches. The linear combination of slices usedto compute the MA parameters can be constructed from dif-ferent sets of cumulants of different orders, providing a generalframework where all the statistics can be combined. Further-more, it is not necessary to use second-order statistics (the autocorrelation slice), and therefore the proposed algorithm stillprovides consistent estimates in the presence of colored Gaussian noise. Another advantage of the method is that while mostlinear methods developed so far give totally erroneous estimates if the order is overestimated, the proposed approach doesnot require a previous estimation of the filter order. The simulation results confirm the good numerical conditioning of thealgorithm and the improvement in performance with respect to existing methods.

Use of anisotropic modelling in electrical impedance tomography: description of method and preliminary assessment of utility in imaging brain function in the adult human head.

Electrical Impedance Tomography (EIT) is an imaging method which enables a volume conductivity map of a subject to be produced from multiple impedance measurements. It has the potential to become a portable non-invasive imaging technique of particular use in imaging brain function. Accurate numerical forward models may be used to improve image reconstruction but, until now, have employed an assumption of isotropic tissue conductivity. This may be expected to introduce inaccuracy, as body tissues, especially those such as white matter and the skull in head imaging, are highly anisotropic. The purpose of this study was, for the first time, to develop a method for incorporating anisotropy in a forward numerical model for EIT of the head and assess the resulting improvement in image quality in the case of linear reconstruction of one example of the human head. A realistic Finite Element Model (FEM) of an adult human head with segments for the scalp, skull, CSF, and brain was produced from a structural MRI. Anisotropy of the brain was estimated from a diffusion tensor-MRI of the same subject and anisotropy of the skull was approximated from the structural information. A method for incorporation of anisotropy in the forward model and its use in image reconstruction was produced. The improvement in reconstructed image quality was assessed in computer simulation by producing forward data, and then linear reconstruction using a sensitivity matrix approach. The mean boundary data difference between anisotropic and isotropic forward models for a reference conductivity was 50%. Use of the correct anisotropic FEM in image reconstruction, as opposed to an isotropic one, corrected an error of 24 mm in imaging a 10% conductivity decrease located in the hippocampus, improved localisation for conductivity changes deep in the brain and due to epilepsy by 4-17 mm, and, overall, led to a substantial improvement on image quality. This suggests that incorporation of anisotropy in numerical models used for image reconstruction is likely to improve EIT image quality.

Monte Carlo Methods in Parameter Estimation of Nonlinear Models

Yksi keskeisimmistä tehtävistä matemaattisten mallien tilastollisessa analyysissä on mallien tuntemattomien parametrien estimointi. Tässä diplomityössä ollaan kiinnostuneita tuntemattomien parametrien jakaumista ja niiden muodostamiseen sopivista numeerisista menetelmistä, etenkin tapauksissa, joissa malli on epälineaarinen parametrien suhteen. Erilaisten numeeristen menetelmien osalta pääpaino on Markovin ketju Monte Carlo -menetelmissä (MCMC). Nämä laskentaintensiiviset menetelmät ovat viime aikoina kasvattaneet suosiotaan lähinnä kasvaneen laskentatehon vuoksi. Sekä Markovin ketjujen että Monte Carlo -simuloinnin teoriaa on esitelty työssä siinä määrin, että menetelmien toimivuus saadaan perusteltua. Viime aikoina kehitetyistä menetelmistä tarkastellaan etenkin adaptiivisia MCMC menetelmiä. Työn lähestymistapa on käytännönläheinen ja erilaisia MCMC -menetelmien toteutukseen liittyviä asioita korostetaan. Työn empiirisessä osuudessa tarkastellaan viiden esimerkkimallin tuntemattomien parametrien jakaumaa käyttäen hyväksi teoriaosassa esitettyjä menetelmiä. Mallit kuvaavat kemiallisia reaktioita ja kuvataan tavallisina differentiaaliyhtälöryhminä. Mallit on kerätty kemisteiltä Lappeenrannan teknillisestä yliopistosta ja Åbo Akademista, Turusta.

Benchmarking project of the Department of Electrical Engineering of Lappeenranta University of Technology

Lappeenrannan teknillisen korkeakoulun sähkötekniikan osasto muutti 1.8.2005 sähkötekniikan tutkinnon kaksiportaiseksi ja vastaamaan näin Bologna-prosessia ja Suomen yliopistolainsäädäntöä. Tutkinnonuudistuksen myötä osasto haluaa varmistaa sähkötekniikan tutkintojen laadun ja vertailtavuuden sekä parantaa opiskelijoidensekä henkilökunnan liikkuvuutta. Tutkintojen laatu ja vertailtavuus osoitetaan sähkötekniikan osaston benchmark-projektilla, jossa kerätään tietoja maisteri- ja tohtorintutkintoa tarjoavista eurooppalaisista yliopistoista. Diplomityö käsittää BM-projektin kolmannen vaiheen suunnittelun ja toteutuksen sisältäen teoriaa benchmark-projekteille tyypillisistä toimintatavoista. Hyväksi havaitut menetelmiä, kuten kyselyt ja matriisit, on tässä työssä otettu soveltuvin osin sähkötekniikan osaston BM-projektin työkaluiksi. Diplomityössä analysoidaan työkalujen avulla BM-kumppaneilta kerättyjä tietoja sekä esitetään ratkaisuja, miten sähkötekniikan osastolla voidaan jatkaa parhaiden toimintatapojen löytämistä.

Electrical source imaging for presurgical focus localization in epilepsy patients with normal MRI.

PURPOSE: Patients with magnetic resonance (MR)-negative focal epilepsy (MRN-E) have less favorable surgical outcomes (between 40% and 70%) compared to those in whom an MRI lesion guides the site of surgical intervention (60-90%). Patients with extratemporal MRN-E have the worst outcome (around 50% chance of seizure freedom). We studied whether electroencephalography (EEG) source imaging (ESI) of interictal epileptic activity can contribute to the identification of the epileptic focus in patients with normal MRI. METHODS: We carried out ESI in 10 operated patients with nonlesional MRI and a postsurgical follow-up of at least 1 year. Five of the 10 patients had extratemporal lobe epilepsy. Evaluation comprised surface and intracranial EEG monitoring of ictal and interictal events, structural MRI, [(18)F]fluorodeoxyglucose positron emission tomography (FDG-PET), ictal and interictal perfusion single photon emission computed tomography (SPECT) scans. Eight of the 10 patients also underwent intracranial monitoring. RESULTS: ESI correctly localized the epileptic focus within the resection margins in 8 of 10 patients, 9 of whom experienced favorable postsurgical outcomes. DISCUSSION: The results highlight the diagnostic value of ESI and encourage broadening its application to patients with MRN-E. If the surface EEG contains fairly localized spikes, ESI contributes to the presurgical decision process.

Electrical Machines' Market in Russia

Venäjän valtion osuus maailmantaloudesta on pieni verrattuna sen maantieteelliseen kokoon, väkilukuun ja luonnonvaroihin. Sitä pidetään kuitenkin yhtenä tulevaisuuden merkittävistä kasvumarkkinoista. Venäjällä on tyypillisesti teollisuutta, joka hyödyntää luonnonvaroja ja tuottaa raaka-aineita sekä kotimaan että ulkomaiden markkinoille. Tällaisia tyypillisiä teollisuudenaloja Venäjällä ovat kaivos- ja metsäteollisuus sekä kemikaalien- kaasun- ja öljyntuotanto. Myös näiden teollisuusalojen tarvitsemien tuotantolaitteiden ja koneiden valmistusta on Venäjällä. Näitä koneita viedään Venäjältä entisiin neuvostovaltioihin ja päinvastoin. Tässä diplomityössä tutkitaan sähkömoottorien markkinapotentiaalia ja kilpailutilannetta Venäjällä. Venäjän osalta perehdytään sen kansantalouden tilaan ja tutkitaan sähkökonemarkkinoiden kokoa segmenteittäin monien erilähteiden avulla. Venäjän arvioidaan olevan erittäin potentiaalinen ja kasvava markkina-alue. Diplomityössä selvitetään ostoprosessia Venäjällä ja sähkökonemarkkinoiden ominaisuuksia kyseisellä alueella.

Linjasekoittimensekoituskyvyn määrittäminen

Työn tavoitteena oli kehittää sekoituskyvyn empiirinen monimuuttujafunktio eräälle dynaamiselle linjasekoittimelle. Monimuuttujafunktio oli tarkoitus kehittää sekoittimen kierrosnopeuden, virtaavien materiaalien ja tilavuusvirtausten perus-teella. Työn kirjallisuusosassa tarkasteltiin pääosin dynaamisia linjasekoittimia ja niiden toimintaperiaatteita sekä sekoituskyvyn määrittämiseen soveltuvia mittausmene-telmiä. Sekoitettavien aineiden epähomogeenisuus määritettiin mittaamalla termoelemen-teillä sekoittimen jälkeisen virran lämpötilavaihtelut. Sekoitettavina aineina käy-tettiin kolmea erilaista seosta: vesi-vesi-, kuitususpensio-vesi- ja karboksyylime-tyyliselluloosa-vesiseoksia. Muita muuttujia kokeissa olivat neljä eri sekoittimen kierrosnopeutta, neljä eri päävirran tilavuusvirtausta ja kolme päävirran sekäsii-hen lisättävän sivuvirran suhdetta. Monimuuttujafunktiokehitettiin vain kuitususpensio-vesiajojen pohjalta muilla seoksilla tehtyjen koeajojen osittaisen epäonnistumisen vuoksi. Hallitsevaksi pa-rametriksi monimuuttujafunktiossa osoittautui sekoittimen kierrosnopeus. Osittai-nen epäonnistuminen kokeissa johtui osaksi termoelementtien käytön sopimatto-muudesta sekoituskyvyn määrittämiseen ja osaksi sekoitettavien aineiden valin-nasta. Jatkotutkimuksiaajatellen muista sekoituskyvyn mittaamiseen käytettävissä olevista menetelmistäkäyttökelpoisimmaksi arvioitiin sähkötomografia.

Spatial distribution of motor units recruited during electrical stimulation of the quadriceps muscle versus the femoral nerve.

INTRODUCTION: In this study we investigated differences in the spatial recruitment of motor units (MUs) in the quadriceps when electrical stimulation is applied over the quadriceps belly versus the femoral nerve. METHODS: M-waves and mechanical twitches were evoked using over-the-quadriceps and femoral nerve stimulation of gradually increasing intensity from 22 young, healthy subjects. Spatial recruitment was investigated using recruitment curves of M-waves recorded from the vastus medialis (VM) and vastus lateralis (VL) and of twitches recorded from the quadriceps. RESULTS: At maximal stimulation intensity (Imax), no differences were found between nerve and over-the-quadriceps stimulation. At submaximal intensities, VL M-wave amplitude was higher for over-the-quadriceps stimulation at 40% Imax, and peak twitch force was greater for nerve stimulation at 60% and 80% Imax. CONCLUSIONS: For the VM, MU spatial recruitment during nerve and over-the-quadriceps stimulation of increasing intensity occurred in a similar manner, whereas significant differences were observed for the VL. Muscle Nerve, 2013.

Converter-flux-based current control of voltage source PWM rectifiers - analysis and implementation

Pulsewidth-modulated (PWM) rectifier technology is increasingly used in industrial applications like variable-speed motor drives, since it offers several desired features such as sinusoidal input currents, controllable power factor, bidirectional power flow and high quality DC output voltage. To achieve these features,however, an effective control system with fast and accurate current and DC voltage responses is required. From various control strategies proposed to meet these control objectives, in most cases the commonly known principle of the synchronous-frame current vector control along with some space-vector PWM scheme have been applied. Recently, however, new control approaches analogous to the well-established direct torque control (DTC) method for electrical machines have also emerged to implement a high-performance PWM rectifier. In this thesis the concepts of classical synchronous-frame current control and DTC-based PWM rectifier control are combined and a new converter-flux-based current control (CFCC) scheme is introduced. To achieve sufficient dynamic performance and to ensure a stable operation, the proposed control system is thoroughly analysed and simple rules for the controller design are suggested. Special attention is paid to the estimationof the converter flux, which is the key element of converter-flux-based control. Discrete-time implementation is also discussed. Line-voltage-sensorless reactive reactive power control methods for the L- and LCL-type line filters are presented. For the L-filter an open-loop control law for the d-axis current referenceis proposed. In the case of the LCL-filter the combined open-loop control and feedback control is proposed. The influence of the erroneous filter parameter estimates on the accuracy of the developed control schemes is also discussed. A newzero vector selection rule for suppressing the zero-sequence current in parallel-connected PWM rectifiers is proposed. With this method a truly standalone and independent control of the converter units is allowed and traditional transformer isolation and synchronised-control-based solutions are avoided. The implementation requires only one additional current sensor. The proposed schemes are evaluated by the simulations and laboratory experiments. A satisfactory performance and good agreement between the theory and practice are demonstrated.

Applicability of Power-Line Communications to Data Transfer of On-line Condition Monitoring of Electrical Drives

The research of power-line communications has been concentrated on home automation, broadband indoor communications and broadband data transfer in a low voltage distribution network between home andtransformer station. There has not been carried out much research work that is focused on the high frequency characteristics of industrial low voltage distribution networks. The industrial low voltage distribution network may be utilised as a communication channel to data transfer required by the on-line condition monitoring of electric motors. The advantage of using power-line data transfer is that it does not require the installing of new cables. In the first part of this work, the characteristics of industrial low voltage distribution network components and the pilot distribution network are measured and modelled with respect topower-line communications frequencies up to 30 MHz. The distributed inductances, capacitances and attenuation of MCMK type low voltage power cables are measured in the frequency band 100 kHz - 30 MHz and an attenuation formula for the cables is formed based on the measurements. The input impedances of electric motors (15-250 kW) are measured using several signal couplings and measurement based input impedance model for electric motor with a slotted stator is formed. The model is designed for the frequency band 10 kHz - 30 MHz. Next, the effect of DC (direct current) voltage link inverter on power line data transfer is briefly analysed. Finally, a pilot distribution network is formed and signal attenuation in communication channels in the pilot environment is measured. The results are compared with the simulations that are carried out utilising the developed models and measured parameters for cables and motors. In the second part of this work, a narrowband power-line data transfer system is developed for the data transfer ofon-line condition monitoring of electric motors. It is developed using standardintegrated circuits. The system is tested in the pilot environment and the applicability of the system for the data transfer required by the on-line condition monitoring of electric motors is analysed.