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Time Series Modeling of Clinical Electroencephalogram Data - An Information Theory ApproachSnyder, Selena Tyr 25 June 2018 (has links)
No description available.
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Automatsko određivanje i analitička provera parametara uzajamne entropije kardiovaskularnih vremenskih nizova / Automatic determination and analytical verification of cross entropyparameters of cardiovascular time seriesŠkorić Tamara 05 October 2017 (has links)
<p>Unakrsna aproksimativna entropija kvantifikuje međusobnu uređenost<br />dva istomvremeno snimljena vremenska niza. Iako je izvedena iz<br />veoma zastupljene entropije za procenu uređenosti jednog vremenskog<br />niza, još uvek nije dostigla njenu reputaciju. Cilj ove disertacije je<br />da identifikuje probleme koji otežavaju širu primenu unakrsne<br />entropije i da predloži skup rešenja. Validacija rezultata je rađena<br />na kardiovaskularnim signalima, sistolnog krvnog pritiska i palsnog<br />inetervala snimljenim na laboratorijskim pacovima i na signalima<br />zdravih volontera.</p> / <p>Cross-approximate entropy (XApEn) quantifies a mutual orderliness of two<br />simultaneously recorded time series. Although derived from the firmly<br />establishe solitary entropies, it has never reached their reputation and<br />deployment. The aim of this thesis is to identify the problems that preclude<br />wider XApEn implementation and to develop a set of solutions. Results were<br />validated using the cardiovascular time series, systolic blood pressure and<br />pulse interval, recorded from laboratories animals and also signals recorded<br />from healthy human volunteers.</p>
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Analyse, caractérisation et classification de signaux foetaux / Analysis, characterization and classification of fetal signalsVoicu, Iulian 13 December 2011 (has links)
L’objectif de ce travail est d’obtenir, grâce à un mélange de différentes informations, un monitorage de l’activité du fœtus pour apprécier son état de bien-être ou de souffrance.Actuellement, les paramètres qui caractérisent la souffrance fœtale, issus du rythme cardiaque et des mouvements fœtaux, sont évalués par le médecin et ils sont réunis dans le score de Manning. Deux inconvénients majeurs existent: a) l’évaluation du score est trop longue puisqu’elle dure 1 heure b) il existe des variations inter et intra-opérateur conduisant à différentes interprétations du bilan médical de la patiente.Pour s’affranchir de ces désavantages nous évaluons le bien-être fœtal d’une façon objective, à travers le calcul d’un score. Pour atteindre ce but, nous avons développé une technologie ultrasonore mufti-capteurs permettant de recueillir une soixantaine de signaux Doppler en provenance du cœur, des membres inférieurs et supérieurs. / The objective of this work is to assess the fetal parameters and the fetal well-being using a mixture of fetal parameters. In our days, the parameters derived from heart rate and fetal movements that characterize the fetal distress are assessed by the physician and unified in the score of Manning. Two major disadvantages of Manning’s score exist: a) the assessment of the score is time consuming; b) there are variations inter and intra operators leading to different interpretations of the patients medical record. To overcome these disadvantages we assess the fetal well-being objectively, by computing an automatic/electronic score. To achieve this goal, we developed an ultrasonic multi-sensor unit with 12 sensors allowing to collect sixty Doppler signals from the heart, lower and upper limbs.
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VARIABILITY ANALYSIS & ITS APPLICATIONS TO PHYSIOLOGICAL TIME SERIES DATAKaffashi, Farhad 06 June 2007 (has links)
No description available.
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Complexity of the Electroencephalogram of the Sprague-Dawley RatSmith, Phillip James 27 July 2010 (has links)
No description available.
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ALTERATIONS IN POSTURAL CONTROL FOLLOWING AN ACUTE BOUT OF SOCCER HEADINGHaran, Francis Joseph January 2009 (has links)
This study sought to determine if an acute bout of soccer heading adversely altered postural control and pronounced self-reported symptoms of cerebral concussion. Sixteen collegiate soccer players were randomly assigned to one of two groups: control (CG) or experimental (EG). Participants either simulated or performed 10 headers in 10 min at a ball velocity 11.2 m/s. A concussion signs and symptoms checklist was completed and postural control was assessed on four separate occasions: prior to heading (hr 0), hr 1, hr 24, and hr 48 post heading. The postural control parameters were the root mean square (RMS) of the center of mass (COM) and approximate entropy (ApEN) of the center of pressure (COP). The results indicated that there were no significant differences between the CG and EG in the sum of self-reported concussion signs and symptoms; however, there were significant alterations in postural control, occurring primarily at 24 hrs following heading. Within the EG only there were significant differences across time for anterior-posterior (AP) COM RMS for conditions 3 (i.e., rotating virtual environment [VE] and stable support surface) and 4 (i.e., rotating VE and unstable support surface). Also, medial-lateral (ML) COM RMS values were significantly higher for the EG when compared to the CG at hr 24. The EG had significantly lower COP ApEn values in both the AP and ML directions when compared to the CG at hr 24. Condition 4 was found to induce significantly greater postural control deficits when compared to the other conditions in the ML COM RMS and AP COP ApEn. These findings indicate that an acute bout of heading, even at the low velocities presented in this experiment, result in quantifiable alterations in postural control that are detectable 24 hours post heading and dissipate within an additional 24 hours. The significant findings are contrary to the acute heading literature and may be due to the postural control assessment that incorporated robust discordant environmental conditions. Further research on the clinical usefulness of the assessment as well as long-term accumulation effects of heading is warranted. / Kinesiology
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The Effects of Vibratory Noise on Responses to Postural StabilityLanaria, Lois January 2011 (has links)
Our human balance system is critical for preventing falls. The system consists of a complex set of sensorimotor controls that includes integration of sensory inputs including sight, touch and vestibular to produce motor output. Tactile afferents from the plantar surface contribute to the human balance and movement control system. Loss of sensory information could lead to impaired balance primarily because of impaired detection of changes in upright position, delayed postural reflexes, or failure to realize how far one's center of mass has been displaced thus increasing the probability of falls. Somatosensory and visual information must be integrated to interpret complex sensory environment. Sensory pathways that are simultaneously feeding inputs into the system exhibit non-linear behavior and it is unlikely that the role of a single pathway can be characterized in a static environment. As the sensory environment changes, the need to re-weight the relative dependence on each senses is essential for maintaining stability. Thus, attention also plays an important role in postural control. Attention can be defined as the individual's capacity for information processing. Performing two or more tasks at the same time may require more than an individual's attention capacity and thereby may weaken performance in the other task. Stochastic resonance phenomena has been shown to enhance sensory information processing and perception. This series of studies sought to analyze the effects of vibrotactile noise on human postural responses using a sub-threshold vibration (SV) and above-threshold vibration (AV). The vibrotactile noise was applied at the soles of both feet with six DC vibrator disks embedded in open-type footwear. Twenty one healthy adults wearing the vibrating footwear stood quietly on a compliant surface for 90 seconds inside a three-wall virtual environment. The visual conditions were either eyes closed, eyes open or a continuous visual flow field in a pitch-up direction at constant velocity of 30°/sec. A dual task paradigm was presented as a computation task, the Fibonacci sequence. The first 30 seconds of the 90 seconds trial had no vibration followed by 30 seconds of either sub-threshold or above-threshold vibration. Vibration was removed for the final 30 seconds. Root mean squares (RMS) and approximate entropy (ApEn) of center of mass (COM) and center of pressure (COP) excursions were calculated in the anterior-posterior (AP) and medio-lateral (ML) directions for each 30 second time period and normalized to each subject's initial position. Approximate entropy (ApEn) was used to detect movement variability in a time series to determine the unpredictability of the postural responses. COP and COM data were tested for statistical significance using repeated measures analysis of variance (ANOVA) with within-subject factors of vision (3 levels: eyes closed, eyes open and pitch-up), task (2 levels: single task and dual task), and vibration level (2 levels: sub-threshold vibration and above-threshold vibration) at a 95% confidence level (p<0.05). Results supported the hypothesis that the application of SV and AV affected COP regularity and variability differently when subjected to different visual conditions (eyes closed, eyes open and pitch-up). COM randomness increased (higher ApEn) when attention was diverted from postural control which is in agreement with previous studies. The decrease in COM AP randomness (lower ApEn) with vibration suggested that the application of vibration increased the amount of attention invested in postural control or balance when performing an attention demanding cognitive task. The SV increased the COP-AP regularity (lower ApEn) during eyes-closed and eyes-open conditions while AV increased COP-AP variability (increased RMS) during the pitch-up visual condition. In conclusion, posture and balance were affected by the application of vibration noise. The vibration noise enhanced the amount of attention invested in postural control while performing an attention demanding cognitive task and sensory-motor learning was achieved by increasing COM sway structure regularity (lower ApEn) but not the sway magnitude. These results suggest that the interaction between vibration noise and an attention demanding task resulted in the temporal re-structuring of the postural control system without affecting the equilibrium region for the COM sway excursion. Vibration noise appears to facilitate postural control by altering postural response regularity (lower ApEn). For COM, only postural response regularity but not sway variability was affected by vibration noise in relation to vision regardless of the vibration level (SV or AV). For COP postural responses, the effect of SV and AV differs. Due to the perception of self-motion from the pitch-up visual condition, COP postural response most likely arise from cortical level. Since AV only affected COP responses during pitch-up visual condition and not SV, this study suggests that AV applied affected the cortical level of postural control. Effects of SV on postural responses between the eyes-open and eyes-closed vision conditions suggests that SV may affect a subcortical level of postural control. Understanding the effects and mechanism of vibratory noise may help in the design of effective interventions to prevent falls and rehabilitation. These results provide the scientific basis for development of a SR-based rehabilitation device for people with sensory information and processing deficiency as occurs with aging or stroke. The finding of after effects of vibratory noise can be used to determine dosage of vibrotactile stimulation in the design of vibrating footwear. / Bioengineering
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Análise temporal da sinalização elétrica em plantas de soja submetidas a diferentes perturbações externas / Temporal analysis of electrical signaling in soybean plants subjected to different external disturbancesSaraiva, Gustavo Francisco Rosalin 31 March 2017 (has links)
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Previous issue date: 2017-03-31 / Plants are complex organisms with dynamic processes that, due to their sessile way of life, are influenced by environmental conditions at all times. Plants can accurately perceive and respond to different environmental stimuli intelligently, but this requires a complex and efficient signaling system. Electrical signaling in plants has been known for a long time, but has recently gained prominence with the understanding of the physiological processes of plants. The objective of this thesis was to test the following hypotheses: temporal series of data obtained from electrical signaling of plants have non-random information, with dynamic and oscillatory pattern, such dynamics being affected by environmental stimuli and that there are specific patterns in responses to stimuli. In a controlled environment, stressful environmental stimuli were applied in soybean plants, and the electrical signaling data were collected before and after the application of the stimulus. The time series obtained were analyzed using statistical and computational tools to determine Frequency Spectrum (FFT), Autocorrelation of Values and Approximate Entropy (ApEn). In order to verify the existence of patterns in the series, classification algorithms from the area of machine learning were used. The analysis of the time series showed that the electrical signals collected from plants presented oscillatory dynamics with frequency distribution pattern in power law. The results allow to differentiate with great efficiency series collected before and after the application of the stimuli. The PSD and autocorrelation analyzes showed a great difference in the dynamics of the electric signals before and after the application of the stimuli. The ApEn analysis showed that there was a decrease in the signal complexity after the application of the stimuli. The classification algorithms reached significant values in the accuracy of pattern detection and classification of the time series, showing that there are mathematical patterns in the different electrical responses of the plants. It is concluded that the time series of bioelectrical signals of plants contain discriminant information. The signals have oscillatory dynamics, having their properties altered by environmental stimuli. There are still mathematical patterns built into plant responses to specific stimuli. / As plantas são organismos complexos com processos dinâmicos que, devido ao seu modo séssil de vida, sofrem influência das condições ambientais todo o tempo. Plantas podem percebem e responder com precisão a diferentes estímulos ambientais de forma inteligente, mas para isso se faz necessário um complexo e eficiente sistema de sinalização. A sinalização elétrica em plantas já é conhecida há muito tempo, mas vem ganhando destaque recentemente com seu entendimento em relação aos processos fisiológicos das plantas. O objetivo desta tese foi testar as seguintes hipóteses: séries temporais de dados obtidos da sinalização elétrica de plantas possuem informação não aleatória, com padrão dinâmico e oscilatório, sendo tal dinâmica afetada por estímulos ambientais e que há padrões específicos nas respostas a estímulos. Em ambiente controlado, foram aplicados estímulos ambientais estressantes em plantas de soja, e captados os dados de sinalização elétrica antes e após a aplicação dos mesmos. As séries temporais obtidas foram analisadas utilizando ferramentas estatísticas e computacionais para se determinar o Espectro de Frequências (FFT), Autocorrelação dos valores e Entropia Aproximada (ApEn). Para se verificar a existência de padrões nas séries, foram utilizados algoritmos de classificação da área de aprendizado de máquina. A análise das séries temporais mostrou que os sinais elétricos coletados de plantas apresentaram dinâmica oscilatória com padrão de distribuição de frequências em lei de potência. Os resultados permitem diferenciar com grande eficácia séries coletadas antes e após a aplicação dos estímulos. As análises de PSD e autocorrelação mostraram grande diferença na dinâmica dos sinais elétricos antes e após a aplicação dos estímulos. A análise de ApEn mostrou haver diminuição da complexidade do sinal após a aplicação dos estímulos. Os algoritmos de classificação alcançaram valores significativos na acurácia de detecção de padrões e classificação das séries temporais, mostrando haver padrões matemáticos nas diferentes respostas elétricas das plantas. Conclui-se que as séries temporais de sinais bioelétricos de plantas possuem informação discriminante. Os sinais possuem dinâmica oscilatória, tendo suas propriedades alteradas por estímulos ambientais. Há ainda padrões matemáticos embutidos nas respostas da planta a estímulos específicos.
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Complexity Analysis of Physiological Time Series with Applications to Neonatal Sleep Electroencephalogram SignalsLi, Chang 08 March 2013 (has links)
No description available.
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Ανάπτυξη μεθόδων ανάλυσης ηλεκτροεγκεφαλογραφήματος με χρήση μοντέλων συνδεσιμότητας και μεγεθών εντροπίαςΓιαννακάκης, Γιώργος Α. 20 April 2011 (has links)
Σκοπός της παρούσας διδακτορικής διατριβής είναι η ανάπτυξη και η εφαρμογή εξελιγμένων αλγορίθμων ανάλυσης ηλεκτροεγκεφαλογραφήματος ηρεμίας (rest EEG) και προκλητών δυναμικών (ERP) για την εξαγωγή νευροφυσιολογικών συμπερασμάτων σχετικά με νευρολογικές/ψυχιατρικές ασθένειες. Οι τεχνικές που αναπτύσσονται εφαρμόζονται τόσο σε συνθετικά σήματα όσο και σε πραγματικά σήματα μαρτύρων και ατόμων με δυσλεξία, που υποβάλλονται στην ακουστική δοκιμασία Wechsler.
Αρχικά μελετούνται τα συμβατικά χαρακτηριστικά προκλητών δυναμικών που αποτελούνται από τα πλάτη των κορυφώσεων και τους λανθάνοντες χρόνους πραγματοποίησής τους μετά το ερέθισμα. Μέσω στατιστικών αναλύσεων αναδεικνύεται ότι τα άτομα με δυσλεξία παρουσιάζουν σημαντικά μικρότερο πλάτος κορύφωσης N100 το οποίο μάλιστα συσχετίζεται με την απόδοση μνήμης. Επίσης, ο προσυνειδητός χρόνος απόκρισης στα ηχητικά ερεθίσματα παρουσιάζεται σε συγκεκριμένα ηλεκτρόδια σημαντικά παρατεταμένος σε άτομα με δυσλεξία.
Οι ενεργειακές διαφοροποιήσεις στα φάσματα EEG/ERP προσφέρουν σημαντική πληροφορία σχετικά με το βαθμό ενεργοποίησης των διαφόρων περιοχών του εγκεφάλου. Η ανάλυση ενεργειακών διαφοροποιήσεων πραγματοποιείται στο πεδίο χρόνου-συχνότητας, αναδεικνύοντας χρονικές μεταβολές του φασματικού περιεχομένου. Στο πλαίσιο αυτό, αξιολογούνται συγκριτικά τεχνικές αναπαράστασης χρόνου-συχνότητας τόσο δεύτερης τάξης όσο και προσαρμοστικές. Ο αλγόριθμος matching pursuit αποδεικνύεται ιδιαίτερα αποτελεσματικός στη μείωση των διαγώνιων όρων και στην ανάδειξη ενεργειακών κορυφών. Για τη στατιστική αποτίμηση των ενεργειακών διαφορών στις ζώνες συχνοτήτων δ (0-4 Hz), θ (5-7 Hz), α (8-13 Hz), β (14-30 Hz), προτείνεται μεθοδολογία βασισμένη στο συνδυασμό μεθόδων κανονικοποίησης και διόρθωσης πολλαπλών συγκρίσεων.
Η ύπαρξη σημαντικών ενεργειακών διαφοροποιήσεων ενδεχόμενα είναι απόρροια του διαφορετικού τρόπου λειτουργικής συνδεσιμότητας μεταξύ των δύο μελετούμενων ομάδων (μαρτύρων, ατόμων με δυσλεξία). Για το σκοπό αυτό, υπολογίζονται μεγέθη συνδεσιμότητας και αιτιότητας μεταξύ ηλεκτροεγκεφαλογραφικών καταγραφών, με χρήση του μοντέλου πολλαπλής παλινδρόμησης σε συνδυασμό με τις μεθόδους εκτίμησης Yule-Walker, Burg και Least Squares, καταδεικνύοντας την ανωτερότητα των δύο τελευταίων όσον αφορά στην ακρίβεια πρόβλεψης. Μετά από εκτεταμένη συγκριτική αξιολόγηση των μεγεθών αιτιότητας, προτείνεται ένα νέο μέγεθος ανάδειξης των άμεσων ροών δραστηριότητας, το οποίο βασίζεται στο συνδυασμό της μη κανονικοποιημένης κατευθυνόμενης συνάρτησης μεταφοράς και της μερικής κατευθυνόμενης συμφωνίας. Το μέγεθος αυτό αποδεικνύεται ιδιαίτερα αποδοτικό στη μείωση ψευδών ή μη άμεσων ροών και παρουσιάζει φασματικές ιδιότητες παρόμοιες με αυτές των εμπλεκόμενων κυματομορφών. Η εφαρμογή του σε ηλεκτροεγκεφαλογράφημα ηρεμίας, όπου ικανοποιείται η συνθήκη στασιμότητας, οδηγεί στην ανάδειξη διαφοροποιήσεων σε συγκεκριμένες ροές δραστηριότητας. Στην περίπτωση μη στάσιμων χρονοσειρών, όπως είναι τα προκλητά δυναμικά, χρησιμοποιείται δυναμικό μοντέλο πολλαπλής παλινδρόμησης για την εκτίμηση των μεγεθών σύζευξης.
Μελετάται η ικανότητας αναπαράστασης γρήγορα μεταβαλλόμενων αιτιακών σχέσεων, με χρήση τόσο της προσέγγισης μικρού χρονικού παραθύρου όσο και προσαρμοζόμενων φίλτρων Kalman. Η μελέτη περιλαμβάνει την επίδραση του επιπέδου θορύβου, του συντελεστή προσαρμογής και της χρονικής μεταβολής των συνδέσεων του προτύπου συνδεσιμότητας. Το φίλτρο Kalman αποδεικνύεται ιδιαίτερα ακριβές στην εκτίμηση της χρονικής εξέλιξης των συντελεστών του μοντέλου τόσο σε συνθετικά όσο και σε πραγματικά ηλεκτροεγκεφαλογραφικά δεδομένα.
Επιπλέον, μελετήθηκε η προβλεψιμότητα/πολυπλοκότητα των χρονοσειρών, με χρήση μεγεθών φασματικής και προσεγγιστικής εντροπίας. Η φασματική εντροπία και οι παραλλαγές της αποτελούν μεγέθη που αναδεικνύουν τη φασματική πολυπλοκότητα μιας χρονοσειράς και σχετίζονται με φαινόμενα συγχρονισμού και επικράτησης συγκεκριμένων ζωνών συχνοτήτων. Επειδή χρειάζεται να μελετηθεί η χρονική εξέλιξη της πολυπλοκότητας αυτής, τα μεγέθη αυτά υπολογίζονται τόσο με χρήση μετασχηματισμού κυματιδίου όσο και με χρήση βέλτιστου πυρήνα, καταδεικνύοντας την ανωτερότητα του τελευταίου στο διαχωρισμό μεταξύ των δύο ομάδων (μαρτύρων, ατόμων με δυσλεξία). Η αναπαράσταση με χρήση βέλτιστου πυρήνα επιτρέπει την προσαρμογή του πυρήνα σε κάθε υπό ανάλυση σήμα, κάτι το οποίο έχει ιδιαίτερη σημασία σε περιπτώσεις που παρατηρείται έντονη διακύμανση μεταξύ των καταγραφών. Τέλος, μέσω της προσεγγιστικής εντροπίας μελετάται η ύπαρξη όμοιων προτύπων παρατηρήσεων κατά μήκος των χρονοσειρών τόσο σε συγκεκριμένα ηλεκτρόδια όσο και μεταξύ ηλεκτροδίων.
Οι μέθοδοι που παρουσιάζονται στο πλαίσιο της παρούσας διδακτορικής διατριβής συμβάλλουν στην πιο αντικειμενική και αξιόπιστη μελέτη συγχρονισμού, αιτιακών σχέσεων και πολυπλοκότητας κατά την ανάλυση ηλεκτροεγκεφαλογραφικών καταγραφών. / The purpose of the present Ph.D. thesis is to develop and apply advanced algorithms for EEG/ERP signal analysis in order to study neurophysiological alterations associated with dyslexia. The used methods aim at a reliable analysis of synchronization, causal connectivity and complexity of EEG/ERP signals and are evaluated on both synthetic and real EEG/ERP signals of dyslexics and controls, acquired during Wechsler auditory test.
First, the conventional components of ERP waveforms (peak amplitudes, latencies) are studied. Statistical analysis points out that dyslexics’ signals present significantly lower N100 amplitudes which are known to be associated with memory performance. An important parameter in dyslexia is the pre-attentive reaction time to auditory stimuli which is reflected through P50 latency and is found to be significantly prolonged at specific electrodes.
Energy differentiations in time-frequency between the two groups (dyslexics and controls) are examined, enabling study of the temporal changes of ERP content. Various second order and adaptive time-frequency methods are comparatively assessed in terms of their accuracy in representing temporally changing spectra. Matching pursuit is proved to be quite effective in cross terms suppression and representation of energy peaks. Significant energy differentiations at delta (0-4 Hz), theta (5-7 Hz), alpha (8-13 Hz) and beta (14-30 Hz) frequency bands are detected, through a methodology of statistical evaluation based on normalization and multiple comparisons correction methods.
The presence of significant energy differentiations may be the result of differing functional connectivity patterns between the two groups (controls, dyslexics). In order to study causal connectivity patterns, the multivariate autoregressive model is estimated using the Yule-Walker, Burg and Least Squares methods, with Burg and Least Squares proved to provide superior performance in terms of prediction error. A new measure for the estimation of direct causal interactions is proposed, which is based on the combination of the full frequency directed transfer function and the partial directed coherence, exhibiting spectral properties similar with those of the involved signals, and increased efficiency in suppressing false and non direct flows. Study of rest EEG connectivity patterns, by means of the new connectivity measure, revealed differentiations in specific activity flows between the two groups under study (controls and dyslexics).
In order to calculate coupling measures of non-stationary signals, like ERP, the dynamic autoregressive model is used and its ability to accurately represent rapid changes of causal interactions is assessed using short window and adaptive Kalman filter approaches. The superiority of the Kalman filter approach in terms of the accuracy provided in the estimation of the model’s autoregressive parameters is demonstrated on both synthetic and real EEG/ERP signals.
Furthermore, the predictability/complexity of EEG/ERP time-series of dyslexics versus controls was studied, using measures of spectral and approximate entropy. Spectral entropy and its modifications quantify the spectral complexity of time-series and are related with synchronization and dominance of specific frequency bands. In order to study the temporal evolution of signals’ spectral complexity, wavelet transform and optimal kernel approaches were used, and the superiority of the latter concerning its ability to discriminate the two groups was demonstrated. The representation through optimal kernel permits the adjustment to each analyzed signal, a property that is quite important in analyzing data characterized by intense variability. Finally, through approximate entropy, the presence of differentiations in predictability of EEG time series related with single electrodes or pairs of electrodes is studied, demonstrating that dyslexics’ signals are characterized by more predictable patterns.
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