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Yue, Chongshi. "EOG Signals in Drowsiness Research". Thesis, Linköpings universitet, Biomedicinsk instrumentteknik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-81761.
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Blink waveform in electrooculogram (EOG) data was used to develop and adjust the method of drowsiness detection in drivers. The origins of some other waveforms in EOG signal were not very clearly understood. The purpose of this thesis work is to study the EOG signal and give explanation of different kind of waveforms in EOG signal, and give suggestions to improve the blink detection algorithm. The road driving test video records and synchronized EOG signal were used to build an EOG library. By comparing the video record of the driver’s face and the EOG data, the origin of the unknown waveforms were discovered and related with the driver’s behavior. Literature descriptions were given to explain the EOG signal. The EOG library is the main result of this project. It organized by different types of EOG signal. Description and explanation were given for each type of waveform, as well as some examples. The knowledge gained from the previous research review and the EOG library gives some improvement suggestions for the blink detection algorithm. These suggestions still need to be verified in practical way.
2
Kelly, Graham. "Development of a compact, low-cost wireless device for biopotential acquisition". VCU Scholars Compass, 2014. http://scholarscompass.vcu.edu/etd/3559.
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A low-cost circuit board design is presented, which in one embodiment is smaller than a credit card, for biopotential (EMG, ECG, or EEG) data acquisition, with a focus on EEG for brain-computer interface applications. The device combines signal conditioning, low-noise and high-resolution analog-to-digital conversion of biopotentials, user motion detection via accelerometer and gyroscope, user-programmable digital pre-processing, and data transmission via Bluetooth communications. The full development of the device to date is presented, spanning three embodiments. The device is presented both as a functional data acquisition system and as a template for further development based on its publicly-available schematics and computer-aided design (CAD) files. The design will be made available at the GitHub repository https://github.com/kellygs/eeg.
3
Noureddin, Borna. "Online removal of eye movement and blink artifacts from EEG signals without EOG". Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/27818.
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In this thesis, two novel methods are presented for online removal of ocular artifacts (OA) from EEG without the need for EOG electrodes attached to the face. Both methods are fully automated and can remove the effects of both eye movements and blinks. The first method employs a high speed eye tracker and three frontal EEG electrodes as a reference to any nonlinear adaptive filter to remove OAs without any calibration. For the filters considered, at some frontal electrodes, using the eye tracker-based reference was shown to significantly (p < .05) improve the ability to remove OAs over using either EOG or only frontal EEG as a reference. Using an eye tracker provides the means for recording point-of-gaze and blink dynamics simultaneously with EEG, which is often desired or required in clinical studies and a variety of human computer interface applications. The second method uses a biophysical model of the head and movement of the eyes to remove OAs. It only requires a short once-per-subject calibration and does not require subject-specific MRI. It was compared to four existing methods, and was shown to perform consistently over a variety of tasks. In removing both saccades and blinks, it removed more than 4 times as much OA as the other methods. In terms of distortion, it was the only method that never removed more power than was present in the original EEG. To carry out the above studies, several related original investigations and developments were needed. These included a novel algorithm to extract the blink time course from eye tracker images, a new measure of OA removal distortion, a high speed eye tracker recording system, a study to determine whether frontal EEG could be used to replace EOG for OA removal and studies of the frequency content of blinks, the effects of an electromagnetic sensor on EEG, and the effects of varying mental states on OA removal methods. In summary this thesis has helped pave the way towards a real-time EEG-based human interface that is free of OAs and does not require EOG electrodes in its operation.
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Chocos, Ruiz Miguel Edgardo. "Estudo de filtros adaptativos para a remoção de artefatos de EOG em sinais de EEG". Florianópolis, SC, 1999. http://repositorio.ufsc.br/xmlui/handle/123456789/81217.
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Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico.Made available in DSpace on 2012-10-19T00:32:09Z (GMT). No. of bitstreams: 0Bitstream added on 2016-01-09T03:28:58Z : No. of bitstreams: 1 172499.pdf: 38594896 bytes, checksum: 8eb495de1be467f13160055357a2675e (MD5)
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Hapuarachchi, Pasan. "Feature selection and artifact removal in sleep stage classification". Thesis, University of Waterloo, 2006. http://hdl.handle.net/10012/2879.
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The use of Electroencephalograms (EEG) are essential to the analysis of sleep disorders in patients. With the use of electroencephalograms, electro-oculograms (EOG), and electromyograms (EMG), doctors and EEG technician can make conclusions about the sleep patterns of patients. In particular, the classification of the sleep data into various stages, such as NREM I-IV, REM, Awake, is extremely important. The EEG signal itself is highly sensitive to physiological and non-physiological artifacts. Trained human experts can accommodate for these artifacts while they are analyzing the EEG signal. However, if some of these artifacts are removed prior to analysis, their job will be become easier. Furthermore, one of the biggest motivations, of our team's research is the construction of a portable device that can analyze the sleep data as they are being collected. For this task, the sleep data must be analyzed completely automatically in order to make the classifications.
The research presented in this thesis concerns itself with the denoising and the feature selection aspects of the teams' goals. Since humans are able to process artifacts and ignore them prior to classification, an automated system should have the same capabilities or close to them. As such, the denoising step is performed to condition the data prior to any other stages of the sleep stage neoclassicisms. As mentioned before, the denoising step, by itself, is useful to human EEG technicians as well.
The denoising step in this research mainly looks at EOG artifacts and artifacts isolated to a single EEG channel, such as electrode pop artifacts. The first two algorithms uses Wavelets exclusively (BWDA and WDA), while the third algorithm is a mixture of Wavelets and In- dependent Component Analysis (IDA). With the BWDA algorithm, determining consistent thresholds proved to be a difficult task. With the WDA algorithm, the performance was better, since the selection of the thresholds was more straight-forward and since there was more control over defining the duration of the artifacts. The IDA algorithm performed inferior to the WDA algorithm. This could have been due to the small number of measurement channels or the automated sub-classifier used to select the denoised EEG signal from the set of ICA demixed signals.
The feature selection stage is extremely important as it selects the most pertinent features to make a particular classification. Without such a step, the classifier will have to process useless data, which might result in a poorer classification. Furthermore, unnecessary features will take up valuable computer cycles as well. In a portable device, due to battery consumption, wasting computer cycles is not an option. The research presented in this thesis shows the importance of a systematic feature selection step in EEG classification. The feature selection step produced excellent results with a maximum use of just 5 features. During automated classification, this is extremely important as the automated classifier will only have to calculate 5 features for each given epoch.
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Karlsson, Johanna. "Identifying patterns in physiological parameters of expert and novice marksmen in simulation environment related to performance outcomes". Thesis, Linköpings universitet, Avdelningen för medicinsk teknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-139589.
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The goal of this thesis is to investigate if it is possible to use measurements of physiological parameters to accelerate learning of target shooting for novice marksmen in Saab’s Ground combat indoor trainer (GC-IDT). This was done through a literature study that identified brain activity, eye movements, heart activity, muscle activity and breathing as related to shooting technique. The sensors types Electroencephalography (EEG), Electroocculography (EOG), Electrocardiogram (ECG), Electromyography (EMG) and impedance pneumography (IP) were found to be suitable for measuring the respective parameters in the GC-IDT. The literature study also showed that previous studies had found differences in the physiological parameters in the seconds leading up to the shot when comparing experts and novices. The studies further showed that it was possible to accelerate learning by giving feedback to the novices about their physiological parameters allowing them to mimic the behavior of the experts. An experiment was performed in the GC-IDT by measuring EOG, ECG, EMG and IP on expert and novice marksmen to investigate if similar results as seen in previous studies were to be found. The experiment showed correlation between eye movements and shooting score, which was in line with what previous studies had shown. The respiration measurement did not show any correlation to the shooting scores in this experiment, it was however possible to see a slight difference between expert and novices. The other measurements did not show any correlation to the shooting score in this experiment. In the future, further experiments needs to be made as not all parameters could be explored in depth in this experiment. Possible improvements to such experiments are i.e. increasing the number of participants and/or the number of shots as well as marking shots automatically in the data and increasing the time between shots.
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Peiris, Malik Tivanka Rajiv. "Lapses in Responsiveness: Characteristics and Detection from the EEG". Thesis, University of Canterbury. Electrical and Computer Engineering, 2008. http://hdl.handle.net/10092/1261.
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Performance lapses in occupations where public safety is paramount can have disastrous consequences, resulting in accidents with multiple fatalities. Drowsy individuals performing an active task, like driving, often cycle rapidly between periods of wake and sleep, as exhibited by cyclical variation in both EEG power spectra and task performance measures. The aim of this project was to identify reliable physiological cues indicative of lapses, related to behavioural microsleep episodes, from the EEG, which could in turn be used to develop a real-time lapse detection (or better still, prediction) system. Additionally, the project also sought to achieve an increased understanding of the characteristics of lapses in responsiveness in normal subjects. A study was conducted to determine EEG and/or EOG cues (if any) that expert raters use to detect lapses that occur during a psychomotor vigilance task (PVT), with the subsequent goal of using these cues to design an automated system. A previously-collected dataset comprising physiological and performance data of 10 air traffic controllers (ATCs) was used. Analysis showed that the experts were unable to detect the vast majority of lapses based on EEG and EOG cues. This suggested that, unlike automated sleep staging, an automated lapse detection system needed to identify features not generally visible in the EEG. Limitations in the ATC dataset led to a study where more comprehensive physiological and performance data were collected from normal subjects. Fifteen non-sleep-deprived male volunteers aged 18-36 years were recruited. All performed a 1-D continuous pursuit visuomotor tracking task for 1 hour during each of two sessions that occurred between 1 and 7 weeks apart. A video camera was used to record head and facial expressions of the subject. EEG was recorded from electrodes at 16 scalp locations according to the 10-20 system at 256 Hz. Vertical and horizontal EOG was also recorded. All experimental sessions were held between 12:30 and 17:00 hours. Subjects were asked to refrain from consuming stimulants or depressants, for 4 h prior to each session. Rate and duration were estimated for lapses identified by a tracking flat spot and/or video sleep. Fourteen of the 15 subjects had one or more lapses, with an overall rate of 39.3 ± 12.9 lapses per hour (mean ± SE) and a lapse duration of 3.4 ± 0.5 s. The study also showed that lapsing and tracking error increased during the first 30 or so min of a 1-h session, then decreased during the remaining time, despite the absence of external temporal cues. EEG spectral power was found to be higher during lapses in the delta, theta, and alpha bands, and lower in the beta, gamma, and higher bands, but correlations between changes in EEG power and lapses were low. Thus, complete lapses in responsiveness are a frequent phenomenon in normal subjects - even when not sleep-deprived - undertaking an extended, monotonous, continuous visuomotor task. This is the first study to investigate and report on the characteristics of complete lapses of responsiveness during a continuous tracking task in non-sleep-deprived subjects. The extent to which non-sleep-deprived subjects experience complete lapses in responsiveness during normal working hours was unexpected. Such findings will be of major concern to individuals and companies in various transport sectors. Models based on EEG power spectral features, such as power in the traditional bands and ratios between bands, were developed to detect the change of brain state during behavioural microsleeps. Several other techniques including spectral coherence and asymmetry, fractal dimension, approximate entropy, and Lempel-Ziv (LZ) complexity were also used to form detection models. Following the removal of eye blink artifacts from the EEG, the signal was transformed into z-scores relative to the baseline of the signal. An epoch length of 2 s and an overlap of 1 s (50%) between successive epochs were used for all signal processing algorithms. Principal component analysis was used to reduce redundancy in the features extracted from the 16 EEG derivations. Linear discriminant analysis was used to form individual classification models capable of detecting lapses using data from each subject. The overall detection model was formed by combining the outputs of the individual models using stacked generalization with constrained least-squares fitting used to determine the optimal meta-learner weights of the stacked system. The performance of the lapse detector was measured both in terms of its ability to detect lapse state (in 1-s epochs) and lapse events. Best performance in lapse state detection was achieved using the detector based on spectral power (SP) features (mean correlation of φ = 0.39 ± 0.06). Lapse event detection performance using SP features was moderate at best (sensitivity = 73.5%, selectivity = 25.5%). LZ complexity feature-based detector showed the highest performance (φ = 0.28 ± 0.06) out of the 3 non-linear feature-based detectors. The SP+LZ feature-based model had no improvement in performance over the detector based on SP alone, suggesting that LZ features contributed no additional information. Alpha power contributed the most to the overall SP-based detection model. Analysis showed that the lapse detection model was detecting phasic, rather than tonic, changes in the level of drowsiness. The performance of these EEG-based lapse detection systems is modest. Further research is needed to develop more sensitive methods to extract cues from the EEG leading to devices capable of detecting and/or predicting lapses.
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Mathew, Blesy Anu. "ENTROPY OF ELECTROENCEPHALOGRAM (EEG) SIGNALS CHANGES WITH SLEEP STATE". UKnowledge, 2006. http://uknowledge.uky.edu/gradschool_theses/203.
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We hypothesized that temporal features of EEG are altered in sleep apnea subjects comparedto normal subjects. The initial aim was to develop a measure to discriminate sleep stages innormals. The longer-term goal was to apply these methods to identify differences in EEGactivity in sleep apnea subjects from normals. We analyzed the C3A2 EEG and anelectrooculogram (EOG) recorded from 9 normal adults awake and in rapid eye movement(REM) and non-REM sleep. The EEG signals were filtered to remove EOG contamination. Twomeasures of the irregularity of EEG signals, Sample Entropy (SpEn) and Tsallis Entropy, wereevaluated for their ability to discriminate sleep stages. SpEn changes with sleep state, beinglargest in Wake. Stage 3/4 had the smallest SpEn (0.57??0.11) normalized to Wake values,followed by Stage 2 (0.72??0.09), REM (0.75??0.1) and Stage 1 (0.89??0.05). This pattern wasconsistent in all the polysomnogram records analyzed. Similar pattern was observed in leadO1A2 as well. We conclude that SpEn may be useful as part of a montage for assessing sleepstate. We analyzed data from sleep apnea subjects having obstructive and central apnea eventsand have made some preliminary observations; the SpEn values were more similar across sleepstages and also high correlation with oxygen saturation was observed.
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Hartmann, Daniel Michael. "Einsatz eines superfundierten Retina-RPE-Choroidea Präparats vom Haushuhn (Gallus domesticus) zur Untersuchung pharmakologischer Wirkungen mittels in vitro elektroretinographischer Erfassung (ERG und EOG) von okulären Funktionen". [S.l. : s.n.], 2004. http://www.bsz-bw.de/cgi-bin/xvms.cgi?SWB11679860.
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Escola, Henri. "Analyse et traitement de signaux physiologiques pour la mesure de l'action de substances pharmacologiques". Compiègne, 1993. http://www.theses.fr/1993COMPD593.
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L'objectif de ce travail est de proposer des méthodes d'analyse de de traitement des signaux physiologiques (EEG, EMG, EOG) tant diurnes (Chap. II) que nocturnes (Chap. III, IV, V). Nous présentons dans un premier temps une méthode d'analyse qualitative basée sur la notion de distance dans un espace multidimensionnel qui peut venir compléter la cartographie cérébrale classique (Chap. II). Pour l'étude du sommeil, nous proposons de décrire l'activité EEG par plusieurs types de paramètres continus. Nous montrons également comment des variables capables de mettre en évidence les effets de substances pharmacologiques peuvent être extraites de ces différents paramètres (Chap. III). Pour caractériser le signal EOG, Nous avons développé une méthode de détection automatique des mouvements oculaires permettant de mesurer l'action de deux substances sur cette activité (Chap. IV). Pour finir, nous tentons de faire une synthèse des résultats obtenus dans les chapitres précédents en jetant les bases d'une analyse ou les différents signaux sont pris simultanément en considération. Plusieurs techniques (corrélation, indice de dispersion, prédiction non-linéaire) sont évaluées toujours dans le cadre d'une étude pharmacologique (Chap. V)
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Svensson, Ulrika. "Blinkbeteendebaserad trötthetsdetektering : metodutveckling och validering". Thesis, Linköping University, Department of Biomedical Engineering, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2578.
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Electrooculogram (EOG) data was used to develop, adjust and validate a method for drowsiness detection in drivers. The drowsiness detection was based on changes in blink behaviour and classification was made on a four graded scale. The purpose was to detect early signs of drowsiness in order to warn a driver. MATLAB was used for implementation. For adjustment and validatation, two different reference measures were used; driver reported ratings of drowsiness and an electroencephalogram (EEG) based scoring scale. A correspondence of 70 % was obtained between the program and the self ratings and 56 % between the program and the EEG based scoring scale. The results show a possibility to detect drowsiness by analyzing blink behaviour changes, but that inter-individual differences need to be considered. It is also difficult to find a comparable reference measure. The comparability of the blink based scale and the EEG based scale needs further investigation.
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Bissoli, A. L. C. "Solução Multimodal para Interação Com Dispositivos de Assistência e Comunicação". Universidade Federal do Espírito Santo, 2016. http://repositorio.ufes.br/handle/10/9549.
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Previous issue date: 2016-07-29Pessoas com deficiência têm dificuldade de interagir com o ambiente onde vivem, devido às próprias limitações inerentes à sua deficiência. Atividades simples como ligar lâmpada, ventilador, televisão ou qualquer outro equipamento, de forma independente, pode ser impossível para esse grupo de pessoas. Este trabalho apresenta um sistema assistivo multimodal para controlar um ambiente inteligente por meio de sinais biológicos. Os usuários em potencial deste sistema são indivíduos com deficiências motoras graves, que desejam adquirir mais autonomia dentro do ambiente doméstico. Os sinais biológicos utilizados são sEMG, EOG e VOG. Isso possibilitou dois tipos de interação: uma empregando gestos faciais e movimento dos olhos, e a outra utilizando o rastreamento das fixações do olhar (eye/gaze tracking). Um diferencial importante deste trabalho é a utilização de dispositivos convencionais de baixo custo, fácil manuseio e de rápida configuração. No primeiro bloco de testes, o objetivo era avaliar o desempenho do sistema utilizando o Emotiv EPOC e o Eye Tracker, comparando a Taxa de Transferência de Informação (ITR) e a Utilidade (U) de ambas as Interfaces Humano-Máquina (IHM) desenvolvidas para controlar o Ambiente Inteligente. Para esses testes foram pré-estabelecidas cinco tarefas, as quais foram realizadas por dez voluntários. No segundo bloco de testes, o objetivo era avaliar a usabilidade (SUS) e o desempenho (GAS) do sistema do ponto de vista do usuário, utilizando o Eye Tracker em três aplicações diferentes: Controle do Ambiente Inteligente (AI), Comunicação Aumentativa e Alternativa (CAA) e Ambiente Virtual (AV). Os testes foram realizados por 17 voluntários (sendo dois com deficiência em todas as aplicações) e foram pré-estabelecidas 5, 5 e 18 tarefas para as três aplicações (AI, CAA e AV, respectivamente). Com relação aos resultados da avaliação de desempenho, observou-se que 15 dos 17 participantes obtiveram resultado esperado ou superior ao esperado logo na primeira utilização. Este resultado ainda pode ser melhorado, à medida que o participante obtiver maior familiaridade com o sistema.
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Laurent, François. "Détection de la fatigue mentale à partir de données électrophysiologiques". Phd thesis, Université Pierre et Marie Curie - Paris VI, 2010. http://tel.archives-ouvertes.fr/tel-00634776.
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Trois expériences ont été réalisées pour évaluer la faisabilité d'un détecteur de fatigue mentale qui exploiterait des signaux électrophysiologiques pour discriminer des fenêtres de temps associées à un état " fatigué " de fenêtres associées à un état " pas fatigué ". Dans la première expérience, les sujets réalisaient une tâche de task switching pendant environ 2 h. Deux segments de 20 min ont été retenus pour chaque sujet. Le premier a été associé à un état " pas fatigué ", l'autre à un état " fatigué ". Puis ces segments ont été découpés en fenêtres de temps glissantes sur lesquelles les signaux électrophysiologiques (EOG, ECG et EEG) ont été quantifiés. L'usage de SVM linéaires (appris sujet par sujet) pour la classification des fenêtres de temps a permis plusieurs observations. Le taux de bonnes classifications augmentaient avec la taille des fenêtres de temps (de 4 à 30 s) mais pas assez pour que l'ITR augmentât lui aussi avec cette taille des fenêtres. Les quantifications de l'EOG se plaçaient derrière celles de l'ECG, elles-mêmes supplantées par les amplitudes moyennes de l'EEG qui elles aussi étaient dépassées par les PLV de l'EEG en termes de taux de bonnes classifications avec (pour les PLV) des taux supérieurs à 90 %. L'examen des poids SVM permît de constater que les quantifications d'EOG et en particulier d'ECG contribuaient à la classification lorsque toutes les quantifications des différentes modalités étaient utilisées ensemble, en utilisant des fenêtres de temps de 30 s. Les amplitudes moyennes de l'EEG augmentaient en 7-13 Hz et diminuaient en 13-18 Hz. En 3-7 Hz apparaissait une augmentation en FCz évoquant la négativité d'erreur. Dans une deuxième expérience avec une tâche de compatibilité spatiale, nous avons discriminé des fenêtres de 20 s entre un niveau de bonnes performances (temps moyen de réaction courts) et un niveau de moins bonnes performances, en quantifiant ces fenêtres à l'aide des amplitudes moyennes, des PLV ou des cohérences de l'EEG, au niveau du scalp et au niveau de sources reconstruites sur le cortex cérébral. Nous nous attendions à des meilleurs taux de bonnes classifications avec les sources reconstruites qu'avec les données de scalp, quelque soit la quantification, mais ce ne fût pas le cas. Nous avons également réalisé une simulation reprenant l'essentiel des analyses réalisées précédemment et en provoquant deux phénomènes, l'un à travers l'amplitude de signaux utiles à la classification, l'autre jouant sur le couplage entre deux signaux utiles. Ces simulations ont montré d'une part la complémentarité des mesures de synchronie locale, telles que l'amplitude moyenne, avec les mesures de synchronie à distance telles que la cohérence ou la PLV, et d'autre part l'apport de la reconstruction de sources en termes de taux de bonnes classifications et de localisation des motifs discriminants. Cette incompatibilité entre les résultats sur données simulées et ceux sur les données EEG réelles est interprétée ici comme la conséquence de la non-prise en compte, dans le processus de reconstruction, de sources extra-corticales comme les sources cérébrales sous-corticales et les sources extra-craniennes (yeux, muscles) qui pourraient avoir eu une contribution. La troisième étude portait sur une troisième expérience en contexte écologique cette fois-ci, impliquant les élèves-pilotes dans un simulateur de vol. La simulation durait près de 3 h et les signaux EEG ainsi que trois paramètres de vol (cap, altitude, vitesse) ont été enregistrés. Nous avons proposé une mesure comportementale quantifiant la variabilité des paramètres de vol, par fenêtres de 10 s, pour suivre la performance des pilotes avec une résolution temporelle adaptée à nos analyses. Nous avons construit deux classes, à savoir un groupe de fenêtres de temps de 10 s associé aux bonnes performances (variabilité faible) et un second groupe de fenêtres associé aux moins bonnes performances. Plutôt que d'utiliser une procédure de validation croisée, nous avons évalué les classifieurs appris sur des données postérieures aux données d'apprentissage, de manière à évaluer la capacité de la procédure de classification à déterminer la tendance générale des performances du pilote. Cette procédure permettait effectivement de déterminer si les performances des pilotes se dégradaient en fin de vol ou pas, ce pour 12 sujets sur 13. Les corrélats physiologiques exhibés ne correspondaient pas d'une expérience à une autre ce qui laissait penser que soit les différentes manières de construire les classes ne permettaient pas d'isoler un même différentiel de fatigue mentale, soit la fatigue mentale telle qu'observée à travers les techniques électrophysiologiques employées dépendait de la tâche et/ou des sujets. En revanche, la faisabilité d'une discrimination d'états mentaux proches de réalités opérationnelles a été établie.
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Hartmann, Daniel Michael [Verfasser]. "Einsatz eines superfundierten Retina-RPE-Choroidea-Präparats vom Haushuhn (Gallus domesticus) zur Untersuchung pharmakologischer Wirkungen mittels in-vitro-elektroretinographischer Erfassung (ERG und EOG) von okulären Funktionen / vorgelegt von Daniel Michael Hartmann". Tübingen, Stöcklestr. 22 : D. M. Hartmann, 2004. http://d-nb.info/973244127/34.
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Vennelaganti, Swetha. "AGING AND SLEEP STAGE EFFECTS ON ENTROPY OF ELECTROENCEPHALOGRAM SIGNALS". UKnowledge, 2008. http://uknowledge.uky.edu/gradschool_theses/553.
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The aging brain is characterized by alteration in synaptic contacts, which leads to decline of motor and cognitive functions. These changes are reflected in the age related shifts in power spectrum of electroencephalogram (EEG) signals in both wakefulness and sleep. Various non-linear measures have been used to obtain more insights from EEG analysis compared to the conventional spectral analysis. In our study we used Sample Entropy to quantify regularity of the EEG signal. Because elderly subjects arouse from sleep more often than younger subjects, we hypothesized that Entropy of EEG signals from elderly subjects would be higher than that from middle aged subjects, within a sleep stage. We also hypothesized that the entropy increases during and following an arousal and does not return to background levels immediately after an arousal. Our results show that Sample Entropy varies systematically with sleep state in healthy middle-aged and elderly female subjects, reflecting the changing regularity in the EEG. Sample Entropy is significantly higher in elderly in sleep Stage 2 and REM, suggesting that in these two sleep stages the cortical state is closer to wake than in middle-aged women. Sample Entropy is higher in post-arousal compared to the pre-arousal and stays high for a 30 sec period.
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Romero, Lafuente Sergio. "Reducción de artefactos en señales electroencefalográficas mediante nuevas técnicas de filtrado automático basadas en separación ciega de fuentes". Doctoral thesis, Universitat Politècnica de Catalunya, 2010. http://hdl.handle.net/10803/6208.
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El análisis cuantitativo y la interpretación de las señales electroencefalográficas (EEG) permiten la comprensión de la función cerebral, ayudando al diagnóstico de estados disfuncionales. Sin embargo, es conocido que cierta actividad de origen no cortical contribuye también en los registros de EEG, siendo el caso más crítico y relevante el producido por la contaminación debida a la actividad ocular. El método considerado gold standard en neuropsicofarmacología para la reducción de artefactos oculares en señales EEG está basado en la regresión lineal. Sin embargo, esta técnica no sólo reduce la contaminación ocular sino que también elimina cierta actividad cerebral. Por tanto, el desarrollo de nuevos métodos automáticos para la reducción de la actividad ocular presente en las señales EEG, que superen las limitaciones presentadas por los métodos actualmente más utilizados, constituye un paso definitivo en los ensayos clínicos dedicados a evaluar los efectos de un fármaco en el sistema nervioso central. El objetivo principal de la tesis es el diseño y evaluación objetiva de métodos automáticos de filtrado de artefactos oculares en señales EEG espontáneas para la mejora cuantitativa en los estudios de fármaco-EEG. Para ello, se estudian las diferentes situaciones de contaminación ocular en las señales EEG y su problemática bajo la situación de vigilia, mediante bases de datos de registros adquiridos en voluntarios sanos tras la administración de fármacos. Se describen los métodos clásicos de filtrado ocular y la implementación del nuevo método de filtrado automático basado en BSS. La situación más propicia para una evaluación objetiva de los diferentes métodos de filtrado ocular precisa la utilización de señales electrooculográficas (EOG) y EEG simuladas, donde las actividades ocular y cerebral puedan ser conocidas de antemano. Se generan señales simuladas a partir de la mezcla de las actividades ocular y cerebral (extraídas de señales EOG y EEG reales) mediante dos estrategias: mezclas instantáneas y mezclas convolutivas. Se realiza un análisis comparativo de la eficacia de los métodos de filtrado ocular en las señales simuladas. A continuación, se determina el impacto del filtrado ocular en la evaluación de los efectos inducidos por un fármaco en el cerebro, comparando el método propuesto basado en BSS con el procedimiento considerado gold standard.
A partir de los resultados obtenidos se puede concluir que el método para la reducción de artefactos oculares basado en BSS propuesto en esta tesis doctoral muestra un mejor comportamiento que el método gold standard tanto en señales simuladas [Romero et al, 2008] [Romero et al, 2009a] como en señales reales [Romero et al, 2009b].
Las aportaciones más relevantes de esta tesis son: 1) La implementación de un nuevo método completamente automático para el filtrado de la contaminación ocular en señales EEG. Este método está basado en los algoritmos de BSS AMUSE o SOBI indistintamente, se aplica a segmentos de corta duración, e incluye la detección automática de las componentes fuente asociadas a la actividad ocular. 2) La estimación de modelos MISO que reflejan la propagación de las actividades ocular y cerebral a lo largo del cuero cabelludo. Dichos modelos han permitido aportar información para aclarar la discusión acerca de la dependencia o independencia de la frecuencia en la propagación ocular. Estos resultados afirman que ambas propagaciones de la actividad ocular y cerebral pueden considerarse independientes de la frecuencia, y por tanto totalmente de acuerdo con lo esperado a partir del conocimiento biofísico existente. 3) La realización de una herramienta informática para el procesado de señales EEG en estudios de fármaco-EEG. Esta interfaz gráfica interactiva ya ha empezado a ser utilizada en diversos estudios de evaluación del efecto de un fármaco en el sistema nervioso central [Alonso et al., 2010], por el CIM del Hospital de la Santa Creu i Sant Pau de Barcelona.
Quantitative analysis and interpretation of electroencefalographic (EEG) signals are useful methods to study functional states of the brain, to evaluate drug effects and to diagnose psychiatric and neurological disorders. However, it is known that non-cortical interferences contribute to EEG recordings. Ocular artifacts are the most relevant and critical interference. The gold standard method in neuropsychopharmacology for reducing ocular contamination is based on linear regression. Nevertheless, this technique not only reduces the ocular contamination, but also cancels relevant cerebral information contained in the electrooculographic (EOG) recordings. In this way, the development of new automatic methods for reducing ocular artifacts in EEG signals, that solve the drawbacks shown by most common used techniques, is a crucial step in the clinical trials that assess the effects of a drug in the central nervous system.
The aim of this PhD thesis is the design and the objective evaluation of automatic ocular filtering methods in spontaneous EEG signals in order to quantitatively improve the results and conclusions obtained in pharmaco-EEG studies. Thus, different ocular contamination situations in EEG signals are evaluated in order to understand this problematic situation during wakefulness by means of databases acquired from healthy volunteers after drug administration. The classical ocular filtering methods and the implementation of a new automatic procedure based on blind source separation (BSS) are described. The best situation for an objective evaluation of the different ocular reduction methods needs the use of simulated EOG and EEG signals, where ocular and cerebral activities can be known a priori. Simulated signals are generated from a linear mixture between ocular and cerebral activities (extracted from real EOG and EEG signals) by means of two strategies: instantaneous and convolutive mixing models. A comparative analysis of the effectiveness of the filtering methods on the simulated signals is performed. Next, the influence of ocular filtering procedures in the conclusions drawn from a pharmaco-EEG trial is assessed, comparing the method proposed in this PhD thesis based on BSS with the gold standard procedure.
From the results obtained in time and frequency domain, it can be concluded that the method for reducing ocular artifacts based on BSS, developed in this PhD thesis, shows a better performance than the gold standard procedure in simulated signals [Romero et al, 2008] [Romero et al, 2009a] as much as in real signals [Romero et al, 2009b].
The most relevant contributions of this thesis are: 1) The implementation of a new completely automatic method for reducing ocular contamination in EEG signals. This procedure is based on the BSS algorithms, AMUSE or SOBI indistinctly, it is applied in short duration segments, and it includes the automatic detection of the source components related to ocular activity. 2) The estimation of MISO models corresponding to the propagation of ocular and cerebral activities across the scalp. These models have contributed with interesting information about the discussion if ocular propagation is frequency dependent or independent. These results conclude that ocular and cerebral propagation can be considered practically frequency independent which is consistent to what would be expected from the biophysics knowledge. 3) The development of a computer tool for EEG signals processing in pharmaco-EEG studies. The Drug Research Center (CIM) of the Hospital de la Santa Creu i Sant Pau of Barcelona has started to use this interactive graphical user interface for evaluating the effect of a drug on the brain in several pharmaco-EEG studies [Alonso et al, 2010].
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Díaz, Suarez José Edgard, i Vargas Christian Ricardo Morales. "Desarrollo de una interfaz mediante señales EOG para el manejo de la computadora por parte de una persona con discapacidad en los miembros superiores". Bachelor's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2019. http://hdl.handle.net/10757/652754.
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La presente tesis propone el diseño de un sistema que trabaja con señales electro oculográficas para luego procesarlas e interpretarlas con la finalidad de que el usuario pueda realizar trabajos con el ordenador usando únicamente el músculo ocular. El problema que se resuelve tiene una inclinación técnico ingenieril, ya que busca subsanar las debilidades y cubrir los aspectos no tocados por el estado del arte presente, para finalmente diseñar un equipo electrónico que permita la interacción de un usuario con un computador bajo las necesidades de una persona con discapacidad en los miembros superiores. El dispositivo diseñado está compuesto por un circuito capaz de adquirir por medio de electrodos la señal EOG de una persona, procesarla y analizarla para conocer la forma de onda y posteriormente interpretarla y enviar un carácter de reconocimiento de forma de onda usando un bluetooth a una computadora con la que se debe aparear con anterioridad. Esta computadora constará de un software que se diseñó en la presente tesis el será capaz de interpretar los caracteres recibidos y realizar funciones de movimiento y pulsación de un mouse, además de escritura usando un teclado virtual. Para validar el dispositivo diseñado se hicieron pruebas con 16 personas, de las cuales 14 fueron personas sin discapacidad en los miembros superiores y 2 de ellas sí. No se trabajaron con pacientes de un centro de salud específico, se realizaron pruebas con personas contactadas por médicos y fisioterapeutas entre los cuales se encuentran algunos que trabajan para la UPC los cuales brindaron su incondicional apoyo para la validación y pruebas con los pacientes a su cargo. Los resultados obtenidos en las pruebas realizadas muestran que de un grupo de 16 personas la eficiencia en el reconocimiento de la forma de onda de un doble parpadeo es del 92.9%, del parpadeo – mirada arriba y parpadeo – mirada abajo 88.4% y del parpadeo prolongado 93%. El valor trazado como objetivo fue 80% a más, por lo que se logra cumplir con ello.The present thesis proposes the design of a system that works with electro-occupational signals and then processes and interprets them so that the user can work with the computer using only the ocular muscle. The problem that is solved has a technical engineering inclination, since it seeks to correct the weaknesses and cover the aspects not touched by the present state of the art, to finally design an electronic equipment that allows the interaction of a user with a computer under the needs of a person with a disability in the upper limbs. The designed device is composed of a circuit capable of acquiring through electrodes the EOG signal of a person, processing and analyzing it to know the waveform and then interpret it and send a waveform recognition character using a bluetooth to a computer with which it must be paired in advance. This computer will consist of software that was designed in the present thesis and will be able to interpret the received characters and perform functions of moving and pressing a mouse, as well as writing using a virtual keyboard. In order to validate the designed device, tests were made with 16 people, of which 14 were people without disabilities in the upper limbs and 2 of them were. We did not work with patients from a specific health centre, but tested with people contacted by doctors and physiotherapists, including some who work for the UPC, who provided their unconditional support for validation and testing with the patients in their care. The results obtained in the tests carried out show that out of a group of 16 people the efficiency in the recognition of the waveform of a double blink is 92.9%, of the blink - look up and blink - look down 88.4% and of the prolonged blink 93%. The target value was 80% to more, so it is achieved.
Tesis
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伊月, 宣之. "強度視力障害者の眼電位図(EOG)測定法の開発に関する研究". 京都大学, 1996. http://hdl.handle.net/2433/160799.
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本文データは平成22年度国立国会図書館の学位論文(博士)のデジタル化実施により作成された画像ファイルを基にpdf変換したものであるKyoto University (京都大学)
0048
新制・論文博士
博士(工学)
乙第9204号
論工博第3107号
新制||工||1039(附属図書館)
UT51-96-F441
(主査)教授 西川 禕一, 教授 安陪 稔, 教授 池田 光男
学位規則第4条第2項該当
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Němcová, Andrea. "Hodnocení únavy pomocí elektrookulografie". Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2014. http://www.nusl.cz/ntk/nusl-220869.
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The master´s thesis deals with fatigue evaluation in electrooculography records (EOG). The theoretical part focuses on electrooculography itself, fatigue and methods used for fatigue detection from EOG. The practical part includes a plan of optimal methodology for fatigue evaluation using EOG. The EOG signals are recorded during the volunteers are watching prepared scenes. Those scenes are desribed here. There is also definition of signal processing methods with relevant block diagrams. Laboratory protocol describing EOG signals recording using Biopac data acquisition system is included. Ten volunteers were measured according to this protocol and the signal database was created. In brief questionnaire volunteers were supposed to evaluate fatigue and discomfort of the measurment. Recorded signals were processed and acquired parameters were statistically evaluated. Then the parameters were discussed in terms of fatigue detection ability. On the basis of that software application was created. This application detects fatigue in selected signal. The thesis includes detailed laboratory manual for students.
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Hooshidar, Daniel, i Yobart Amino. "Implementation av portabla REM-identifierande sensorer : Undersökning kring lämpliga, icke-påträngande metoder för REM-igenkänning". Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-232117.
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Trötthet i trafiken är ett stort problem i samhället. Det är särskilt farligt att trött framföra tunga lastbilar i trafiken eftersom dessa fordon är stora och har ofta livsavgörande roller vid inblandning i trafikolyckor. För att angripa problemet har det i denna rapport studerats kring vilket sömnstadie som är lämpligast att vakna under, i syfte att vakna pigg och alert samt vilka typer av tekniker och metoder som är lämpliga för att portabelt kunna detektera Rapid-Eye-Movement. Tidigare arbeten och studier har gjorts som påvisar att uppväckning i REM-sömn är optimalt för att känna sig alert. De valda metoderna är baserade på varianter av väletablerade tekniker som används för identifiering av sömnsteg. Elektrookulografi används för att mäta ögonrörelser med hjälp av fyra elektroder som är placerade på huvudet. Kroppsrörelser upptäcks genom en accelerometer som fästs på armen. Pulsmätningar görs och används för att räkna ut pulsvariansen under sömnen. Målet är att skapa en prototyp som ska känna av när användaren är i REM-sömn och sedan väcka användaren. Detta arbete är uppdelat i två inbyggda system som görs mellan två olika examensarbeten. Resultatet blev tre sensorer som fungerar individuellt. På grund av tidsbrist och en längre felsökning blev prototypen inte färdigställd. Innan sensorerna kan tillämpas i en produkt krävs det att ytterligare tester genomförs under monitorering av en sömnspecialist.Tiredness in traffic is a major problem in society. It is especially dangerous to drive heavy trucks when tired because these vehicles are large and often have vital roles when involved in traffic accidents. To address the problem, this degree project has studied which sleep stage is most appropriate to wake up during, in order to wake up sharp and alert, and what types of techniques and methods are suitable for portable detection of Rapid-Eye-Movement. Previous work and studies have been done which indicates that awakening during REM sleep is optimal for feeling alert. The chosen methods are based on variants of well-established techniques that are used to identify sleep stages. Electrooculography is used to measure eye movements using four electrodes placed on the head. Body movements are detected by an accelerometer attached to the arm. Pulse measurements are made and used to calculate the pulse variation during sleep. The goal is to create a prototype which will know when the user is in REM sleep and then wake the user up. This work is divided into two embedded systems that are made between two different degree projects. The result was three sensors that worked individually. Due to lack of time and a longer troubleshooting, the prototype was not completed. Before the sensors can be used in a product, additional tests are required under the supervision of a sleep specialist.
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Balli, Tugce. "Nonlinear analysis methods for modelling of EEG and ECG signals". Thesis, University of Essex, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.528852.
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Chen, Tsai Yuan. "Network Electrophysiology Sensor-On-A- Chip". Digital WPI, 2011. https://digitalcommons.wpi.edu/etd-dissertations/389.
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"
Electroencephalogram (EEG), Electrocardiogram (ECG), and Electromyogram (EMG) bio-potential signals are commonly recorded in clinical practice. Typically, patients are connected to a bulky and mains-powered instrument, which reduces their mobility and creates discomfort. This limits the acquisition time, prevents the continuous monitoring of patients, and can affect the diagnosis of illness. Therefore, there is a great demand for low-power, small-size, and ambulatory bio-potential signal acquisition systems.
Recent work on instrumentation amplifier design for bio-potential signals can be broadly classified as using one or both of two popular techniques: In the first, an AC-coupled signal path with a MOS-Bipolar pseudo resistor is used to obtain a low-frequency cutoff that passes the signal of interest while rejecting large dc offsets. In the second, a chopper stabilization technique is designed to reduce 1/f noise at low frequencies. However, both of these existing techniques lack control of low-frequency cutoff.
This thesis presents the design of a mixed- signal integrated circuit (IC) prototype to provide complete, programmable analog signal conditioning and analog-to-digital conversion of an electrophysiologic signal. A front-end amplifier is designed with low input referred noise of 1 uVrms, and common mode rejection ratio 102 dB. A novel second order sigma-delta analog- to-digital converter (ADC) with a feedback integrator from the sigma-delta output is presented to program the low-frequency cutoff, and to enable wide input common mode range of ¡Ãƒâ€œ0.3 V. The overall system is implemented in Jazz Semiconductor 0.18 um CMOS technology with power consumption 5.8 mW from ¡Ãƒâ€œ0.9V power supplies. "
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Mičánková, Veronika. "Kognitivní evokované potenciály a fixace očí při vizuální emoční stimulaci". Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2016. http://www.nusl.cz/ntk/nusl-220722.
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Cílem této diplomové práce je najít a popsat souvislost mezi fixací očí v emočně zabarveném stimulu, kterým je obrázek či video, a EEG signálu. K tomuto studiu je třeba vyvinout softwarové nástroje v prostředí Matlab k úpravě a zpracování dat získaných z eye trackeru a propojení s EEG signály pomocí nově vytvořených markerů. Na základě získaných znalostí o fixacích, jsou v prostředí BrainVision Analyzeru EEG data zpracovány a následně jsou segmentovány a průměrovány jako evokované potenciály pro jednotlivé stimuly (ERP a EfRP). Tato práce je vypracována ve spolupráci s Gipsa-lab v rámci výzkumného projektu.
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Abbaspour, Sara. "Proposing Combined Approaches to Remove ECG Artifacts from Surface EMG Signals". Licentiate thesis, Mälardalens högskola, Inbyggda system, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-27878.
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Electromyography (EMG) is a tool routinely used for a variety of applications in a very large breadth of disciplines. However, this signal is inevitably contaminated by various artifacts originated from different sources. Electrical activity of heart muscles, electrocardiogram (ECG), is one of sources which affects the EMG signals due to the proximity of the collection sites to the heart and makes its analysis non-reliable. Different methods have been proposed to remove ECG artifacts from surface EMG signals; however, in spite of numerous attempts to eliminate or reduce this artifact, the problem of accurate and effective de-noising of EMG still remains a challenge. In this study common methods such as high pass filter (HPF), gating method, spike clipping, hybrid technique, template subtraction, independent component analysis (ICA), wavelet transform, wavelet-ICA, artificial neural network (ANN), and adaptive noise canceller (ANC) and adaptive neuro-fuzzy inference system (ANFIS) are used to remove ECG artifacts from surface EMG signals and their accuracy and effectiveness is investigated. HPF, gating method and spike clipping are fast; however they remove useful information from EMG signals. Hybrid technique and ANC are time consuming. Template subtraction requires predetermined QRS pattern. Using wavelet transform some artifacts remain in the original signal and part of the desired signal is removed. ICA requires multi-channel signals. Wavelet-ICA approach does not require multi-channel signals; however, it is user-dependent. ANN and ANFIS have good performance, but it is possible to improve their results by combining them with other techniques. For some applications of EMG signals such as rehabilitation, motion control and motion prediction, the quality of EMG signals is very important. Furthermore, the artifact removal methods need to be online and automatic. Hence, efficient methods such as ANN-wavelet, adaptive subtraction and automated wavelet-ICA are proposed to effectively eliminate ECG artifacts from surface EMG signals. To compare the results of the investigated methods and the proposed methods in this study, clean EMG signals from biceps and deltoid muscles and ECG artifacts from pectoralis major muscle are recorded from five healthy subjects to create 10 channels of contaminated EMG signals by adding the recorded ECG artifacts to the clean EMG signals. The artifact removal methods are also applied to the 10 channels of real contaminated EMG signals from pectoralis major muscle of the left side. Evaluation criteria such as signal to noise ratio, relative error, correlation coefficient, elapsed time and power spectrum density are used to evaluate the performance of the proposed methods. It is found that the performance of the proposed ANN-wavelet method is superior to the other methods with a signal to noise ratio, relative error and correlation coefficient of 15.53, 0.01 and 0.98 respectively.Elektromyografi (EMG) är ett verktyg som rutinmässigt används för en mängd olika applikationer inom många discipliner. Dock är denna signal oundvikligen kontaminerad av artefakter som kommer från olika källor. Elektrisk aktivitet av hjärtmuskln, elektrokardiogram (EKG), är en av störkällorna som påverkar EMG-signalerna på grund av närheten till hjärtat och som försämrar analysens tillförlitlig. Olika metoder har föreslagits för att ta bort EKG artefakter från yt-EMG-signaler men trots många försök att eliminera eller minska denna artefakt, kvarstår problemet med korrekt och effektivt brusreducering av EMG. I denna studie har vanliga metoder för brusundertryckning undersökts, såsom högpassfilter (HPF), gatingmetod, spikklippning, hybridteknik, subtraktionsmetod, oberoende komponentanalys (ICA), wavelet, wavelet-ICA, artificiella neurala nätverk (ANN), och adaptiv brusreducering (ANC) och adaptiv neuro fuzzy inference system (ANFIS). Metorderna har använts för att avlägsna EKG- artefakter från yt-EMG-signaler och deras noggrannhet och effektivitet har undersökts. HPF, gatingmetod och spikklippning är snabba; men de tar även bort relevant information från EMG-signalen. Hybridteknik och ANC är tidskrävande. Subtraktionsmetoden kräver kännedom om QRS-mönstret.Wavelettransformen lämnade kvar vissa artefakter i signalen, och avlägsnade även endel av den ursprungliga EMG-signalen. ICA kräver flerkanaliga signaler. Wavelet-ICA kräver inte flerkanaliga signaler, men är däremot användarberoende. ANN och ANFIS har bra prestanda, men det är möjligt att förbättra resultaten genom att kombinera dem med andra tekniker. För vissa tillämpningar av EMG-signaler såsom rehabilitering, rörelsekontroll och prediktion, är kvaliteten på EMG-signalerna mycket viktigt. Dessutom måste de artefaktreducerande metoderna vara i realtid och automatiska. Detta innebär att metoderna ANN-wavelet, adaptiv subtraktion och automatiserad wavelet-ICA rekommenderas för effektiv eliminering av EKG-artefakter från yt-EMG-signaler. För att jämföra resultaten av de undersökta och föreslagna metoderna i denna studie, har rena EMG-signaler från biceps och delta-muskler, samt EKG-artefakter från stora bröstmuskeln spelats in från fem friska personer. För att skapa 10-kanaliga brusiga EMG-signaler har de inspelade EKG-artefakterna adderats till de rena EMG-signalerna. De olika artefaktreduceringsmetoderna har även tillämpats på 10 kanaler verkliga EMG signaler med artefakter, från stora bröstmuskeln på vänster sida. Utvärderingskriterier såsom signal-brusförhållandet, relativta felet, korrelationskoefficienten, förfluten tid och effektspektrumstäthet har använts för att utvärdera de föreslagna metoderna. Prestandan hos den föreslagna ANN-wavelet metoden befanns överlägsen de andra metoderna med ett signalbrusförhållande på 15,53, relativt fel på 0,01 och korrelationskoefficient på 0,98.
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Coughlin, Michael J., i n/a. "Calibration of Two Dimensional Saccadic Electro-Oculograms Using Artificial Neural Networks". Griffith University. School of Applied Psychology, 2003. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20030409.110949.
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The electro-oculogram (EOG) is the most widely used technique for recording eye movements in clinical settings. It is inexpensive, practical, and non-invasive. Use of EOG is usually restricted to horizontal recordings as vertical EOG contains eyelid artefact (Oster & Stern, 1980) and blinks. The ability to analyse two dimensional (2D) eye movements may provide additional diagnostic information on pathologies, and further insights into the nature of brain functioning. Simultaneous recording of both horizontal and vertical EOG also introduces other difficulties into calibration of the eye movements, such as different gains in the two signals, and misalignment of electrodes producing crosstalk. These transformations of the signals create problems in relating the two dimensional EOG to actual rotations of the eyes. The application of an artificial neural network (ANN) that could map 2D recordings into 2D eye positions would overcome this problem and improve the utility of EOG. To determine whether ANNs are capable of correctly calibrating the saccadic eye movement data from 2D EOG (i.e. performing the necessary inverse transformation), the ANNs were first tested on data generated from mathematical models of saccadic eye movements. Multi-layer perceptrons (MLPs) with non-linear activation functions and trained with back propagation proved to be capable of calibrating simulated EOG data to a mean accuracy of 0.33° of visual angle (SE = 0.01). Linear perceptrons (LPs) were only nearly half as accurate. For five subjects performing a saccadic eye movement task in the upper right quadrant of the visual field, the mean accuracy provided by the MLPs was 1.07° of visual angle (SE = 0.01) for EOG data, and 0.95° of visual angle (SE = 0.03) for infrared limbus reflection (IRIS®) data. MLPs enabled calibration of 2D saccadic EOG to an accuracy not significantly different to that obtained with the infrared limbus tracking data.
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Coughlin, Michael J. "Calibration of Two Dimensional Saccadic Electro-Oculograms Using Artificial Neural Networks". Thesis, Griffith University, 2003. http://hdl.handle.net/10072/365854.
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The electro-oculogram (EOG) is the most widely used technique for recording eye movements in clinical settings. It is inexpensive, practical, and non-invasive. Use of EOG is usually restricted to horizontal recordings as vertical EOG contains eyelid artefact (Oster & Stern, 1980) and blinks. The ability to analyse two dimensional (2D) eye movements may provide additional diagnostic information on pathologies, and further insights into the nature of brain functioning. Simultaneous recording of both horizontal and vertical EOG also introduces other difficulties into calibration of the eye movements, such as different gains in the two signals, and misalignment of electrodes producing crosstalk. These transformations of the signals create problems in relating the two dimensional EOG to actual rotations of the eyes. The application of an artificial neural network (ANN) that could map 2D recordings into 2D eye positions would overcome this problem and improve the utility of EOG. To determine whether ANNs are capable of correctly calibrating the saccadic eye movement data from 2D EOG (i.e. performing the necessary inverse transformation), the ANNs were first tested on data generated from mathematical models of saccadic eye movements. Multi-layer perceptrons (MLPs) with non-linear activation functions and trained with back propagation proved to be capable of calibrating simulated EOG data to a mean accuracy of 0.33° of visual angle (SE = 0.01). Linear perceptrons (LPs) were only nearly half as accurate. For five subjects performing a saccadic eye movement task in the upper right quadrant of the visual field, the mean accuracy provided by the MLPs was 1.07° of visual angle (SE = 0.01) for EOG data, and 0.95° of visual angle (SE = 0.03) for infrared limbus reflection (IRIS®) data. MLPs enabled calibration of 2D saccadic EOG to an accuracy not significantly different to that obtained with the infrared limbus tracking data.Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Applied Psychology
Griffith Health
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Fuchs, Bernhard [Verfasser]. "Integrierte Sensorschaltungen zur EKG- und EEG-Ableitung mit prädiktiver Signalverarbeitung / Bernhard Fuchs". Aachen : Shaker, 2004. http://d-nb.info/1172609055/34.
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Joseph, Jeff Varkey Joshy. "On the relationship between corticomuscular (EEG-EMG) phase coupling and muscular fatigue". Master's thesis, University of Cape Town, 2015. http://hdl.handle.net/11427/15543.
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Contradictory results have been shown in studies measuring the effect of muscle fatigue on the level of synchrony between the oscillatory, cortical and muscular electrical activities (also known as corticomuscular coupling). In every study, the standard method (coherence) used to measure the level of synchrony takes into account both the amplitude and phase of the two signals. However, the use of the phase lock value (PLV) has been over looked as a method for determining the level of synchrony. While the PLV is modulated purely by the phase between the two signals, it is unaffected by any amplitude variation. This study aims to determine whether amplitude variations in electroencephalography (EEG) and electromyography (EMG) could have caused the contradictory results when comparing pre-,during and post-fatigue measures of corticomuscular coupling, which consequently affected the conclusions drawn regarding the monitoring of fatigue by the central nervous system. A determination will be made regarding the contradictions by directly comparing the two methods (coherence and PLV) on the same dataset of simultaneously measured EEG and EMG signals throughout an isometric pre-, during and post-fatigue task.
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Souza, Pedro Victor Eugenio de. "Sistema de aquisição de sinais de EMG e ECG para plataforma Android". reponame:Repositório Institucional da UFPE, 2015. https://repositorio.ufpe.br/handle/123456789/14022.
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Este trabalho fala sobre o desenvolvimento de um protótipo de um sistema de aquisição de sinais de ECG e EMG, de baixo custo de fabricação, baixo consumo de energia e que se comunica via wireless, utilizando protocolo de comunicação Bluetooth, com dispositivos AndroidTM. O desenvolvimento desse protótipo teve como finalidade a monitorização, em tempo real, dos sinais de ECG e EMG de um indivíduo, durante a realização de atividades físicas. Neste equipamento procurou-se realizar o projeto dos amplificadores para sinais biológicos (ECG e EMG), que combinasse baixo consumo e portabilidade, ou seja, os componentes escolhidos para este trabalho objetivaram reduzir o tamanho do circuito. Além disso, a transmissão de dados via Bluetooth foi adequada para que esses dados fossem utilizados em um dispositivo AndroidTM (smartphone), gerando a oportunidade para uma nova gama de produtos, os quais possam integrar a tecnologia existente nos celulares modernos à tecnologia de instrumentação biomédica aplicada ao monitoramento remoto de sinais biológicos. Com o intuito de atingir esse objetivo, foram desenvolvidos os sistemas de controle e processamento, baseados na arquitetura RISC, amplificação e filtragem, fonte de alimentação e comunicação Bluetooth, integrados em duas placas de circuito impresso, ambas com dimensão de 3x5cm. O firmware do sistema de aquisição e o software de visualização, controle e armazenamento de sinal foram desenvolvidos com a finalidade de tornar compatível o sistema com a maioria dos dispositivos baseados no sistema operacional AndroidTM. O sistema foi testado, apresentando bom desempenho na transmissão de dados e boa estabilidade em relação ao armazenamento e controle do consumo de energia. Atualmente, este sistema vem sendo utilizado em projetos de pesquisa e dissertações de mestrado com a finalidade de identificar possíveis problemas ou adequações a serem realizadas, tanto ao nível de hardware como de software. Com o sistema validado muitas pessoas podem ser beneficiadas, pois esse equipamento une a praticidade e multifuncionalidade dos telefones AndroidTM com a tecnologia de aquisição e processamento de sinais biológicos.
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Taffese, T. (Tewodros). "A review of using EEG and EMG psychophysiological measurements in user experience research". Master's thesis, University of Oulu, 2017. http://urn.fi/URN:NBN:fi:oulu-201706022478.
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Application of psychophysiological measurement tools in user experience studies is continuously growing. The development, on one hand, originates from the advantages the tool’s capabilities bring to the user experience(UX) world. On the other hand, the continuous development of systems and devices and the corresponding need for more interactive systems motivate the user experience domain to navigate possible options of improvement.
The thesis reviews the use of electroencephalography (EEG) and electromyography (EMG) measurements in user experience research. Both types of measurements come to the UX domain with their unique advantages. Facial EMG is the most suitable tool to monitor the valence of emotion as well as aspects such as stress and focus. The use of EMG is dependent on the context of use and it is important to take those aspects into consideration when taking it into use. In addition EMG can be used as part a user experience design component. Its application could be implemented as interaction or biofeedback mechanisms.
From the emotion evaluation point of view, EEG is mostly used with respect to attention and withdrawal towards a system. Various aspects of emotion such as engagement, excitement, attention and focus can be evaluated using the tool. EEG can also be used as part of a user experience design component. Applications could be as a brain computer interface or feedback mechanisms for systems that can adjust themselves on the basis of such data.
The study is conducted as a narrative literature review. Background study was extensively done on user experience, psychophysiology, emotion studies, the nervous system and corresponding measurement tools. On the basis of continuous knowledge development, previous studies were assessed, classified, summarized and synthesized. Advantages, limitations, use contexts, application areas and future potentials of EEG and EMG were studied extensively. Results of the study have implications on user experience research domain, as well as industries that intend to produce products with rich user experience.
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Poiseau, Éric. "Traitement du signal appliqué à l'analyse des signaux EEG et ECG enregistrés pendant le sommeil". Compiègne, 1993. http://www.theses.fr/1993COMPD592.
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Ce mémoire concerne l'analyse des signaux EEG et ECG enregistrés pendant le sommeil en vue de l'identification automatique des différents stades du sommeil et de l'évaluation quantitative de l'effet de certaines drogues sur les paramètres électrophysiologiques les caractérisant. Le premier chapitre est un chapitre d'introduction qui présente les différents stades du sommeil. Il présente les conditions expérimentales d'acquisition des signaux utilisés pour l'évaluation des algorithmes décrits dans les chapitres suivants. Le second chapitre est consacré à l'exposé de méthodes d'analyse des signaux EEG durant le stade 2 du sommeil. Deux approches complémentaires ont été développées et validées. La première repose sur une technique de filtrage adapté. Le signal EEGB est convolué avec des "templates" simulant des formes types de fuseaux de sommeil et de complexes-K. La détection repose sur un algorithme multicritères mettant en jeu des seuils d'amplitude de durée et d'énergie. La deuxième approche utilise une analyse spectrale multi-canaux afin d'étudier la répartition énergétique de l'EEG à la surface du scalp en vue de la localisation de l'activité fuseau. Ces deux analyses mettent en évidence la présence de fuseaux de sommeil pendant les stades 3 et 4 du sommeil. Le troisième chapitre traite de l'étude de la variabilité du rythme cardiaque durant les différents stades du sommeil. Un algorithme pour la détection automatique des complexes QRS est proposé. Le processus de reconnaissance retenu repose sur l'étude des pseudo-périodicités morphologiques au sein du signal ECG. Il combine analyse morphologique et approche physiologique. L'algorithme a été utilisé pour l'étude des variations de l'intervalle R-R en fonction des différents stades du sommeil et de l'effet de substances pharmacologiques. Il est montré que certaines variations de l'intervalle R-R pourraient être utilisées pour prévoir les changements dans l'architecture du sommeil.
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Svärd, Daniel. "Design and evaluation of a capacitively coupled sensor readout circuit, toward contact-less ECG and EEG". Thesis, Linköping University, Department of Electrical Engineering, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-54520.
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In modern medicine, the measurement of electrophysiological signals play a key role in health monitoring and diagnostics. Electrical activity originating from our nerve and muscle cells conveys real-time information about our current health state. The two most common and actively used techniques for measuring such signals are electrocardiography (ECG) and electroencephalography (EEG).
These signals are very weak, reaching from a few millivolts down to tens of microvolts in amplitude, and have the majority of the power located at very low frequencies, from below 1 Hz up to 40 Hz. These characteristics sets very tough requirements on the electrical circuit designs used to measure them. Usually, measurement is performed by attaching electrodes with direct contact to the skin using an adhesive, conductive gel to fixate them. This method requires a clinical environment and is time consuming, tedious and may cause the patient discomfort.
This thesis investigates another method for such measurements; by using a non-contact, capacitively coupled sensor, many of these shortcomings can be overcome. While this method relieves some problems, it also introduces several design difficulties such as: circuit noise, extremely high input impedance and interference. A capacitively coupled sensor was created using the bottom layer of a printed circuit board (PCB) as a capacitor plate and placing it against the signal source, that acts as the opposite capacitor plate. The PCB solder mask layer and any air in between the two acts as the insulator to create a full capacitor. The signal picked up by this sensor was then amplified by 60 dB with a high input impedance amplifier circuit and further conditioned through filtering.
Two measurements were made of the same circuit, but with different input impedances; one with 10 MΩ and one with 10 GΩ input impedance. Additional filtering was designed to combat interference from the main power lines at 50 Hz and 150 Hz that was discovered during initial measurements. The circuits were characterized with their transfer functions, and the ability to amplify a very low-level, low frequency input signal. The results of these measurements show that high input impedance is of critical importance for the functionality of the sensor and that an input impedance of 10 GΩ is sufficient to produce a signal-to-noise ratio (SNR) of 9.7 dB after digital filtering with an input signal of 25 μV at 10 Hz.
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Shiman, Farid [Verfasser], i Niels [Akademischer Betreuer] Birbaumer. "EEG and ECoG features for Brain Computer Interface in Stroke Rehabilitation / Farid Shiman ; Betreuer: Niels Birbaumer". Tübingen : Universitätsbibliothek Tübingen, 2018. http://d-nb.info/1168232562/34.
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Pandey, Amare Ketsela Tesfaye and Amrit. "Empirical Evaluation of Machine Learning Algorithms based on EMG, ECG and GSR Data to Classify Emotional States". Thesis, Blekinge Tekniska Högskola, Sektionen för datavetenskap och kommunikation, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3673.
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The peripheral psychophysiological signals (EMG, ECG and GSR) of 13 participants were recorded in the well planned Cognition and Robotics lab at BTH University and 9 participants data were taken for further processing. Thirty(30) pictures of IAPS were shown to each participant individually as stimuli, and each picture was displayed for five-second intervals. Signal preprocessing, feature extraction and selection, models, datasets formation and data analysis and interpretation were done. The correlation between a combination of EMG, ECG and GSR signal and emotional states were investigated. 2- Dimensional valence-arousal model was used to represent emotional states. Finally, accuracy comparisons among selected machine learning classification algorithms have performed. Context: Psychophysiological measurement is one of the recent and popular ways to identify emotions when using computers or robots. It can be done using peripheral signals: Electromyography (EMG), Electrocardiography (ECG) and Galvanic Skin Response (GSR). The signals from these measurements are considered as reliable signals and can produce the required data. It is further carried out by preprocessing of data, feature selection and classification. Classification of EMG, ECG and GSR data can be conducted with appropriate machine learning algorithms for better accuracy results. Objectives: In this study, we investigate and analyzed with psychophysiological (EMG, ECG and GSR) data to find best classifier algorithm. Our main objective is to classify those data with appropriate machine learning techniques. Classifications of psychophysiological data are useful in emotion recognition. Therefore, our ultimate goal is to provide validated classified psychological measures for the automated adoption of human robot performance. Methods: We conducted a literature review in order to answer RQ1. The sources used are Inspec/ Compendex, IEEE, ACM Digital Library, Google Scholar and Springer Link. This helps us to identify suitable features required for the classification after reading the articles and papers that are peer reviewed as well as lie relevant to the area. Similarly, this helps us to select appropriate machine learning algorithms. We conducted an experiment in order to answer RQ2 and RQ3. A pilot experiment, then after main experiment was conducted in the Cognition and Robotics lab at the university. An experiment was conducted to take measures from EMG, ECG and GSR signal. Results: We obtained different accuracy results using different sets of datasets. The classification accuracy result was best given by the Support Vector Machine algorithm, which gives up to 59% classified emotional states correctly. Conclusions: The psychophysiological signals are very inconsistent with individual participant for specific emotion. Hence, the result we got from the experiment was higher with a single participant than all participants were together. Although, having large number of instances are good to train the classifier well.The thesis is focused to classify emotional states from physiological signals. Features extraction and selection of the physiological signal was done, which was used for dataset formation and then classification of those emotional states. IAPS pictures were used to elicit emotional/affective states. Experiment was conducted with 13 participants in cognition and Robotics lab using biosensors EMG, ECG and GSR at BTH University. Nine participants data were taken for further preprocessing. We observed in our thesis the classification of emotions which could be analyzed by a combination of psychophysiological signal as Model A and Model B. Since signals of subjects are different for same emotional state, the accuracy was better for single participant than all participants together. Classification of emotional states is useful for HCI and HRI to manufacture emotional intelligence robot. So, it is essential to provide best classifier algorithms which can be helpful to detect emotions for developing emotional intelligence robots. Our work contribution lies in providing best algorithms for emotion recognition for psychophysiological data and selected features. Most of the results showed that SVM performed best with classification accuracy up to 59 % for single participant and 48.05 % for all participants together. For a single dataset and single participant, we found 60.17 % accuracy from MLP but it consumed more time and memory than other algorithms during classification. The rest of the algorithms like BNT, Naive Bayes, KNN and J48 also gave competitive accuracy to SVM. We conclude that SVM algorithm for emotion recognition from a combination of EMG, ECG and GSR is capable of handling and giving better classification accuracy among others. Tally between IAPS pictures with SAM helped to remove less correlated signals and to obtain better accuracies. Still the obtained results are small in percentage. Therefore, more participants are probably needed to get a better accuracy result over the whole dataset.
amarehenry@gmail.com ; Mobile: 0767042234 amrit.pandey111@gmail.com ; Mobile : 0704763190
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Kurz, Stefan. "Das Verhältnis der EG-Fusionskontrollverordnung zu Artikel 85 und 86 des EWG-Vertrages /". Frankfurt am Main ;Berlin [u.a.] : Lang, 1993. http://www.gbv.de/dms/spk/sbb/recht/toc/271828463.pdf.
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Meste, Olivier. "Modélisations et Traitements de Signaux Biomédicaux". Habilitation à diriger des recherches, Université de Nice Sophia-Antipolis, 2003. http://tel.archives-ouvertes.fr/tel-00545558.
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Cette recherche a été menée dans le contexte scientifique proposé par l'équipe BIOMED (Pr. H. RIX), équipe qui regroupe des chercheurs du laboratoire I3S et des médecins (F. RAYBAUD, G. SUISSE) , Praticiens Hospitaliers, ayant une formation scientifique complémentaire (DEA ou Doctorat SPI). Cette association permet d'aborder des problèmes réels posés par la Médecine ou la Physiologie concernant l'interprétation des signaux biomédicaux. Mon activité au sein de cette équipe se situe dans le domaine du Traitement du Signal pour ce qui concerne l'élaboration de nouveaux concepts ou outils et en amont du Génie Biologique et Médical pour les applications. Dans le même type d'activité, on peut citer les équipes françaises de Jean-Louis COATRIEUX (INSERM- Rennes 1), Catherine MARQUE (CNRS-UTC), Jacques DUCHENE (UTT), Paul RUBEL (INSERM- INSA Lyon). Les principaux domaines d'application actuels sont l'électrocardiographie (ECG), les signaux électriques cérébraux (EEG et PE) et l'électromyographie (EMG) de surface. Les signaux étudiés sont donc des transitoires bruités souvent répétitifs. Ce sont soit des signaux 1D soit des signaux vectoriels constitués d'enregistrements simultanés provenant de capteurs diversement positionnés ou d'enregistrements successifs d'un même capteur. Les problèmes généraux rencontrés sont l'estimation de signaux moyens associés le plus souvent à des phénomènes permanents ou stables au cours du temps, la caractérisation de la variabilité naturelle et enfin la mesure de variations significatives de paramètres ou plus généralement de forme, liées à un agent extérieur tel qu'une pathologie, un effort ou un médicament. Les approches théoriques relèvent de la détection, de l'estimation de modèles paramétriques, semi-paramétriques ou non paramétriques et de la classification, dans le cas non stationnaire.
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Leonard, James W. Jr. "Replacing indirect manual assistive solutions with hands-free, direct selection". Wright State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=wright1309282777.
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Carvalho, Jhonnata Bezerra de. "Classificador m?quina de suporte vetorial com an?lise de Fourier aplicada em dados de EEG e EMG". Universidade Federal do Rio Grande do Norte, 2016. http://repositorio.ufrn.br/handle/123456789/20964.
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Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior (CAPES)
O classificador M?quina de Suporte Vetorial, que vem do termo em ingl?s \textit{Support Vector Machine}, ? utilizado em diversos problemas em v?rias ?reas do conhecimento. Basicamente o m?todo utilizado nesse classificador ? encontrar o hiperplano que maximiza a dist?ncia entre os grupos, para aumentar o poder de generaliza??o do classificador. Neste trabalho, s?o tratados alguns problemas de classifica??o bin?ria com dados obtidos atrav?s da eletroencefalografia (EEG) e eletromiografia (EMG), utilizando a M?quina de Suporte Vetorial com algumas t?cnicas complementares, destacadas a seguir como: An?lise de Componentes Principais para a identifica??o de regi?es ativas do c?rebro, o m?todo do periodograma que ? obtido atrav?s da An?lise de Fourier, para ajudar a discriminar os grupos e a suaviza??o por M?dias M?veis Simples para a redu??o dos ru?dos existentes nos dados. Foram desenvolvidas duas fun??es no $software$ \textbf{R}, para a realiza??o das tarefas de treinamento e classifica??o. Al?m disso, foram propostos 2 sistemas de pesos e uma medida sumarizadora para auxiliar na decis?o do grupo pertencente. A aplica??o dessas t?cnicas, pesos e a medida sumarizadora no classificador, mostraram resultados bastantes satisfat?rios, em que os melhores resultados encontrados foram, uma taxa m?dia de acerto de 95,31\% para dados de est?mulos visuais, 100\% de classifica??o correta para dados de epilepsia e taxas de acerto de 91,22\% e 96,89\% para dados de movimentos de objetos para dois indiv?duos.
The classifier support vector machine is used in several problems in various areas of knowledge. Basically the method used in this classier is to end the hyperplane that maximizes the distance between the groups, to increase the generalization of the classifier. In this work, we treated some problems of binary classification of data obtained by electroencephalography (EEG) and electromyography (EMG) using Support Vector Machine with some complementary techniques, such as: Principal Component Analysis to identify the active regions of the brain, the periodogram method which is obtained by Fourier analysis to help discriminate between groups and Simple Moving Average to eliminate some of the existing noise in the data. It was developed two functions in the software R, for the realization of training tasks and classification. Also, it was proposed two weights systems and a summarized measure to help on deciding in classification of groups. The application of these techniques, weights and the summarized measure in the classier, showed quite satisfactory results, where the best results were an average rate of 95.31% to visual stimuli data, 100% of correct classification for epilepsy data and rates of 91.22% and 96.89% to object motion data for two subjects.
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Ravelomanantsoa, Andrianiaina. "Approche déterministe de l'acquisition comprimée et la reconstruction des signaux issus de capteurs intelligents distribués". Thesis, Université de Lorraine, 2015. http://www.theses.fr/2015LORR0136/document.
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Le réseau sans fil sur le corps humain ou « wireless body area network (WBAN) » est une nouvelle technologie de réseau sans fil dédié à la surveillance des paramètres physiologiques d’une personne. Le réseau est composé de dispositifs électroniques miniatures, appelés nœuds, disposés aux alentours ou à l’intérieur du corps humain. Chaque nœud est doté d’un ou plusieurs capteurs mesurant les paramètres physiologiques de la personne, comme l’électrocardiogramme ou bien la température du corps, et les caractéristiques de l’environnement qui l’entoure. Ces nœuds sont surtout soumis à une contrainte énergétique importante puisque la miniaturisation a réduit les dimensions de leurs batteries. Puisque les nœuds consomment la majorité de l’énergie pour transmettre les données, une solution pour diminuer leur consommation consisterait à compresser les données avant la transmission. Les méthodes classiques de compression ne sont pas adaptées pour le WBAN particulièrement à cause de la puissance de calcul requise et la consommation qui en résulterait. Dans cette thèse, pour contourner ces problèmes, nous utilisons une méthode à base de l’acquisition comprimée pour compresser et reconstruire les données provenant des nœuds. Nous proposons un encodeur simple et facile à mettre en œuvre pour compresser les signaux. Nous présentons aussi un algorithme permettant de réduire la complexité de la phase de reconstruction des signaux. Un travail collaboratif avec l’entreprise TEA (Technologie Ergonomie Appliquées) nous a permis de valider expérimentalement une version numérique de l’encodeur et l’algorithme de reconstruction. Nous avons aussi développé et validé une version analogique de l’encodeur en utilisant des composants standardsA wireless body area network (WBAN) is a new class of wireless networks dedicated to monitor human physiological parameters. It consists of small electronic devices, also called nodes, attached to or implanted in the human body. Each node comprises one or many sensors which measure physiological signals, such as electrocardiogram or body heat, and the characteristics of the surrounding environment. These nodes are mainly subject to a significant energy constraint due to the fact that the miniaturization has reduced the size of their batteries. A solution to minimize the energy consumption would be to compress the sensed data before wirelessly transmitting them. Indeed, research has shown that most of the available energy are consumed by the wireless transmitter. Conventional compression methods are not suitable for WBANs because they involve a high computational power and increase the energy consumption. To overcome these limitations, we use compressed sensing (CS) to compress and recover the sensed data. We propose a simple and efficient encoder to compress the data. We also introduce a new algorithm to reduce the complexity of the recovery process. A partnership with TEA (Technologie Ergonomie Appliquées) company allowed us to experimentally evaluate the performance of the proposed method during which a numeric version of the encoder has been used. We also developed and validated an analog version of the encoder
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Thomas, Brigitta. "Die Europa-Politik Italiens : der Beitrag Italiens zur europäischen Einigung zwischen EVG und EG /". Baden-Baden : Nomos, 2005. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=013222886&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.
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Tolaszová, Eva. "Analýza EEG signálů při Stroopově testu". Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-218220.
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Master’s thesis deals with the measurement of biological signals for the effect of psychological burden. To monitor this effect was elected Stroop test, which is in the psychology used to detect disorders of attention and concentration. EEG and ECG signals during Stroop test were obtained using the EEG recording systém, in the context of research evoked potentials. As a part of the work it has been designed custom application for analyzing and interpreting data and statistical analysis by t-test.
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Klarkowski, Madison W. "The psychophysiological evaluation of the player experience". Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/112418/1/Madison_Klarkowski_Thesis.pdf.
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This thesis investigates the role of psychophysiology in the evaluation of the video game player experience. In doing so, it reports results from a program of research assessing the psychophysiological response of players to optimal and sub-optimal play experiences as moderated by challenge. The thesis identifies psychophysiological evaluation as an insightful and distinctive approach for assessing the player experience, proposes recommendations for the use of psychophysiology in related research, and clarifies current understanding of psychophysiological response to video game play.
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Eon, Antoine. "Contribution à la génération de mouvements dynamiques pour les robots humanoïdes et au dimensionnement de leurs actionneurs". Poitiers, 2009. http://theses.edel.univ-poitiers.fr/theses/2009/Eon-Antoine/2009-Eon-Antoine-These.pdf.
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Le travail développé dans cette thèse porte sur l’étude et la génération de mouvements de marche et de saut pour les robots humanoïdes. Les outils conçus dans cette optique sont ensuite utilisés afin d'aider à leur dimensionnement. La première partie présente un outil de génération de mouvements pour le robot HRP2. L'assimilation du robot par un pendule inversé, couplée à un modèle de commande prédictive permet de calculer la trajectoire du centre de gravité. Une marche dynamique est synthétisée en résolvant le Modèle Géométrique Inverse. Les écarts de modélisation sont mis en avant à l'aide d'un modèle dynamique. Une solution est proposée permettant une correction efficace de ces écarts. Une méthode de résolution de l'hyperstatisme (phases de double-appui) basée sur une hypothèse de répartition est également proposée. Les trajectoires obtenues sont validées en termes de non-basculement, de performances (actionneurs) et de respect des lois de Coulomb. Enfin, des améliorations substantielles sont apportées au générateur de mouvements permettant le pilotage de quantités dynamiques. Dans une deuxième partie, les concepts précédemment construits sont utilisés pour générer des mouvements pour un humain virtuel défini à partir de données anthropométriques. En considérant un mouvement extrait par un procédé de capture de mouvement, une étude des performances (actionneurs) est menée pour une population d'humains virtuels de tailles et de masses différentes. L'impact de ces paramètres sur le frottement et la localisation du ZMP est mis en avant. Enfin, une base de mouvements jugés dimensionnants est utilisée pour choisir finement les actionneurs d’un robot de taille et de masse fixéesThe work developed in this thesis focuses on the study and the generation of walking and jumping motions for humanoid robots. The tools developed for this purpose are then used to assist their design. The first part presents a motion generation tool applied to the robot HRP2. The robot is approached by an inverted pendulum. This model is coupled with predictive control to compute the trajectory of the center of gravity. A dynamic walk is then synthesized by solving the Inverse Kinematics Model. Modeling errors are highlighted using multi-body dynamics. An effective correction is given. A method to solve the redundancy during double-support phases, based on a given distribution of forces and torques (ground/sole contact), is also proposed. The trajectories obtained are validated in terms of fall risk, actuators needs and slipping. Finally, substantial improvements are carried out, allowing the planning of dynamic quantities during the motion generation. In a second part, the previously introduced concepts are used to generate motions for a virtual human defined from anthropometric data. A movement extracted by motion capture is considered in order to study actuators needs for a population of virtual humans of different sizes and masses. The impact of these parameters on the slipping risk and on the location of the ZMP is highlighted. Finally, a database of motions judged meaningful is used to properly select the actuators of a robot of a given size and mass
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BARRA, SILVIO. "Design of a Multi-biometric Platform, based on physical traits and physiological measures: Face, Iris, Ear, ECG and EEG". Doctoral thesis, Università degli Studi di Cagliari, 2016. http://hdl.handle.net/11584/266893.
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Security and safety is one the main concerns both for governments and for private
companies in the last years so raising growing interests and investments in
the area of biometric recognition and video surveillance, especially after the sad
happenings of September 2001. Outlays assessments of the U.S. government for
the years 2001-2005 estimate that the homeland security spending climbed from
$56.0 billions of dollars in 2001 to almost $100 billion of 2005. In this lapse of
time, new pattern recognition techniques have been developed and, even more
important, new biometric traits have been investigated and refined; besides
the well-known physical and behavioral characteristics, also physiological measures
have been studied, so providing more features to enhance discrimination
capabilities of individuals. This dissertation proposes the design of a multimodal
biometric platform, FAIRY, based on the following biometric traits: ear,
face, iris EEG and ECG signals. In the thesis the modular architecture of the
platform has been presented, together with the results obtained for the solution
to the recognition problems related to the different biometrics and their possible
fusion. Finally, an analysis of the pattern recognition issues concerning the
area of videosurveillance has been discussed.
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Zeaiter, Hayssam. "Analyse des stades de sommeil et de veille chez les nouveaux-nés prémarturés par évaluation des signaux EEG et ECG". Compiègne, 2001. http://www.theses.fr/2001COMP1337.
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L'objectif principal de cette thèse est la détection automatique des stades de sommeil chez les nouveau-nés prématurés à partir de l'électroencéphalogramme (EEG). Deux objectifs complémentaires sont l'évaluation de la relation température-sommeil ainsi que la relation température-maturité de la partie autonome du système nerveux central (SNC). Le but souhaité est de trouver la relation transitive entre le sommeil et la maturité du SNC. Nous avons appliqué deux méthodes de détection d'événements par traitement du signal. La première méthode, basée sur le principe de la construction d'une base de données à partir des paramètres temporaux et spectraux, est appelée méthode de détection et de classification automatique (MDA). Celle-ci a fourni des résultats encourageants puisque le taux moyen de bonne détection varie de 37 à 47% selon le protocole utilisé. La deuxième méthode est appelée méthode de détection par analyse des moments statistiques (MDM). Celle-ci est très satisfaisante puisque le taux de bonne détection varie de 77% à 85%. Pour évaluer la relation entre température et sommeil, nous avons réalisé une étude statistique (test ) sur 20 sujets (données cliniques), pour évaluer l'influence du changement de température sur la distribution et la durée des stades dans un cycle de sommeil. Les résultats ont montré une relation forte entre la température ambiante et le sommeil surtout dans un milieu froid. Enfin, pour évaluer la relation entre température et maturité de la partie autonome du SNC, nous avons utilisé des techniques nommées PIB (puissance instantanée dans une bande de fréquence sur l'EEG) et PTI (information mutuelle entre EEG et l'électrocardiogramme (ECG)) sous l'influence du changement de température ambiante.
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Hohlefeld, Friederike U. [Verfasser]. "Neural correlates of covert and overt movements investigated by EEG/EMG with implications for brain-computer interfacing / Friederike U. Hohlefeld". Berlin : Freie Universität Berlin, 2011. http://d-nb.info/1025355628/34.
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Julås, Daniel. "EKG-Screening för unga idrottare på elitnivå : En systematisk litteraturstudie". Thesis, Högskolan i Halmstad, Sektionen för hälsa och samhälle (HOS), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-23640.
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ECG-Screening for young elite athletes Abstract Background Sudden cardiac death (SCD) during physical activity is a frightening and emotional tragedy that draws huge media attentions when it occurs. Fortunately it is a relatively uncommon occurrence but happens nonetheless to young athletes who often seems to be in perfect health. SCD is used as a term for sudden unexpected complications on the cardiovascular system that leads to a deadly outcome normally within the first hour of onset of symptoms and the cause is some sort of underlying cardiovascular disease that gets triggered by physical activity.Normally athletes gets divided into two groups dependent on age, over and under 35 years, and this studies focus is on the younger group since it is often during this period athletes are at the elite level. It is also in this category the most unexpected sudden deaths occur that is not due to coronary atherosclerosis, which is the dominant cause of death, and drastically increases, for people over 35 years old. Aim The aim of this study was to scientific and unbiased analyze peer-reviewed clinical articles todescribe the pros, cons and cost to implement an ECG-screening as a standard before physicalactivities for specifically defined elite athletes. Method A systematic review was performed and after all data collection 21 articles was chosen to beused as a base for both background and analyze. At the end 10 articles was fulfilling the criteria to be used at the analyze and later the results. Results The implementation of ECG-screening has reduced SCD in Italy by 89 % between the years 1979-2004. There is a higher risk of SCD for active elite athletes. ECG-screening could be aneffective way to detect hypertrophic cardiomyopathy but a similar study showed oppositeresult. The positive negative results from ECG are relatively low. Hypertrophiccardiomyopathy is a rare disease among elite athletes. A standardized help tool for ECG can help all sorts of physicians in judging the results from ECG. The cost for implementation ofECG-screening for all young athletes is high and will probably not be implemented in countries like USA for a foreseable future. Discussion There is a lot of studies done on the matter but only a couple has shown any positive numbers that gives the implementation of en ECG-screening actually reduce the mortality to SCD. More studies are published every year and the debate will probably go on for a long time, especially concerning money and resources but also about its effectiveness. Better technology in the future will probably make it a more affordable project, especially if it develops to be amore efficient tool.
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Albaba, Adnan. "MODEL-BASED ECG ANALYSIS:TOWARDS PATIENT-SPECIFIC WEARABLE ECG MONITORING : MODEL-BASED ECG ANALYSIS:TOWARDS PATIENT-SPECIFIC WEARABLE ECG MONITORING". Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-409069.
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In this thesis, model-based analysis approach is considered as a possible solution towards a patient-specific point-of-care device for the purpose of electrocardiogram monitoring. Two novel methods are proposed, tested, and quantitatively evaluated. First, a method for estimating the instantaneous heart rate using the morphologicalfeatures of one electrocardiogram beat at a time is proposed. This work is not aimed at introducing an alternative way for heart rate estimation, but rather illustrates the utility of model-basedelectrocardiogram analysis in online individualized monitoring ofthe heart function. The heart rate estimation problem is reduced to fitting one parameter, whose value is related to the nine parameters of a realistic nonlinear model of the electrocardiogram and estimated from data by nonlinear least-squares optimization. The method feasibility is evaluated on synthetic electrocardiogram signals as well as signals acquired from MIT-BIH databases at Physionet website. Moreover, the performance of the method was tested under realistic free-moving conditions using a wearable electrocardiogram and heart monitor with encouraging results. Second, a model-based method for patient-specific detection of deformed electrocardiogram beats is proposed. Five parameters of a patient-specific nonlinear electrocardiogram model are estimated from data by nonlinear least-squares optimization. The normal variability of the model parameters is captured by estimated probability density functions. A binary classifier, based on stochastic anomaly detection methods, along with a pre-tuned classification threshold, is employed for detecting the abnormal electrocardiogram beats. The utility of the proposed approach is tested by validating it on annotated arrhythmia data recorded underclinical conditions.
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Medem, Andreas von. "Kündigungsschutz und allgemeines Gleichbehandlungsgesetz : die Integration der Diskriminierungsverbote der Richtlinien 2000/78/EG, 2000/43/EG und 76/207/EWG in das deutsche Kündigungsschutzrecht /". Berlin : Duncker & Humblot, 2008. http://d-nb.info/989741230/04.
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Misner, Scottie, i Evelyn Whitmer. "Egg and Egg Product Safety and Quality". College of Agriculture and Life Sciences, University of Arizona (Tucson, AZ), 2008. http://hdl.handle.net/10150/146664.
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2 pp.Revision of 1997 title by Meer and Misner
From 1988 to 1992, 66% of all food-borne illnesses caused by salmonella enteritidis involved eggs or foods containing eggs. Contamination of eggs may occur on the inside as well as the outside of the shell. This article outlines the proper refrigeration, cooking and handling methods to prevent most egg safety problems.