Emotion states greatly influence many areas in our daily lives, such as: learning, decision making and interaction with others. Therefore, the ability to detect and recognize one’s emotional states is essential in intelligence Human Machine Interaction (HMI). In this thesis, a pattern classification framework was developed to sense and communicate emo- tion changes expressed by the Central Nervous System (CNS) through the use of EEG signals. More specifically, an EEG-based subject-dependent affect recognition system was developed to quantitatively measure and categorize three affect states: Positively excited, neutral and negatively excited. Several existing feature extraction algorithms and classifiers were researched, analyzed and evaluated through a series of classification simulations using a publicly available emotion-based EEG database. Simulation results were presented followed by an interpretation discussion. The findings in this thesis can be useful for the design of affect sensitive applications such as augmented means of communication for severely disabled people that cannot directly express their emotions. Furthermore, we have shown that with significantly reduced number of channels, classification rates maintained a level that is feasible for emotion recognition. Thus current HMI paradigms to integrate consumer electronics such as smart hand-held device with commercially available EEG headsets is promising and will significantly broaden the application cases.

Denna rapport har som syfte att samla erfarenhet kring de möjligheter och den potential som finns i den EEG-teknik och de BCI-headset från NeuroSky som använts. Detta görs genom design och utveckling av ett spel som utnyttjar tekniken. Det finns redan idag ett mindre urval av sådana spel, men dessa har samtliga varit av mycket trivial karaktär och med en bristande förmåga att övertyga och engagera. Samtidigt som EEG-teknik når ut till konsumenter, ökar också allmänintresset för mental träning. Studier och rapporter visar indikationer på att sådan träning inte bara förbättrar hjärnans effektivitet, utan också kan förebygga vissa neurologiska sjukdomar som Alzheimers och demens. Forskningsrapporter pekar också på att spel med fördel kan användas för mental träning, vilket är en motivering till relevansen i att detta examensarbete representeras i form av ett spel. Hårdvaran som använts har färdiga algoritmer för avläsning av användarens koncentrations-, meditations- och blinkstyrkenivåer. Det bristande antalet olika former av input som enheterna kan leverera i sitt standardutförande, skapar begränsningar i komplexiteten på interaktionen. Trots detta har det kunnat konstateras som ett resultat av detta arbete att en betydligt rikare interaktionsmodell än den som idag ofta påträffas i tillgängliga spel, är fullt möjlig. Cortex Wars, som det utvecklade spelet heter, tänjer på gränserna genom att vara det första spelet för två samtidiga spelare; var och en med varsitt NeuroSky headset. Resultaten av arbetet visar också på att tekniken och den hårdvara som använts inte är utan problem och brister. Stabilitetsproblem finns med hårdvaran och tekniken som sådan är också väldigt känslig för yttre påverkan av exempelvis muskelaktivitet. EEG-teknik i den form som använts i arbetet har stor potential att förändra tillvaron och tillgängligheten för en stor grupp människor i flera avseenden. Här avhandlas främst spelområdet och hur detta kan tillgängliggöras på sådant vis att personer med vissa fysiska handikapp har möjlighet att spela på lika villkor som människor utan handikapp.

Pharmacological treatments for pain show limited analgesic benefits when compared with placebo. Neuro-modulatory approaches, such as mindfulness meditation and neurofeedback training show more promising effects, but are time consuming and difficult to complete. Neural entrainment provides an almost instantaneous increase in EEG power of the stimulated frequency, achieved with minimal effort through visual flicker stimuli or auditory binaural beats. EEG recorded alpha power displays a reproducible inverse relationship with pain perception. Hence, the main objective of this PhD thesis was to develop an analgesic alpha entrainment intervention: increasing alpha power with the aim to reduce the perception of acute pain in healthy volunteers and chronic pain patients. Prior to attempting to modulate pain, pilot work assessing the ability to entrain alpha power is reported in Chapter 3. A checkerboard stimulus was used to visually entrain frequencies across the alpha band from 7Hz – 14Hz, resulting in a significant power increase at 10Hz and 11Hz. With the goal to reduce behavioural and electrophysiological responses to a moderately painful stimulus, EEG alpha entrainment at 8Hz, 10Hz and 12Hz through auditory binaural beats (in Chapters 4 and 5), and visual flashing LED goggles (in Chapters 4, 6 and 7) was then attempted. A significant reduction of pain ratings was found following both the visual and the auditory alpha stimulation across all three frequencies in Chapters 4,5 and 6. Chapter 5 revealed a significant alpha power increase following 10Hz and 12Hz auditory stimulation. The laser-evoked potential’s (LEP) N2 peak reduced significantly following 10Hz auditory entrainment and the P2 peak reduced significantly across all auditory entrainment conditions. In Chapter 6, alpha power entrained significantly at 8Hz and 10Hz. The P2 peak reduced significantly following the 10Hz visual stimulation. Source analysis showed the precuneus and posterior cingulate cortex might mediate alpha entrainment-induced reductions in LEPs and pain ratings. The paradigm used in Chapter 6 was repeated in osteoarthritic patients in Chapter 7. Significant reductions in pain ratings were observed following all three alpha stimulation sessions, despite a lack of alpha power increase. A significantly reduced response in the P2 peak was also observed following the 12Hz visual stimulation. Decreases in P2 source activity in the posterior insula suggest a functional role in the reduction of pain intensity triggered by alpha stimulation. A significant reduction in the electrophysiological response and the perception of moderately painful stimuli can be achieved through visual or auditory entrainment across the alpha band range, in both healthy volunteers and osteoarthritic patients. The findings from this PhD thesis provide a solid foundation for further investigation of alpha based neuro-modulation as an analgesic intervention.

The effects of smoking cigarettes on sensory gating, P50 and stimulus-bound gamma band (32-48 Hz) oscillations were examined in two paradigms: paired-tone and oddball. During a paired-tone paradigm, our previous work (Crawford, McClain-Furmanski, Castagnoli, & Castagnoli, Neuroscience Letters 317(2002) 151-155) found heavy smokers exhibited chronic (rather than acute) effects in the frontal region: (1) larger P50 and GBO responses; (2) greater P50 and GBO sensory gating suppression, as well as earlier GBO sensory gating suppression. During an oddball paradigm, we (McClain-Furmanski, Crawford, Castagnoli & Castagnoli, in prep.) found an acute effect between 0 and 20 ms post-stimulus in the GBO, however we were unable to determine whether this effect was due to nicotine or the act of smoking. In the present study, participants were 24 heavy cigarette (20+/day) right-handed, non-depressed smokers with no known medical or psychiatric problems, and no known familial history of psychiatric problems. In the morning, they were tested after abstaining overnight and after smoking a cigarette containing either 1.1 mg of nicotine, or a denicotinized cigarette (< 0.04 mg). In study 1 (oddball paradigm), although some effects were found related to nicotine and/or smoking, observed as condition by group interactions with the groups changing differently across conditions, they differed in temporal and spatial localization from those hypothesized. Thus, the present study was unable to differentiate between nicotine effects and effects due to the act of smoking. In study 2 (paired-pulse paradigm), in traditional evoked potential analysis, we observed signficant chronic sensory gating, as measured by the ratio of N40-P50 amplitude in response to the second tone (S2) as compared to the response to the first tone (S1). The effect was greatest at the hypothesized location (FCZ). In time series analysis of the underlying GBO, we replicated our earlier findings in that S2/S1 effects could be detected across 60 msec of the response. These results are discussed in relation to the neurochemistry and neural processes underlying sensory gating at GBO production, as well as in relation to the known and hypothesized psychpharmacological effects of smoking tobacco. Furthermore, these results are related to the theorized basis of addiction. / Ph. D.

With increased age, some individuals experience cognitive declines that are more severe than what is observed in healthy cognitive aging. This decline may be related to mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Much of the current research on dementia attempts to detect subtle cognitive and memory declines before behavioral and cognitive symptoms are more apparent. Intense research interest has focused on MCI, a condition that includes impairment in some areas of cognitive functioning but is not severe enough to warrant the diagnosis of dementia. MCI may represent a transitional stage between healthy aging and AD and is considered a risk factor for AD development. The purpose of the present thesis was to examine if EEG and ERPs can be used as reliable predictors of cognitive changes in aging and MCI. Study 1 was designed to examine if there is evidence of changes in the EEG between cognitively healthy older adults and people with MCI. The purpose of this study was to examine differences in EEG activity between healthy older adults and people with MCI during early and late portions of a longer-than-normal resting-state recording. Resting state recordings typically last 1-3 minutes. It would be advantageous to run a longer testing session because this would provide more data, but such a procedure might be problematic because it might result in increased drowsiness in the latter half of testing. If this drowsiness affected those with MCI more than healthy adults, this might produce artifactual differences between groups. If increased drowsiness occurs as the duration of the recording becomes longer, an increase of low-frequency EEG activity should be observed, particularly in the delta band. Resting state EEG was recorded in 20 healthy older adults and 20 people with MCI who rested with their eyes closed. The EEG recording was divided into two three-minute halves. People with MCI exhibited a significant increase in theta power density over posterior regions of the scalp compared to healthy older adults. Power density for all frequency bands did not change over the two halves of the recording. That is, there was little evidence of drowsiness in the second half of the recording. Taken together, these findings indicate that longer resting-state EEG recording can be reliably employed without increased risk of drowsiness. Study 2 examined whether there is evidence of a dysfunction in the salience network in older adults. Previous research suggests that older adults may be less able to compute the level of salience of unattended stimulus inputs. The transient detector system is a specialized network of brain areas for detecting sudden changes in the intensity of an auditory stimulus. The output of this system, as reflected by the auditory ERP components N1 and P2, provides a measure of the level of salience of the stimulus. Twenty younger adults and healthy older adults participated in this study. A single auditory stimulus was presented rapidly, every 1.5 s, or very slowly, every 12 s, in different conditions. When the stimuli were presented rapidly, group differences were not observed for the amplitudes of N1 and P2, peaking at 100 and 180 ms, respectively. When stimuli were presented very slowly, their amplitudes were greatly enhanced for younger adults but did not increase for older adults. The failure to observe a large increase in the amplitude of N1 and P2 in older adults for very slowly presented stimuli provides strong evidence of a dysfunction of the salience network in this group. There is evidence that both the functioning of salience network and the frontoparietal network deteriorate in cognitively healthy older adults. These networks might further deteriorate in people with MCI. In study 2, when stimuli were presented slowly, the P2 was delayed and peaked at a time that is more consistent with a P3a. The P3a is elicited by a potentially highly salient, but unattended stimulus input that interrupts the functioning of the frontoparietal network, resulting in a switch of processing priorities away from current task demands and toward the processing of the stimulus input. In study 3, auditory stimuli were again presented either rapidly or very slowly to 20 healthy older adults and 20 people with MCI. The amplitude of N1 did not differ between the two groups in either the fast or slow conditions. Thus, there is little evidence that people with MCI have a deficit in computing the salience of unattended auditory stimuli. When stimuli were presented slowly, the P2/P3a was significantly smaller in people with MCI compared to healthy older adults. The attenuated P2/P3a in people with MCI may reflect a reduced frontoparietal ability to determine processing priorities. In people with MCI, priority of processing may not be switched from the ongoing cognitive task to the potentially much more relevant auditory input. In the results of studies 2 and 3, there was ambiguity regarding whether the positivity observed in the slow condition reflected P2 or P3a activity. A more definite P3a had been elicited in oddball paradigms. In the oddball paradigm, the participant is presented with a sequence of frequently presented homogenous standard stimuli. At rare and unpredictable times, a deviant is presented, the deviant representing a change in a feature of the standard. Deviants that represent a large change from the standard may elicit a P3a. Two experiments were run in which at least one of the deviants had previously been shown to elicit a large P3a in younger adults. Study 4 consisted of two experiments. In Experiment 1, the deviants represented either decreases or increases in the intensity of the standard. The deviant that represented an increase in intensity has been found to elicit a large P3a in previous studies. In Experiment 2, six different deviants were presented. The deviants included a white noise burst and environmental sounds, both of which have elicited a large P3a in previous studies. Across both experiments, the MMN/DRN and P3a did not differ between healthy older adults and people with MCI. Previous studies have indicated that the P3a is reduced in amplitude in healthy older adults compared to younger adults. The results of study 4 indicate that the P3a was not further reduced in people with MCI. This is in contrast to study 3 in which the P2/P3a was reduced in people with MCI. This could be because of the use of the oddball paradigm in study 4. Detection of the deviant would be carried out, at least in part, by the change detection system while in study 3, the presentation of a single stimulus would have been detected only by the transient detection system. Operations of the frontoparietal network controlling processing priorities can be interrupted by sufficient output from either the transient or change detector systems. This results in a switch of processing from an ongoing task to the processing of the potentially more relevant stimulus input. When this interrupt is sent from the change detection system, the operations of the frontoparietal network do not appear to deteriorate in people with MCI compared to what is observed in cognitively healthy older adults.

The need for individual neural markers has been expressed in both basic and clinical neuroscience. To address this, we here designed a novel behavioural paradigm in which to test several measures as possible neural markers of individuality which distinguish participants from each other in how they perceive, feel and perform cognitive tasks. The individualized paradigm for consequentialist moral dilemmas was validated, showing variability across participants in thresholds and reaction times. Next, task-induced activity changes in EEG activity during the time interval of the Late Positive Potential (LPP) in alpha power, along with phase coherence early in the trial, correlated with reaction times and scores of subjective emotional distress. From these findings in study one, in study two we measured trial-to-trial variability (TTV) and found that the TTV index in the alpha and beta bands correlated with reaction time and prestimulus Lempel-Ziv Complexity. These findings, again in the alpha and beta bands, support alpha power during the LPP, variability quenching in these bands, and early intertrial coherence as markers of neural individuality. Finally, measures of scale-free activity in the resting state, along with others, and self-consciousness scale subscores as indices of the self were investigated. It was found that the power-law exponent, autocorrelation window, modulation index and electromagnetic tomography activity in two Default Mode Network areas correlated significantly with the Private subscore of the Self-Consciousness Scale only. These findings indicate that these resting state measures, along with activity in the DMN, may serve as markers of neural individuality in the brain’s spontaneous activity.

Emotions have significant importance in human life in learning, decision-making, daily interaction, and perception of the surrounding environment. Hence, it has become very essential to detect and recognize a person's emotional states and to build a connection between humans and computers. This process is called brain-computer interaction (BCI) and is a vast field of research in neuroscience. Hence, in the past few years, emotion recognition has gained adequate attention in the research community. In this thesis, an emotion recognition system is designed and analyzed using EEG signals. Several existing feature extraction techniques are studied, analyzed, and implemented to extract features from the EEG signals. An SVM classifier is used to classify the features into various emotional states. Four emotional states are detected, namely, happy, sad, anger, and relaxed state. The model is tested, and simulation results are presented with an interpretation. Furthermore, this study has mentioned and discussed the efficacy of the results achieved. The findings from this study could be beneficial in developing emotion-sensitive technologies, such as augmented modes of communication for severely disabled individuals who are unable to communicate their feelings directly.

No description available.

Mit der EEG-Umlage wurden bis zum Jahr 2023 die Förderkosten für den Ökostromausbau auf die Stromverbraucher umgelegt. Ursprünglich knüpfte die Umlagepflicht an eine Stromlieferung an, weshalb der eigenerzeugte Strom nicht erfasst war. Das sog. Eigenstromprivileg wurde mit dem EEG 2014 grundsätzlich abgeschafft. Allerdings führten diverse Ausnahmetatbestände dazu, dass ein Großteil der Eigenverbrauchsmengen weiterhin privilegiert waren. Die Arbeit untersucht, in welchem Maße dieser Flickenteppich an unterschiedlichen Regelungen auf die verfassungs- und europarechtlichen Rahmenbedingungen zurückzuführen ist. Neben einer systematischen Erfassung des einfachgesetzlichen Rechtsrahmens erfolgt eine Analyse, inwiefern das Verfassungs- und Europarecht den gesetzlichen Gestaltungsspielraum für staatlich veranlasste, jedoch privatrechtlich ausgestaltete Umlagesysteme einschränkt. / With the EEG levy, the funding costs for the expansion of green electricity were passed on to electricity consumers until 2023. Originally, the levy obligation was linked to an electricity supply, which is why self-generated electricity was not included. The so-called own electricity privilege was fundamentally abolished with the EEG 2014. However, various exceptions meant that a large proportion of the volumes of self-consumption continued to be privileged. The work examines the extent to which this patchwork of different regulations can be attributed to the constitutional and European legal framework. In addition to a systematic recording of the simple legal framework, an analysis is carried out of the extent to which constitutional and European law restricts the legal scope for state-mandated but private-law apportionment systems.

Dans de nombreux pays, le taux de mortalité des motocyclistes est beaucoup plus élevé que celui des autres conducteurs de véhicules. Parmi de nombreux autres facteurs, les collisions arrière des motocyclettes contribuent fortement à ces décès de motards. Les systèmes de détection de collision peuvent être utilisés pour minimiser ces accidents mortels. Cependant, la plupart des systèmes de détection de collision existants n'identifient pas le type de danger potentiel auquel sont exposés les motocyclistes. Chaque système d'alerte de collision utilise une technique de détection de collision distincte, ce qui limite ses performances et rend impératif l'étude de son efficacité. Malheureusement, aucun travail de ce type n'a été signalé dans ce domaine particulier pour les motocyclistes. Par conséquent, il est important d'étudier la réponse physiologique du motocycliste contre ces systèmes d'alerte de collision. Dans cette recherche, une méthode de détection et de classification des véhicules approchant par l'arrière est présentée. Pour la détection de collision, une approche basee vision et la technique basee sur le son ont été utilisées. Pour les techniques visuelles et acoustiques, des caractéristiques d'apparence et de spectre de puissance ont été utilisées, respectivement, pour détecter le véhicule qui s'approche à l'extrémité arrière de la motocyclette. En ce qui concerne la classification des véhicules, seule une technique acoustique est utilisée; un spectre de puissance acoustique et des caractéristiques énergétiques sont utilisés pour classer les véhicules qui approchent. Deux types d'ensembles de données, à savoir des ensembles de données acquises durant ce travail (obtenues en plaçant une caméra à l'arrière d'une motocyclette) et des ensembles de données disponibles telechargeables (pour la détection visuelle et pour la classification audio des véhicules) sont utilisés pour la validation. La méthodologie proposée a permis de détecter et de classer les véhicules pour des ensembles de données acquises durent cette these. De même, pour les ensembles de données disponibles , le taux positif vrai le plus élevé et le taux de détection faux le plus faible ont été atteints par rapport aux méthodes de l etat de l art. En outre, une étude physiologique basée sur le potentiel lié à l'événement (ERP) a été réalisée sur les motocyclistes afin d'étudier leurs réponses vis-à-vis du système d'alerte de collision arrière. Deux types d'avertissements auditifs (c'est-à-dire verbal et buzzer) sont utilisés pour ce système d'avertissement. Pour étudier la réponse des motocyclistes, les composantes N1, N2, P3 et N400 ont été extraits des données d'électroencéphalographie (EEG). Ces systèmes d avertissement ont montré des effets positifs au niveau des neuronal sur les motocyclistes et réduisent leur temps de réaction et les ressources attentionnelles nécessaires pour traiter correctement la cible. En résumé, le système d'avertissement de collision par l'arrière proposé avec des avertissements verbaux auditifs augmente considérablement la vigilance du motocycliste et peut être utile pour éviter les scénarios possibles de collision arrière. / In many countries, motorcyclist fatality rate is much higher than that of other vehicle drivers. Among many other factors, motorcycle rear-end collisions are also contributing to these biker fatalities. Collision detection systems can be used to minimize these fatalities. However, most of the existing collision detection systems do not identify the type of potential hazard faced by motorcyclists. Every collision warning system used a distinctive collision detection technique, which limits its performance and makes it imperative to study its effectiveness. Unfortunately, no such work has been reported in that particular domain for motorcyclists. Therefore, it is important to study the physiological response of the motorcyclist against these collision warning systems. In this research, a rear end vehicle detection and classification method is presented for motorcyclists. For collision detection, vision technique and acoustic technique have been used. For visual and acoustic techniques, appearance features and power spectrum have been used, respectively, to detect the approaching vehicle at the rear end of the motorcycle. As for the vehicle classification, only an acoustic technique is utilized; an acoustic power spectrum and energy features are used to classify the approaching vehicles. Two types of datasets which are comprised of self-recorded datasets (obtained by placing a camera at the rear end of a motorcycle) and online datasets (for vision-based vehicle detection and for audio based vehicle classification techniques) are used for validation. Proposed methodology successfully detected and classified the vehicle for self-recorded datasets. Similarly, for online datasets, the higher true positive rate and less false detection rate has been achieved as compared to the existing state of the art methods. Moreover, an event-related potential (ERP) based physiological study has been performed on motorcyclists to investigate their responses towards the rear end collision warning system. Two types of auditory warnings (i.e., verbal and buzzer) are used for this warning system. To study the response of the motorcyclists, the N1, N2, P3, and N400 components have been extracted from the Electroencephalography (EEG) data. These introduced systems have shown positive effects at neural levels on motorcyclists and reduce their reaction time and attentional resources required for processing the target correctly. In summary, the proposed rear-end collision warning system with auditory verbal warnings significantly increases the alertness of the motorcyclist and can be helpful to avoid the possible rear-end collision scenarios.