866 research outputs found

    Design and Evaluation of a Hardware System for Online Signal Processing within Mobile Brain-Computer Interfaces

    Get PDF
    Brain-Computer Interfaces (BCIs) sind innovative Systeme, die eine direkte Kommunikation zwischen dem Gehirn und externen GerĂ€ten ermöglichen. Diese Schnittstellen haben sich zu einer transformativen Lösung nicht nur fĂŒr Menschen mit neurologischen Verletzungen entwickelt, sondern auch fĂŒr ein breiteres Spektrum von Menschen, das sowohl medizinische als auch nicht-medizinische Anwendungen umfasst. In der Vergangenheit hat die Herausforderung, dass neurologische Verletzungen nach einer anfĂ€nglichen Erholungsphase statisch bleiben, die Forscher dazu veranlasst, innovative Wege zu beschreiten. Seit den 1970er Jahren stehen BCIs an vorderster Front dieser BemĂŒhungen. Mit den Fortschritten in der Forschung haben sich die BCI-Anwendungen erweitert und zeigen ein großes Potenzial fĂŒr eine Vielzahl von Anwendungen, auch fĂŒr weniger stark eingeschrĂ€nkte (zum Beispiel im Kontext von Hörelektronik) sowie völlig gesunde Menschen (zum Beispiel in der Unterhaltungsindustrie). Die Zukunft der BCI-Forschung hĂ€ngt jedoch auch von der VerfĂŒgbarkeit zuverlĂ€ssiger BCI-Hardware ab, die den Einsatz in der realen Welt gewĂ€hrleistet. Das im Rahmen dieser Arbeit konzipierte und implementierte CereBridge-System stellt einen bedeutenden Fortschritt in der Brain-Computer-Interface-Technologie dar, da es die gesamte Hardware zur Erfassung und Verarbeitung von EEG-Signalen in ein mobiles System integriert. Die Architektur der Verarbeitungshardware basiert auf einem FPGA mit einem ARM Cortex-M3 innerhalb eines heterogenen ICs, was FlexibilitĂ€t und Effizienz bei der EEG-Signalverarbeitung gewĂ€hrleistet. Der modulare Aufbau des Systems, bestehend aus drei einzelnen Boards, gewĂ€hrleistet die Anpassbarkeit an unterschiedliche Anforderungen. Das komplette System wird an der Kopfhaut befestigt, kann autonom arbeiten, benötigt keine externe Interaktion und wiegt einschließlich der 16-Kanal-EEG-Sensoren nur ca. 56 g. Der Fokus liegt auf voller MobilitĂ€t. Das vorgeschlagene anpassbare Datenflusskonzept erleichtert die Untersuchung und nahtlose Integration von Algorithmen und erhöht die FlexibilitĂ€t des Systems. Dies wird auch durch die Möglichkeit unterstrichen, verschiedene Algorithmen auf EEG-Daten anzuwenden, um unterschiedliche Anwendungsziele zu erreichen. High-Level Synthesis (HLS) wurde verwendet, um die Algorithmen auf das FPGA zu portieren, was den Algorithmenentwicklungsprozess beschleunigt und eine schnelle Implementierung von Algorithmusvarianten ermöglicht. Evaluierungen haben gezeigt, dass das CereBridge-System in der Lage ist, die gesamte Signalverarbeitungskette zu integrieren, die fĂŒr verschiedene BCI-Anwendungen erforderlich ist. DarĂŒber hinaus kann es mit einer Batterie von mehr als 31 Stunden Dauerbetrieb betrieben werden, was es zu einer praktikablen Lösung fĂŒr mobile Langzeit-EEG-Aufzeichnungen und reale BCI-Studien macht. Im Vergleich zu bestehenden Forschungsplattformen bietet das CereBridge-System eine bisher unerreichte LeistungsfĂ€higkeit und Ausstattung fĂŒr ein mobiles BCI. Es erfĂŒllt nicht nur die relevanten Anforderungen an ein mobiles BCI-System, sondern ebnet auch den Weg fĂŒr eine schnelle Übertragung von Algorithmen aus dem Labor in reale Anwendungen. Im Wesentlichen liefert diese Arbeit einen umfassenden Entwurf fĂŒr die Entwicklung und Implementierung eines hochmodernen mobilen EEG-basierten BCI-Systems und setzt damit einen neuen Standard fĂŒr BCI-Hardware, die in der Praxis eingesetzt werden kann.Brain-Computer Interfaces (BCIs) are innovative systems that enable direct communication between the brain and external devices. These interfaces have emerged as a transformative solution not only for individuals with neurological injuries, but also for a broader range of individuals, encompassing both medical and non-medical applications. Historically, the challenge of neurological injury being static after an initial recovery phase has driven researchers to explore innovative avenues. Since the 1970s, BCIs have been at one forefront of these efforts. As research has progressed, BCI applications have expanded, showing potential in a wide range of applications, including those for less severely disabled (e.g. in the context of hearing aids) and completely healthy individuals (e.g. entertainment industry). However, the future of BCI research also depends on the availability of reliable BCI hardware to ensure real-world application. The CereBridge system designed and implemented in this work represents a significant leap forward in brain-computer interface technology by integrating all EEG signal acquisition and processing hardware into a mobile system. The processing hardware architecture is centered around an FPGA with an ARM Cortex-M3 within a heterogeneous IC, ensuring flexibility and efficiency in EEG signal processing. The modular design of the system, consisting of three individual boards, ensures adaptability to different requirements. With a focus on full mobility, the complete system is mounted on the scalp, can operate autonomously, requires no external interaction, and weighs approximately 56g, including 16 channel EEG sensors. The proposed customizable dataflow concept facilitates the exploration and seamless integration of algorithms, increasing the flexibility of the system. This is further underscored by the ability to apply different algorithms to recorded EEG data to meet different application goals. High-Level Synthesis (HLS) was used to port algorithms to the FPGA, accelerating the algorithm development process and facilitating rapid implementation of algorithm variants. Evaluations have shown that the CereBridge system is capable of integrating the complete signal processing chain required for various BCI applications. Furthermore, it can operate continuously for more than 31 hours with a 1800mAh battery, making it a viable solution for long-term mobile EEG recording and real-world BCI studies. Compared to existing research platforms, the CereBridge system offers unprecedented performance and features for a mobile BCI. It not only meets the relevant requirements for a mobile BCI system, but also paves the way for the rapid transition of algorithms from the laboratory to real-world applications. In essence, this work provides a comprehensive blueprint for the development and implementation of a state-of-the-art mobile EEG-based BCI system, setting a new benchmark in BCI hardware for real-world applicability

    A Survey on Socially Aware Robot Navigation: Taxonomy and Future Challenges

    Get PDF
    Socially aware robot navigation is gaining popularity with the increase in delivery and assistive robots. The research is further fueled by a need for socially aware navigation skills in autonomous vehicles to move safely and appropriately in spaces shared with humans. Although most of these are ground robots, drones are also entering the field. In this paper, we present a literature survey of the works on socially aware robot navigation in the past 10 years. We propose four different faceted taxonomies to navigate the literature and examine the field from four different perspectives. Through the taxonomic review, we discuss the current research directions and the extending scope of applications in various domains. Further, we put forward a list of current research opportunities and present a discussion on possible future challenges that are likely to emerge in the field

    Neuroimaging investigations of cortical specialisation for different types of semantic knowledge

    Get PDF
    Embodied theories proposed that semantic knowledge is grounded in motor and perceptual experiences. This leads to two questions: (1) whether the neural underpinnings of perception are also necessary for semantic cognition; (2) how do biases towards different sensorimotor experiences cause brain regions to specialise for particular types of semantic information. This thesis tackles these questions in a series of neuroimaging and behavioural investigations. Regarding question 1, strong embodiment theory holds that semantic representation is reenactment of corresponding experiences, and brain regions for perception are necessary for comprehending modality-specific concepts. However, the weak embodiment view argues that reenactment may not be necessary, and areas near to perceiving regions may be sufficient to support semantic representation. In the particular case of motion concepts, lateral occipital temporal cortex (LOTC) has been long identified as an important area, but the roles of its different subregions are still uncertain. Chapter 3 examined how different parts of LOTC reacted to written descriptions of motion and static events, using multiple analysis methods. A series of anterior to posterior sub-regions were analyzed through univariate, multivariate pattern analysis (MVPA), and psychophysical interaction (PPI) analyses. MVPA revealed strongest decoding effects for motion vs. static events in the posterior parts of LOTC, including both visual motion area (V5) and posterior middle temporal gyrus (pMTG). In contrast, only the middle portion of LOTC showed increased activation for motion sentences in univariate analyses. PPI analyses showed increased functional connectivity between posterior LOTC and the multiple demand network for motion events. These findings suggest that posterior LOTC, which overlapped with the motion perception V5 region, is selectively involved in comprehending motion events, while the anterior part of LOTC contributes to general semantic processing. Regarding question 2, the hub-and-spoke theory suggests that anterior temporal lobe (ATL) acts as a hub, using inputs from modality-specific regions to construct multimodal concepts. However, some researchers propose temporal parietal cortex (TPC) as an additional hub, specialised in processing and integrating interaction and contextual information (e.g., for actions and locations). These hypotheses are summarized as the "dual-hub theory" and different aspects of this theory were investigated in in Chapters 4 and 5. Chapter 4 focuses on taxonomic and thematic relations. Taxonomic relations (or categorical relations) occur when two concepts belong to the same category (e.g., ‘dog’ and ‘wolf’ are both canines). In contrast, thematic relations (or associative relations) refer to situations that two concepts co-occur in events or scenes (e.g., ‘dog’ and ‘bone’), focusing on the interaction or association between concepts. Some studies have indicated ATL specialization for taxonomic relations and TPC specialization for thematic relations, but others have reported inconsistent or even converse results. Thus Chapter 4 first conducted an activation likelihood estimation (ALE) meta-analysis of neuroimaging studies contrasting taxonomic and thematic relations. This found that thematic relations reliably engage action and location processing regions (left pMTG and SMG), while taxonomic relations only showed consistent effects in the right occipital lobe. A primed semantic judgement task was then used to test the dual-hub theory’s prediction that taxonomic relations are heavily reliant on colour and shape knowledge, while thematic relations rely on action and location knowledge. This behavioural experiment revealed that action or location priming facilitated thematic relation processing, but colour and shape did not lead to priming effects for taxonomic relations. This indicates that thematic relations rely more on action and location knowledge, which may explain why the preferentially engage TPC, whereas taxonomic relations are not specifically linked to shape and colour features. This may explain why they did not preferentially engage left ATL. Chapter 5 concentrates on event and object concepts. Previous studies suggest ATL specialization for coding similarity of objects’ semantics, and angular gyrus (AG) specialization for sentence and event structure representation. In addition, in neuroimaging studies, event semantics are usually investigated using complex temporally extended stimuli, unlike than the single-concept stimuli used to investigate object semantics. Thus chapter 5 used representational similarity analysis (RSA), univariate analysis, and PPI analysis to explore neural activation patterns for event and object concepts presented as static images. Bilateral AGs encoded semantic similarity for event concepts, with the left AG also coding object similarity. Bilateral ATLs encoded semantic similarity for object concepts but also for events. Left ATL exhibited stronger coding for events than objects. PPI analysis revealed stronger connections between left ATL and right pMTG, and between right AG and bilateral inferior temporal gyrus (ITG) and middle occipital gyrus, for event concepts compared to object concepts. Consistent with the meta-analysis in chapter 4, the results in chapter 5 support the idea of partial specialization in AG for event semantics but do not support ATL specialization for object semantics. In fact, both the meta-analysis and chapter 5 findings suggest greater ATL involvement in coding objects' associations compared to their similarity. To conclude, the thesis provides support for the idea that perceptual brain regions are engaged in conceptual processing, in the case of motion concepts. It also provides evidence for a specialised role for TPC regions in processing thematic relations (pMTG) and event concepts (AG). There was mixed evidence for specialisation within the ATLs and this remains an important target for future research

    Microcredentials to support PBL

    Get PDF

    A philosophical discussion of the implications and limitations of using Virtual Reality Technology (VR) as an “Empathy Machine”

    Get PDF
    This thesis engages in a philosophical discussion on “empathy”, “virtuality”, and the use of virtual reality (VR) technology as an “empathy machine”. Here, I define empathy as the intentional activity (or skill) of recreating aspects of another subject’s emotional experience in one’s imagination to reflectively and “experientially” understand what another is feeling. As opposed to isomorphically appropriating another’s feelings to oneself, I identify empathy as third-personally “feeling with” others. After exploring the narrow and pluralistic approaches to understanding empathy, I argue that there are compelling pragmatic reasons for adopting the pluralistic approach, the proponents of which prefer to highlight varieties of empathy instead of a sole conceptualisation of “empathy proper”. As for virtuality, I subscribe to a third view that can be located between “virtual realism” and “virtual irrealism”, in that I understand virtuality as a sui generis mode of technological actualisation, where psychophysiological illusions, of virtual presence and embodiment, coexist with veridical elements, such as virtual social objects, without causing a defect in users’ rational judgment. My main contention in this research is that VR’s multisensory affordances can be instrumentally utilised as a complementary extension (but never as a replacement) for offsetting some of the limitations in attaining interpersonal empathy through imaginative perspective-taking alone. After discussing this contention in more depth, I then attempt to address some of the recurrent challenges and criticism raised against VR’s use as an empathy machine. Finally, I highlight some of the limitations in VR technology’s capability to capture and transmit a full representation of others’ lived experiences

    Tradition and Innovation in Construction Project Management

    Get PDF
    This book is a reprint of the Special Issue 'Tradition and Innovation in Construction Project Management' that was published in the journal Buildings

    Towards a holistic understanding of the role of green infrastructure in improving urban air quality

    Get PDF
    Air pollution has been identified as a major problem in modern societies, threatening urban population health. Pedestrians, in particular, are directly exposed to one of the main sources of air pollutants: road transport, which is concentrated in proximity to the road, worsening the air. Green infrastructure (GI) has been promoted as a natural method for reducing exposure to local street air pollutants and providing additional Ecosystem Services with a range of environmental, social and economic benefits for citizens. The effectiveness of GI for improving air quality depends on the spatio-temporal context and the species-specific characteristics of the GI. Urban planting could maximise this benefit by a holistic understanding of the effects of GI in cities, balancing its benefits and constraints. However, little is currently known about the application of GI design and planning with regard to air pollution mitigation. Moreover, there is little agreement on the quantifiable effectiveness of GI in improving street air quality as its effectiveness is highly context dependent. Holistic guidance is therefore needed to inform practitioners of site- and species- specifics, trade-offs, and GI maintenance considerations for successful urban planting. This research reviews the academic literature addressing GI-related characteristics in streets, creating a holistic framework to help guide decision-makers on using GI solutions to improve air quality. Additionally, this research aims to understand how and which GI, along with other local characteristics, influence pedestrian air quality and how these characteristics are considered in real-world practice within the United Kingdom. This research progresses through three stages: First, the mechanisms by which GI is considered to influence air quality were identified through literature reviews. A specific literature review was then conducted for each mechanism to extract the associated GI and spatial characteristics that affect the potential for GI to mitigate urban air pollution. In the second stage, this list of characteristics, together with other Ecosystem Services, was discussed in consultation with practitioners in the UK. A survey was conducted to explore and evaluate the recommendations and resources available for planning plantings, as well as the practitioners’ knowledge about the characteristics associated with mitigating air pollution. Supported by results from the survey and the literature reviews, the third stage evaluated (validated) an easy-to-use computational model for its potential use in improving planting decisions for air pollution mitigation. Green infrastructure influences air quality by providing surfaces for pollutant deposition and absorption, effects on airflow and dispersion, and biogenic emissions. The relationship between the specific GI and the spatio-temporal context also influences air quality. Street structure, weather variables, and the type, shape and size of GI influence the dispersion of pollutants, with micro-and macro-morphological traits additionally influencing particulate deposition and gas absorption. In addition, maintaining GI lessens air quality deterioration by controlling biogenic emissions. According to participants in the survey, aesthetics were the principal drivers of urban planting, followed by improving well-being and increasing biodiversity and air pollution mitigation as a lesser priority. Characteristics such as airflow manipulation, leaf surface traits, and biogenic emissions were the less important influences in planting decisions in the UK, despite the fact that these characteristics influence air quality. Perhaps, a lack of communication of current information and low confidence about which specific characteristics have a tangible effect on air quality reduces the incorporation of GI for air pollution mitigation purposes. Uncertainties exist about the quantification of pollutants removed by GI. Field campaigns and computational models still need improvement to address the effectiveness of GI in real-world environments adequately and also to understand whether GI can exert a significant effect on pollutant levels under real-world conditions. This research showed that a promising and easy-to-use model used to evaluate the effectiveness of trees in removing particles was not an acceptable model to study the effect of GI on streets. The validation results showed a poor agreement between wind tunnel data and the model results. More effort is needed to develop better modelling tools that can quantify the actual effect of GI on improving street air quality. This research contributes to the air pollution mitigation field, explicitly helping to inform decision-making for more health-promoting urban settings by optimising the expected benefits of GI through a holistic understanding of their impacts. Facilitating the communication of current evidence through a holistic guide that considers both the benefits and trade-offs of planting decisions for air quality improvement. Improving information on air pollution mitigation to feed the decision-making process might maximise the benefits of GI planting for air pollution mitigation in streets.Open Acces

    Database of Video Games and Their Therapeutic Properties

    Get PDF
    There are reported to be 2.96 billion video game players in the world as of 2021 and this number is expected to grow to 3.32 billion by the year 2024. Of that total, 215.5 million video game players live in the United States with a reported average age of 33 years old. Thousands of commercial video games are released every year. There is evidence to support video game technology use as therapeutic media however it predominately utilizes outdated technology or technology designed for a specific purpose also called “serious games.” The problem is that OT practitioners are unaware of the potential therapeutic properties of video games they have not played, so are unable to integrate unfamiliar video games as therapeutic media in clinical practice. The purpose of this capstone project is to develop an online database of commercial video games, and their therapeutic properties, to facilitate their use as therapeutic media in OT practice. To address this problem a webpage was developed in partnership with the Family Gaming Database that cataloged 10 commercial video games from commercially available video game subscription services and the Nintendo Switch. The 10 games were subject to an activity analysis based on the AMPS to determine their therapeutic potential. The resulting webpage contains three main lists in which filters can be applied in order to display games that meet a specific desired criterion. Applicable filters include platform, age rating, difficulty, and specific accessibility features. Keywords: database, occupational therapy, video game, video game

    Connected World:Insights from 100 academics on how to build better connections

    Get PDF
    • 

    corecore