1,078 research outputs found

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

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    Brain-Computer Interfaces (BCIs) sind innovative Systeme, die eine direkte Kommunikation zwischen dem Gehirn und externen Geräten ermöglichen. Diese Schnittstellen haben sich zu einer transformativen Lösung nicht nur für Menschen mit neurologischen Verletzungen entwickelt, sondern auch für 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 anfänglichen Erholungsphase statisch bleiben, die Forscher dazu veranlasst, innovative Wege zu beschreiten. Seit den 1970er Jahren stehen BCIs an vorderster Front dieser Bemühungen. Mit den Fortschritten in der Forschung haben sich die BCI-Anwendungen erweitert und zeigen ein großes Potenzial für eine Vielzahl von Anwendungen, auch für weniger stark eingeschränkte (zum Beispiel im Kontext von Hörelektronik) sowie völlig gesunde Menschen (zum Beispiel in der Unterhaltungsindustrie). Die Zukunft der BCI-Forschung hängt jedoch auch von der Verfügbarkeit zuverlässiger BCI-Hardware ab, die den Einsatz in der realen Welt gewährleistet. 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 Flexibilität und Effizienz bei der EEG-Signalverarbeitung gewährleistet. Der modulare Aufbau des Systems, bestehend aus drei einzelnen Boards, gewährleistet 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 Mobilität. Das vorgeschlagene anpassbare Datenflusskonzept erleichtert die Untersuchung und nahtlose Integration von Algorithmen und erhöht die Flexibilität 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 für verschiedene BCI-Anwendungen erforderlich ist. Darüber hinaus kann es mit einer Batterie von mehr als 31 Stunden Dauerbetrieb betrieben werden, was es zu einer praktikablen Lösung für mobile Langzeit-EEG-Aufzeichnungen und reale BCI-Studien macht. Im Vergleich zu bestehenden Forschungsplattformen bietet das CereBridge-System eine bisher unerreichte Leistungsfähigkeit und Ausstattung für ein mobiles BCI. Es erfüllt nicht nur die relevanten Anforderungen an ein mobiles BCI-System, sondern ebnet auch den Weg für eine schnelle Übertragung von Algorithmen aus dem Labor in reale Anwendungen. Im Wesentlichen liefert diese Arbeit einen umfassenden Entwurf für die Entwicklung und Implementierung eines hochmodernen mobilen EEG-basierten BCI-Systems und setzt damit einen neuen Standard für 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

    Mobility classification of cattle with micro-Doppler radar

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    Lameness in dairy cattle is a welfare concern that negatively impacts animal productivity and farmer profitability. Micro-Doppler radar sensing has been previously suggested as a potential system for automating lameness detection in ruminants. This thesis investigates the refinement of the proposed automated system by analysing and enhancing the repeatability and accuracy of the existing scoring method in cattle mobility scoring, used to provide labels in machine learning. The main aims of the thesis were (1) to quantify the performance of the micro-Doppler radar sensing method for the assessment of mobility, (2) to characterise and validate micro-Doppler radar signatures of dairy cattle with varying degrees of gait impairment, and (3) to develop machine learning algorithms that can infer the mobility status of the animals under test from their radar signatures and support automatic contactless classification. The first study investigated inter-assessor agreement using a 4-level system and modifications to it, as well as the impact of factors such as mobility scoring experience, confidence in scoring decisions, and video characteristics. The results revealed low levels of agreement between assessors' scores, with kappa values ranging from 0.16 to 0.53. However, after transforming and reducing the mobility scoring system levels, an improvement was observed, with kappa values ranging from 0.2 to 0.67. Subsequently, a longitudinal study was conducted using good-agreement scores as ground truth labels in supervised machine-learning models. However, the accuracy of the algorithmic models was found to be insufficient, ranging from 0.57 to 0.63. To address this issue, different labelling systems and data pre-processing techniques were explored in a cross-sectional study. Nonetheless, the inter-assessor agreement remained challenging, with an average kappa value of 0.37 (SD = 0.16), and high-accuracy algorithmic predictions remained elusive, with an average accuracy of 56.1 (SD =16.58). Finally, the algorithms' performance was tested with high-confidence labels, which consisted of only scores 0 and 3 of the AHDB system. This testing resulted in good classification accuracy (0.82), specificity (0.79), and sensitivity (0.85). This led to the proposal of a new approach to producing labels, testing vantage point changes, and improving the performance of machine learning models (average accuracy = 0.7 & SD = 0.17, average sensitivity = 0.68 & SD = 0.27, average specificity = 0.75 & SD = 0.17). The research identified a challenge in creating high-confidence diagnostic labels for supervised machine learning-based algorithms to automate the detection and classification of lameness in dairy cows. As a result, the original goals were partially overridden, with the focus shifted to creating reliable labels that would perform well with radar data and machine learning. This point was considered necessary for smooth system development and process automation. Nevertheless, we managed to quantify the performance of the micro-Doppler radar system, partially develop the supervised machine learning algorithms, compare levels of agreement among multiple assessors, evaluate the assessment tools, assess the mobility evaluation process and gather a valuable data set which can be used as a foundation for subsequent studies. Finally, the thesis suggests changes in the assessment process to improve the prediction accuracy of algorithms based on supervised machine learning with radar data

    Communication‐less Synchronous Rectification for In Motion Wireless Charging

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    This thesis puts forward a control scheme to allow for synchronous rectification for dynamic wireless power transfer. The automotive industry is transitioning away from internal combustion engines (ICEs) and towards electric vehicles (EVs). This transition is spurred by the environmental and economic benefits EVs offer over ICEs. However, further improvements can still be made to how electric vehicles operate. One of these improvements is the technology of in motion wireless charging or dynamic wireless power transfer. In motion wireless charging offers the ability to remove existing range anxiety concerns for EVs. It also offers the potential for a reduction in battery sizes for EVs, which are the primary cost of EVs, this in turn decreases the total costs of mass EV adoption. Traditional implementations of in motion wireless charging utilize passive rectification to simplify controls between embedded primary pads and the vehicle. However, this solution while effective, limits the potential benefits of wireless charging. The use of synchronous or active rectification techniques, offer improved performance, control techniques, and bidirectional capabilities. However, the reason synchronous rectification is not already used in in motion charging is the complexity of synchronization over wireless communication. To move past this challenge, this thesis investigates a synchronization scheme that can be achieved without communication by taking advantage of induced free resonant currents in the vehicle’s tuning network to synchronize the switching transitions to receive power. In this thesis a traditional in motion wireless charging system utilizing passive rectification is designed and built as a benchmark for dynamic charging. Simulations of this control scheme are presented. Practical considerations are addressed for hardware realization. Finally, the control approach is validated through hardware in static and dynamic applications

    Regulating competition in the digital network industry: A proposal for progressive ecosystem regulation

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    The digital sector is a cornerstone of the modern economy, and regulating digital enterprises can be considered the new frontier for regulators and competition authorities. To capture and address the competitive dynamics of digital markets we need to rethink our (competition) laws and regulatory strategies. The thesis develops new approaches to regulating digital markets by viewing them as part of a network industry. By combining insights from our experiences with existing regulation in telecommunications with insights from economics literature and management theory, the thesis concludes by proposing a new regulatory framework called ‘progressive ecosystem regulation’. The thesis is divided in three parts and has three key findings or contributions. The first part explains why digital platforms such as Google’s search engine, Meta’s social media platforms and Amazon’s Marketplace are prone to monopolization. Here, the thesis develops a theory of ‘digital natural monopoly’, which explains why competition in digital platform markets is likely to lead to concentration by its very nature.The second part of the thesis puts forward that competition in digital markets persists, even if there is monopoly in a market. Here, the thesis develops a conceptual framework for competition between digital ecosystems, which consists of group of actors and products. Digital enterprises compete to carve out a part of the digital network industry where they can exert control, and their strong position in a platform market can be used offensively or defensively to steer competition between ecosystems. The thesis then sets out four phases of ecosystem competition, which helps to explain when competition in the digital network industry is healthy and when it is likely to become problematic.The third and final part of the thesis brings together these findings and draws lessons from our experiences of regulating the network industry for telecommunications. Based on the insights developed in the thesis it puts forward a proposal for ‘progressive ecosystem regulation’. The purpose of this regulation is to protect and empower entrants from large digital ecosystems so that they can develop new products and innovate disruptively. This regulatory framework would create three regulatory pools: a heavily regulated, lightly regulated and entrant pool. The layered regulatory framework allows regulators to adjust who receives protection under the regulation and who faces the burdens relatively quickly, so that the regulatory framework reflects the fast pace of innovation and changing nature of digital markets. With this proposal, the thesis challenges and enriches our existing notions on regulation and specifically how we should regulate digital markets

    Design and implementation of a wideband sigma delta ADC

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    Abstract. High-speed and wideband ADCs have become increasingly important in response to the growing demand for high-speed wireless communication services. Continuous time sigma delta modulators (CTƩ∆M), well-known for their oversampling and noise shaping properties, offer a promising solution for low-power and high-speed design in wireless applications. The objective of this thesis is to design and implement a wideband CTƩ∆M for a global navigation satellite system(GNSS) receiver. The targeted modulator architecture is a 3rdorder single-bit CTƩ∆M, specifically designed to operate within a 15 MHz signal bandwidth. With an oversampling ratio of 25, the ADC’s sampling frequency is set at 768 MHz. The design goal is to achieve a theoretical signal to noise ratio (SNR) of 55 dB. This thesis focuses on the design and implementation of the CTƩ∆M, building upon the principles of a discrete time Ʃ∆ modulator, and leveraging system-level simulation and formulations. A detailed explanation of the coefficient calculation procedure specific to CTƩ∆ modulators is provided, along with a "top-down" design approach that ensures the specified requirements are met. MATLAB scripts for coefficient calculation are also included. To overcome the challenges associated with the implementation of CTƩ∆ modulators, particularly excess loop delay and clock jitter sensitivity, this thesis explores two key strategies: the introduction of a delay compensation path and the utilization of a finite impulse response (FIR) feedback DAC. By incorporating a delay compensation path, the stability of the modulator can be ensured and its noise transfer function (NTF) can be restored. Additionally, the integration of an FIR feedback DAC addresses the issue of clock jitter sensitivity, enhancing the overall performance and robustness of the CTƩ∆M. The CTƩ∆Ms employ the cascade of integrators with feed forward (CIFF) and cascade of integrators with feedforward and feedback (CIFF-B) topologies, with a particular emphasis on the CIFF-B configuration using 22nm CMOS technology node and a supply voltage of 0.8 V. Various simulations are performed to validate the modulator’s performance. The simulation results demonstrate an achievable SNR of 55 dB with a power consumption of 1.36 mW. Furthermore, the adoption of NTF zero optimization techniques enhances the SNR to 62 dB.Laajakaistaisen jatkuva-aikaisen sigma delta-AD-muuntimen suunnittelu ja toteutus. Tiivistelmä. Nopeat ja laajakaistaiset AD-muuntimet ovat tulleet entistä tärkeämmiksi nopeiden langattomien kommunikaatiopalvelujen kysynnän kasvaessa. Jatkuva-aikaiset sigma delta -modulaattorit (CTƩ∆M), joissa käytetään ylinäytteistystä ja kohinanmuokkausta, tarjoavat lupaavan ratkaisun matalan tehonkulutuksen ja nopeiden langattomien sovellusten suunnitteluun. Tämän työn tarkoituksena on suunnitella ja toteuttaa laajakaistainen jatkuva -aikainen sigma delta -modulaattori satelliittipaikannusjärjestelmien (GNSS) vastaanottimeen. Arkkitehtuuriltaan modulaattori on kolmannen asteen 1-bittinen CTƩ∆M, jolla on 15MHz:n signaalikaistanleveys. Ylinäytteistyssuhde on 25 ja AD muuntimen näytteistystaajuus 768 MHz. Tavoitteena on saavuttaa teoreettinen 55 dB signaalikohinasuhde (SNR). Tämä työ keskittyy jatkuva-aikaisen sigma delta -modulaattorin suunnitteluun ja toteutukseen, perustuen diskreettiaikaisen Ʃ∆-modulaattorin periaatteisiin ja systeemitason simulointiin ja mallitukseen. Jatkuva-aikaisen sigma delta -modulaattorin kertoimien laskentamenetelmä esitetään yksityiskohtaisesti, ja vaatimusten täyttyminen varmistetaan “top-down” -suunnitteluperiaatteella. Liitteenä on kertoimien laskemiseen käytetty MATLAB-koodi. Jatkuva-aikaisten sigma delta -modulaattoreiden erityishaasteiden, liian pitkän silmukkaviiveen ja kellojitterin herkkyyden, voittamiseksi tutkitaan kahta strategiaa, viiveen kompensointipolkua ja FIR takaisinkytkentä -DA muunninta. Viivekompensointipolkua käyttämällä modulaattorin stabiilisuus ja kohinansuodatusfunktio saadaan varmistettua ja korjattua. Lisäksi FIR takaisinkytkentä -DA-muuntimen käyttö pienentää kellojitteriherkkyyttä, parantaen jatkuva aikaisen sigma delta -modulaattorin kokonaissuorituskykyä ja luotettavuutta. Toteutetuissa jatkuva-aikaisissa sigma delta -modulaattoreissa on kytketty peräkkäin integraattoreita myötäkytkentärakenteella (CIFF) ja toisessa sekä myötä- että takaisinkytkentärakenteella (CIFF-B). Päähuomio on CIFF-B rakenteessa, joka toteutetaan 22nm CMOS prosessissa käyttäen 0.8 voltin käyttöjännitettä. Suorityskyky varmistetaan erilaisilla simuloinneilla, joiden perusteella 55 dB SNR saavutetaan 1.36 mW tehonkulutuksella. Lisäksi kohinanmuokkausfunktion optimoinnilla SNR saadaan nostettua 62 desibeliin

    Development of electronics for microultrasound capsule endoscopy

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    Development of intracorporeal devices has surged in the last decade due to advancements in the semiconductor industry, energy storage and low-power sensing systems. This work aims to present a thorough systematic overview and exploration of the microultrasound (µUS) capsule endoscopy (CE) field as the development of electronic components will be key to a successful applicable µUSCE device. The research focused on investigating and designing high-voltage (HV, < 36 V) generating and driving circuits as well as a low-noise amplifier (LNA) for battery-powered and volume-limited systems. In implantable applications, HV generation with maximum efficiency is required to improve the operational lifetime whilst reducing the cost of the device. A fully integrated hybrid (H) charge pump (CP) comprising a serial-parallel (SP) stage was designed and manufactured for > 20 V and 0 - 100 µA output capabilities. The results were compared to a Dickson (DKCP) occupying the same chip area; further improvements in the SPCP topology were explored and a new switching scheme for SPCPs was introduced. A second regulated CP version was excogitated and manufactured to use with an integrated µUS pulse generator. The CP was manufactured and tested at different output currents and capacitive loads; its operation with an US pulser was evaluated and a novel self-oscillating CP mechanism to eliminate the need of an auxiliary clock generator with a minimum area overhead was devised. A single-output universal US pulser was designed, manufactured and tested with 1.5 MHz, 3 MHz, and 28 MHz arrays to achieve a means of fully-integrated, low-power transducer driving. The circuit was evaluated for power consumption and pulse generation capabilities with different loads. Pulse-echo measurements were carried out and compared with those from a commercial US research system to characterise and understand the quality of the generated pulse. A second pulser version for a 28 MHz array was derived to allow control of individual elements. The work involved its optimisation methodology and design of a novel HV feedback-based level-shifter. A low-noise amplifier (LNA) was designed for a wide bandwidth µUS array with a centre frequency of 28 MHz. The LNA was based on an energy-efficient inverter architecture. The circuit encompassed a full power-down functionality and was investigated for a self-biased operation to achieve lower chip area. The explored concepts enable realisation of low power and high performance LNAs for µUS frequencies

    Regulating competition in the digital network industry: A proposal for progressive ecosystem regulation

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    The digital sector is a cornerstone of the modern economy, and regulating digital enterprises can be considered the new frontier for regulators and competition authorities. To capture and address the competitive dynamics of digital markets we need to rethink our (competition) laws and regulatory strategies. The thesis develops new approaches to regulating digital markets by viewing them as part of a network industry. By combining insights from our experiences with existing regulation in telecommunications with insights from economics literature and management theory, the thesis concludes by proposing a new regulatory framework called ‘progressive ecosystem regulation’. The thesis is divided in three parts and has three key findings or contributions. The first part explains why digital platforms such as Google’s search engine, Meta’s social media platforms and Amazon’s Marketplace are prone to monopolization. Here, the thesis develops a theory of ‘digital natural monopoly’, which explains why competition in digital platform markets is likely to lead to concentration by its very nature.The second part of the thesis puts forward that competition in digital markets persists, even if there is monopoly in a market. Here, the thesis develops a conceptual framework for competition between digital ecosystems, which consists of group of actors and products. Digital enterprises compete to carve out a part of the digital network industry where they can exert control, and their strong position in a platform market can be used offensively or defensively to steer competition between ecosystems. The thesis then sets out four phases of ecosystem competition, which helps to explain when competition in the digital network industry is healthy and when it is likely to become problematic.The third and final part of the thesis brings together these findings and draws lessons from our experiences of regulating the network industry for telecommunications. Based on the insights developed in the thesis it puts forward a proposal for ‘progressive ecosystem regulation’. The purpose of this regulation is to protect and empower entrants from large digital ecosystems so that they can develop new products and innovate disruptively. This regulatory framework would create three regulatory pools: a heavily regulated, lightly regulated and entrant pool. The layered regulatory framework allows regulators to adjust who receives protection under the regulation and who faces the burdens relatively quickly, so that the regulatory framework reflects the fast pace of innovation and changing nature of digital markets. With this proposal, the thesis challenges and enriches our existing notions on regulation and specifically how we should regulate digital markets

    Path and Motion Planning for Autonomous Mobile 3D Printing

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    Autonomous robotic construction was envisioned as early as the ‘90s, and yet, con- struction sites today look much alike ones half a century ago. Meanwhile, highly automated and efficient fabrication methods like Additive Manufacturing, or 3D Printing, have seen great success in conventional production. However, existing efforts to transfer printing technology to construction applications mainly rely on manufacturing-like machines and fail to utilise the capabilities of modern robotics. This thesis considers using Mobile Manipulator robots to perform large-scale Additive Manufacturing tasks. Comprised of an articulated arm and a mobile base, Mobile Manipulators, are unique in their simultaneous mobility and agility, which enables printing-in-motion, or Mobile 3D Printing. This is a 3D printing modality, where a robot deposits material along larger-than-self trajectories while in motion. Despite profound potential advantages over existing static manufacturing-like large- scale printers, Mobile 3D printing is underexplored. Therefore, this thesis tack- les Mobile 3D printing-specific challenges and proposes path and motion planning methodologies that allow this printing modality to be realised. The work details the development of Task-Consistent Path Planning that solves the problem of find- ing a valid robot-base path needed to print larger-than-self trajectories. A motion planning and control strategy is then proposed, utilising the robot-base paths found to inform an optimisation-based whole-body motion controller. Several Mobile 3D Printing robot prototypes are built throughout this work, and the overall path and motion planning strategy proposed is holistically evaluated in a series of large-scale 3D printing experiments
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