Design and Development of Smart Brain-Machine-Brain Interface (SBMIBI) for Deep Brain Stimulation and Other Biomedical Applications

Machine collaboration with the biological body/brain by sending electrical information back and forth is one of the leading research areas in neuro-engineering during the twenty-first century. Hence, Brain-Machine-Brain Interface (BMBI) is a powerful tool for achieving such machine-brain/body collaboration. BMBI generally is a smart device (usually invasive) that can record, store, and analyze neural activities, and generate corresponding responses in the form of electrical pulses to stimulate specific brain regions. The Smart Brain-Machine-Brain-Interface (SBMBI) is a step forward with compared to the traditional BMBI by including smart functions, such as in-electrode local computing capabilities, and availability of cloud connectivity in the system to take the advantage of powerful cloud computation in decision making. In this dissertation work, we designed and developed an innovative form of Smart Brain-Machine-Brain Interface (SBMBI) and studied its feasibility in different biomedical applications. With respect to power management, the SBMBI is a semi-passive platform. The communication module is fully passive—powered by RF harvested energy; whereas, the signal processing core is battery-assisted. The efficiency of the implemented RF energy harvester was measured to be 0.005%. One of potential applications of SBMBI is to configure a Smart Deep-Brain-Stimulator (SDBS) based on the general SBMBI platform. The SDBS consists of brain-implantable smart electrodes and a wireless-connected external controller. The SDBS electrodes operate as completely autonomous electronic implants that are capable of sensing and recording neural activities in real time, performing local processing, and generating arbitrary waveforms for neuro-stimulation. A bidirectional, secure, fully-passive wireless communication backbone was designed and integrated into this smart electrode to maintain contact between the smart electrodes and the controller. The standard EPC-Global protocol has been modified and adopted as the communication protocol in this design. The proposed SDBS, by using a SBMBI platform, was demonstrated and tested through a hardware prototype. Additionally the SBMBI was employed to develop a low-power wireless ECG data acquisition device. This device captures cardiac pulses through a non-invasive magnetic resonance electrode, processes the signal and sends it to the backend computer through the SBMBI interface. Analysis was performed to verify the integrity of received ECG data

Micron-scale monolithically-integrated ultrasonic wireless sensing motes for physiological monitoring

There has been increasing interest in emerging implantable medical devices (IMDs) for continuous in vivo sensing of physiological signals, including temperature, PH, pressure, oxygen, and glucose, directly at the target locations. Many of these applications can benefit from wireless, miniaturized IMDs that eliminate the percutaneous power cords and facilitate the implantation procedures. This thesis describes such a device for real-time in vivo monitoring of physiological temperature, such as the monitoring of core body temperature and temperature evaluation during thermal-related therapeutic procedures. Featuring a custom temperature sensor chip with a micron-scale piezoelectric transducer fabricated on top of the chip, the monolithic device, in the form of a mote, measures only 380 μm × 300 μm × 570 μm and weighs only 0.3 mg. The device utilizes ultrasound for wireless powering and communication through the on-chip transducer and achieves aggressive miniaturization through “chip-as-system” integration. The proposed motes were successfully validated in both in vitro experiments with animal tissues and in vivo settings with a mouse model. Compared to the state-of-the-art and equivalent commercial devices, the motes performed comparably or better in a fully-wireless manner while presenting a more compact form factor. Such extreme miniaturization through monolithic integration enables multiple of these motes to be implanted/injected using minimally invasive surgeries with improved biocompatibility and reduced subject discomfort. This offers new approaches for localized in vivo monitoring of spatially-fine-grained temperature distributions and also provides a platform for sensing other types of physiological parameters

Smart Devices and Systems for Wearable Applications

Wearable technologies need a smooth and unobtrusive integration of electronics and smart materials into textiles. The integration of sensors, actuators and computing technologies able to sense, react and adapt to external stimuli, is the expression of a new generation of wearable devices. The vision of wearable computing describes a system made by embedded, low power and wireless electronics coupled with smart and reliable sensors - as an integrated part of textile structure or directly in contact with the human body. Therefore, such system must maintain its sensing capabilities under the demand of normal clothing or textile substrate, which can impose severe mechanical deformation to the underlying garment/substrate. The objective of this thesis is to introduce a novel technological contribution for the next generation of wearable devices adopting a multidisciplinary approach in which knowledge of circuit design with Ultra-Wide Band and Bluetooth Low Energy technology, realization of smart piezoresistive / piezocapacitive and electro-active material, electro-mechanical characterization, design of read-out circuits and system integration find a fundamental and necessary synergy. The context and the results presented in this thesis follow an “applications driven” method in terms of wearable technology. A proof of concept has been designed and developed for each addressed issue. The solutions proposed are aimed to demonstrate the integration of a touch/pressure sensor into a fabric for space debris detection (CApture DEorbiting Target project), the effectiveness of the Ultra-Wide Band technology as an ultra-low power data transmission option compared with well known Bluetooth (IR-UWB data transmission project) and to solve issues concerning human proximity estimation (IR-UWB Face-to-Face Interaction and Proximity Sensor), wearable actuator for medical applications (EAPtics project) and aerospace physiology countermeasure (Gravity Loading Countermeasure Skinsuit project)

Modern Telemetry

Telemetry is based on knowledge of various disciplines like Electronics, Measurement, Control and Communication along with their combination. This fact leads to a need of studying and understanding of these principles before the usage of Telemetry on selected problem solving. Spending time is however many times returned in form of obtained data or knowledge which telemetry system can provide. Usage of telemetry can be found in many areas from military through biomedical to real medical applications. Modern way to create a wireless sensors remotely connected to central system with artificial intelligence provide many new, sometimes unusual ways to get a knowledge about remote objects behaviour. This book is intended to present some new up to date accesses to telemetry problems solving by use of new sensors conceptions, new wireless transfer or communication techniques, data collection or processing techniques as well as several real use case scenarios describing model examples. Most of book chapters deals with many real cases of telemetry issues which can be used as a cookbooks for your own telemetry related problems

The selection and evaluation of a sensory technology for interaction in a warehouse environment

In recent years, Human-Computer Interaction (HCI) has become a significant part of modern life as it has improved human performance in the completion of daily tasks in using computerised systems. The increase in the variety of bio-sensing and wearable technologies on the market has propelled designers towards designing more efficient, effective and fully natural User-Interfaces (UI), such as the Brain-Computer Interface (BCI) and the Muscle-Computer Interface (MCI). BCI and MCI have been used for various purposes, such as controlling wheelchairs, piloting drones, providing alphanumeric inputs into a system and improving sports performance. Various challenges are experienced by workers in a warehouse environment. Because they often have to carry objects (referred to as hands-full) it is difficult to interact with traditional devices. Noise undeniably exists in some industrial environments and it is known as a major factor that causes communication problems. This has reduced the popularity of using verbal interfaces with computer applications, such as Warehouse Management Systems. Another factor that effects the performance of workers are action slips caused by a lack of concentration during, for example, routine picking activities. This can have a negative impact on job performance and allow a worker to incorrectly execute a task in a warehouse environment. This research project investigated the current challenges workers experience in a warehouse environment and the technologies utilised in this environment. The latest automation and identification systems and technologies are identified and discussed, specifically the technologies which have addressed known problems. Sensory technologies were identified that enable interaction between a human and a computerised warehouse environment. Biological and natural behaviours of humans which are applicable in the interaction with a computerised environment were described and discussed. The interactive behaviours included the visionary, auditory, speech production and physiological movement where other natural human behaviours such paying attention, action slips and the action of counting items were investigated. A number of modern sensory technologies, devices and techniques for HCI were identified with the aim of selecting and evaluating an appropriate sensory technology for MCI. iii MCI technologies enable a computer system to recognise hand and other gestures of a user, creating means of direct interaction between a user and a computer as they are able to detect specific features extracted from a specific biological or physiological activity. Thereafter, Machine Learning (ML) is applied in order to train a computer system to detect these features and convert them to a computer interface. An application of biomedical signals (bio-signals) in HCI using a MYO Armband for MCI is presented. An MCI prototype (MCIp) was developed and implemented to allow a user to provide input to an HCI, in a hands-free and hands-full situation. The MCIp was designed and developed to recognise the hand-finger gestures of a person when both hands are free or when holding an object, such a cardboard box. The MCIp applies an Artificial Neural Network (ANN) to classify features extracted from the surface Electromyography signals acquired by the MYO Armband around the forearm muscle. The MCIp provided the results of data classification for gesture recognition to an accuracy level of 34.87% with a hands-free situation. This was done by employing the ANN. The MCIp, furthermore, enabled users to provide numeric inputs to the MCIp system hands-full with an accuracy of 59.7% after a training session for each gesture of only 10 seconds. The results were obtained using eight participants. Similar experimentation with the MYO Armband has not been found to be reported in any literature at submission of this document. Based on this novel experimentation, the main contribution of this research study is a suggestion that the application of a MYO Armband, as a commercially available muscle-sensing device on the market, has the potential as an MCI to recognise the finger gestures hands-free and hands-full. An accurate MCI can increase the efficiency and effectiveness of an HCI tool when it is applied to different applications in a warehouse where noise and hands-full activities pose a challenge. Future work to improve its accuracy is proposed

Near-field baseband communication system for use in biomedical implants

This thesis introduces the reader to the near-field baseband pulse radio communication for biomedical implants. It details the design and implementation of the complete communication system with a particular emphasis on the antenna structure and waveform coding that is compatible with this particular technology. The wireless communication system has great employability in small pill-sized biomedical diagnostic devices offering the advantages of low power consumption and easy integration with SoC and lab-in-a-pill technologies. The greatest challenge was the choice of antenna that had to be made to effectively transmit the pulses. A systematic approach has been carried out in arriving at the most suitable antenna for efficient emanation of pulses and the fields around it are analysed electromagnetically using a commercially available software. A magnetic antenna can be used to transmit the information from inside a human body to the outside world. The performance of the above antenna was evaluated in a salt solution of different concentrations which is similar to a highly conductive lossy medium like a human body. Near-field baseband pulse transmission is a waveform transmission scheme wherein the pulse shape is crucial for decoding information at the receiver. This demands a new approach to the antenna design, both at the transmitter and the receiver. The antenna had to be analysed in the time-domain to know its effects on the pulse and an expression for the antenna bandwidth has been proposed in this thesis. The receiving antenna should be able to detect very short pulses and while doing so has to also maintain the pulse shape with minimal distortion. Different loading congurations were explored to determine the most feasible one for receiving very short pulses. Return-to-zero (RZ), Non-return-zero (NRZ) and Manchester coded pulse waveforms were tested for their compatibility and performance with the near-field baseband pulse radio communication. It was concluded that Manchester coded waveform are perfectly suited for this particular near-field communication technology. Pulse interval modulation was also investigated and the findings suggested that it was easier to implement and had a high throughput rate too. A simple receiver algorithm has been suggested and practically tested on a digital signal processor. There is further scope for research to develop complex signal processing algorithms at the receiver

Towards end-to-end security in internet of things based healthcare

Healthcare IoT systems are distinguished in that they are designed to serve human beings, which primarily raises the requirements of security, privacy, and reliability. Such systems have to provide real-time notifications and responses concerning the status of patients. Physicians, patients, and other caregivers demand a reliable system in which the results are accurate and timely, and the service is reliable and secure. To guarantee these requirements, the smart components in the system require a secure and efficient end-to-end communication method between the end-points (e.g., patients, caregivers, and medical sensors) of a healthcare IoT system. The main challenge faced by the existing security solutions is a lack of secure end-to-end communication. This thesis addresses this challenge by presenting a novel end-to-end security solution enabling end-points to securely and efficiently communicate with each other. The proposed solution meets the security requirements of a wide range of healthcare IoT systems while minimizing the overall hardware overhead of end-to-end communication. End-to-end communication is enabled by the holistic integration of the following contributions. The first contribution is the implementation of two architectures for remote monitoring of bio-signals. The first architecture is based on a low power IEEE 802.15.4 protocol known as ZigBee. It consists of a set of sensor nodes to read data from various medical sensors, process the data, and send them wirelessly over ZigBee to a server node. The second architecture implements on an IP-based wireless sensor network, using IEEE 802.11 Wireless Local Area Network (WLAN). The system consists of a IEEE 802.11 based sensor module to access bio-signals from patients and send them over to a remote server. In both architectures, the server node collects the health data from several client nodes and updates a remote database. The remote webserver accesses the database and updates the webpage in real-time, which can be accessed remotely. The second contribution is a novel secure mutual authentication scheme for Radio Frequency Identification (RFID) implant systems. The proposed scheme relies on the elliptic curve cryptography and the D-Quark lightweight hash design. The scheme consists of three main phases: (1) reader authentication and verification, (2) tag identification, and (3) tag verification. We show that among the existing public-key crypto-systems, elliptic curve is the optimal choice due to its small key size as well as its efficiency in computations. The D-Quark lightweight hash design has been tailored for resource-constrained devices. The third contribution is proposing a low-latency and secure cryptographic keys generation approach based on Electrocardiogram (ECG) features. This is performed by taking advantage of the uniqueness and randomness properties of ECG's main features comprising of PR, RR, PP, QT, and ST intervals. This approach achieves low latency due to its reliance on reference-free ECG's main features that can be acquired in a short time. The approach is called Several ECG Features (SEF)-based cryptographic key generation. The fourth contribution is devising a novel secure and efficient end-to-end security scheme for mobility enabled healthcare IoT. The proposed scheme consists of: (1) a secure and efficient end-user authentication and authorization architecture based on the certificate based Datagram Transport Layer Security (DTLS) handshake protocol, (2) a secure end-to-end communication method based on DTLS session resumption, and (3) support for robust mobility based on interconnected smart gateways in the fog layer. Finally, the fifth and the last contribution is the analysis of the performance of the state-of-the-art end-to-end security solutions in healthcare IoT systems including our end-to-end security solution. In this regard, we first identify and present the essential requirements of robust security solutions for healthcare IoT systems. We then analyze the performance of the state-of-the-art end-to-end security solutions (including our scheme) by developing a prototype healthcare IoT system

Performing the digital: performativity and performance studies in digital cultures

How is performativity shaped by digital technologies - and how do performative practices reflect and alter techno-social formations? "Performing the Digital" explores, maps and theorizes the conditions and effects of performativity in digital cultures. Bringing together scholars from performance studies, media theory, sociology and organization studies as well as practitioners of performance, the contributions engage with the implications of digital media and its networked infrastructures for modulations of affect and the body, for performing cities, protest, organization and markets, and for the performativity of critique. With contributions by Marie-Luise Angerer, Timon Beyes, Scott deLahunta and Florian Jenett, Margarete Jahrmann, Susan Kozel, Ann-Christina Lange, Oliver Leistert, Martina Leeker, Jon McKenzie, Sigrid Merx, Melanie Mohren and Bernhard Herbordt, Imanuel Schipper and Jens Schröter

Directly Printed Nanomaterial Sensor for Strain and Vibration Measurement

학위논문 (박사) -- 서울대학교 대학원 : 공과대학 기계공학부, 2020. 8. 안성훈.Most discussions about Industrie 4.0 tacitly assume that any such system would involve the processing and evaluation of large data volumes. Specifically, the operation of complex production processes requires stable and reliable data measurement and communication systems. However, while modern sensor technology may already be capable of collecting a wide range of machine and production data, it has been proving difficult to measure and analyse the data which is not easy to measurable and feed the results quickly back into an optimised production cycle. This is why the cost and installation of sensor, data acquisition, and transmission systems for flexible and adaptive manufacturing process have not been match the requirement of industrial demands. In this dissertation, directly printed nanomaterial sensor capable of strain and vibration measurement with high sensitivity and wide measurable range was fabricated using aerodynamically focused nanomaterial (AFN) printing system which is a direct printing technique for conductive and stretchable pattern printing onto flexible substrate. Specifically, microscale porous conductive pattern composed of silver nanoparticles (AgNPs) and multi-walled carbon nanotubes (MWCNTs) composite was printed onto polydimethylsiloxane (PDMS). Printing mechanism of AFN printing system for nanocomposite onto flexible substrate in order of mechanical crack generation, seed layer deposition, partial aggregation, and fully deposition was demonstrated and experimentally validated. The printed nanocomposite sensor exhibited gauge factor (GF) of 58.7, measurable range of 0.74, and variance in peak resistance under 0.05 during 1,000 times life cycle evaluation test. Furthermore, vibration measurement performance was evaluated according to vibration amplitude and frequency with Q-factor evaluation and statistical verification. Sensing mechanism for nanocomposite sensor was also analysed and discussed by both analytical and statistical methods. First, electron tunnelling effect among nanomaterials was analysed statistically using bivariate probit model. Since electrical property varies by the geometrical properties of nanomaterial, Monte Carlo simulation method based on Lennard-Jones (LJ) potential model and the voter model was developed for deeper understanding of the dynamics of nanomaterial by strain. By simply counting the average attachment among nanomaterials by strain, electrical conductivity was easily estimated with low simulation cost. The main objective of all processes to manufacture high-tech products is compliance with the specified ranges of permissible variation. In this perspective, all data must be recorded that might provide some evidence of status changes anywhere along the process chain. This dissertation covers the monitoring of forming and milling process. By measurement of mechanical deformation of stamp during forming process, it was possible to estimate the forming force according to various process parameters including maximum force, force gradient, and the thickness of sheet metal. Furthermore, accurate and reliable vibration monitoring was also conducted during milling process by simple and direct attachment of printed sensor to workpiece. Using frequency and power spectrum analysis of obtained data, the vibration of workpiece was measured during milling process according to process parameters including RPM, feed rate, cutting depth and width of spindle. Finally, developed sensor was applied to the digital twin of turbine blade manufacturing that vibration greatly affects the quality of product to predict the process defects in real time. To overcome the wire required data acquisition and transmission system, directly printed wireless communication sensor was also developed using chipless radio frequency identification (RFID) technology. It is one of the widely used technique for internet-of-things (IoT) devices due to low-cost, printability, and simplicity. The developed stretchable and chipless RFID sensor exhibited GF more than 0.6 and maximum measurable range more than 0.2 with high degree-of-freedom of motion. Since it showed its original characteristics of sensing in only one direction independently, sensor patch composed of various sensor with different resonance frequency was capable of measuring not only normal strains but also shear strains in all directions. Sensors in machinery and equipment can provide valuable clues as to whether or not the actual values will fall into the tolerance range. In this aspect, a real-time, accurate, and reliable process monitoring is a basic and crucial enabler of intelligent manufacturing operations and digital twin applications. In this dissertation, developed sensor was used for various manufacturing process include forming process, milling process, and wireless communication using highly sensitive and wide measuring properties with low fabrication cost. It is expected that developed sensor could be applied for the digital twin and process defects prediction in real-time.4차 산업혁명에 대한 대부분의 논의는 많은 양의 데이터를 처리하고 평가하는 시스템을 암묵적으로 가정한다. 특히, 복잡한 생산 공정을 운영하기 위해서는 안정적이고 신뢰할 수 있는 데이터 측정 및 통신 시스템이 필요하다. 하지만, 최신 센서 기술은 광범위한 기계 및 생산 공정 중 데이터를 수집하는 것이 가능하지만 측정하기 쉽지 않은 데이터를 측정하고 분석하여 그 결과를 최적화된 생산 공정에 신속하게 제공하는데 한계를 가지고 있다. 때문에, 유연하고 적응 가능한 제조 공정을 위한 센서의 가격과 설치 방법, 데이터 수집 및 전송 시스템이 실제 산업의 요구 사항에 도달하지 못하고 있다. 이 학위 논문에서는 유연 기판에 전도성 및 신축성 패턴을 직접 인쇄할 수 있는 공기역학적 나노물질 집속 인쇄 시스템을 사용하여 높은 민감도와 넓은 측정 가능 범위를 가진 변위 및 진동 센서를 개발하였다. 구체적으로, 은 나노입자와 다중 벽 탄소 나노튜브로 구성된 나노 복합재를 폴리디메틸실록산 위에 직접 인쇄하였다. 유연 기판 위에 공기역학적 나노물질 집속 인쇄 시스템을 사용한 나노 복합재 인쇄 방법의 기작이 기계적 균열 발생, 시드층 적층, 부분 응집 및 완전 증착 순으로 논의 및 실험적으로 검증되었다. 인쇄된 나노 복합재 센서는 58.7의 게이지 팩터, 0.74의 측정 가능 범위를 나타내었으며 1,000번 반복된 수명 주기 평가에서 5% 미만의 정점 저항 변화를 확인할 수 있었다. 또한 Q 인자 평가 및 통계 검증을 사용하여 진동의 진폭 및 주파수에 따른 진동 측정 성능을 평가하였다. 나노 복합재 센서에 대한 측정 기작 또한 해석적 및 통계적 방법으로 분석되었다. 먼저, 나노물질 간 터널 효과가 이변량 프로빗 모델을 통해 통계적으로 분석되었다. 센서의 전기적 물성이 나노물질의 기하학적 물성에 따라 상이하기 때문에 변위에 따른 나노물질의 동적인 이해를 위해 레너드존스 전위 및 유권자 모델을 기반으로 한 몬테카를로 시뮬레이션 방법이 개발되었다. 이를 활용하여 나노물질 간 평균 부착 수를 계산하여 낮은 비용으로 전기전도도를 추정할 수 있었다. 첨단 제품을 제조하기 위한 모든 공정의 주요 목표는 지정된 범위의 허용 가능한 변동을 준수하는 것이다. 이를 위해 공정 중 어디에서나 상태 변경의 증거를 제공할 수 있는 모든 데이터를 기록하는 것이 필수적이다. 이 학위 논문에서는 제작된 센서를 통해 성형 및 절삭 공정의 데이터를 기록함으로써 공정을 모니터링하였다. 성형 공정 동안 스탬프의 기계적 변형을 측정함으로써 최대 힘, 힘의 구배 및 판금의 두께를 포함하는 다양한 공정 변수에 따라 성형 힘을 추정할 수 있었다. 또한, 절삭 공정 중 공작물에 제작된 센서를 직접 부착하여 정확하고 안정적인 진동 모니터링을 수행하였다. 얻어진 데이터의 주파수 및 전력 스펙트럼 분석을 이용하여, 분당 회전 수, 이송 속도, 스핀들의 절삭 깊이 및 너비에 따른 공작물의 진동을 측정하였다. 마지막으로 제조된 센서를 진동이 제품 품질에 큰 영향을 미치는 터빈 동익 제조 공정의 디지털 트윈으로 적용하여 실시간으로 공정 결함을 예측하였다. 유선 데이터 수집 및 전송 시스템을 극복하기 위해 칩리스 무선 주파수 식별 기술을 사용하여 직접 인쇄된 무선 통신 센서를 개발하였다. 칩리스 무선 주파수 식별 기술은 저비용, 인쇄성 및 공정의 평이성으로 인해 사물 인터넷 장치에 널리 사용되는 기술 중 하나이다. 개발된 유연한 칩리스 센서는 0.6 이상의 게이지 팩터와 0.2 이상의 측정 가능 범위를 나타냈다. 또한 제작된 센서는 한 방향의 변위만 독립적으로 측정할 수 있는 특성을 가지고 있기 때문에, 모든 방향의 수직 및 전단 변형을 측정할 수 있는 다양한 공진 주파수로 구성된 센서 패치가 개발되었다. 기계 및 장비의 센서는 실제 값이 공차 범위에 속하는지 여부에 대한 중요한 단서를 제공할 수 있다. 이러한 측면에서, 정확하고 신뢰할 수 있는 실시간 공정 모니터링은 지능형 제조 공정 및 디지털 트윈으로의 응용을 위한 기본적이고 결정적인 요소이다. 이 학위 논문에서 개발된 센서는 낮은 제조 비용과 높은 민감도 및 신축성을 가지고 있기 때문에 성형 공정, 절삭 공정, 무선 통신을 포함한 다양한 제조 공정에서 응용되었다. 뿐만 아니라 제작된 센서는 디지털 트윈 및 공정 결함의 실시간 예측을 위해 다양하게 사용될 수 있을 것으로 예상된다.Chapter 1. Introduction 1 1.1. Toward smart manufacturing 1 1.2. Sensor in manufacturing 4 1.3. Research objective 11 Chapter 2. Background 16 2.1. Aerodynamically focused nanomaterial printing 16 2.2. Printing system envelope 26 2.3. Highly sensitive sensor printing 34 Chapter 3. Sensor fabrication and evaluation 42 3.1. Highly sensitive and wide measuring sensor printing 42 3.2. Sensing performance evaluation 59 3.3. Environmental and industrial evaluation 87 Chapter 4. Sensing mechanism analysis 97 4.1. Theoretical background 97 4.2. Statistical regression anaylsis 101 4.3. Monte Carlo simulation 104 Chapter 5. Application to process monitoring 126 5.1. Forming process monitoring 126 5.2. Milling process monitoring 133 5.3. Wireless communication monitoring 149 Chapter 6. Conclusion 185 Bibliography 192 Abstract in Korean 211Docto

The screen as boundary object in the realm of imagination

As an object at the boundary between virtual and physical reality, the screen exists both as a displayer and as a thing displayed, thus functioning as a mediator. The screen's virtual imagery produces a sense of immersion in its viewer, yet at the same time the materiality of the screen produces a sense of rejection from the viewer's complete involvement in the virtual world. The experience of the screen is thus an oscillation between these two states of immersion and rejection. Nowadays, as interactivity becomes a central component of the relationship between viewers and many artworks, the viewer experience of the screen is changing. Unlike the screen experience in non-interactive artworks, such as the traditional static screen of painting or the moving screen of video art in the 1970s, interactive media screen experiences can provide viewers with a more immersive, immediate, and therefore, more intense experience. For example, many digital media artworks provide an interactive experience for viewers by capturing their face or body though real-time computer vision techniques. In this situation, as the camera and the monitor in the artwork encapsulate the interactor's body in an instant feedback loop, the interactor becomes a part of the interface mechanism and responds to the artwork as the system leads or even provokes them. This thesis claims that this kind of direct mirroring in interactive screen-based media artworks does not allow the viewer the critical distance or time needed for self-reflection. The thesis examines the previous aesthetics of spatial and temporal perception, such as presentness and instantaneousness, and the notions of passage and of psychological perception such as reflection, reflexiveness and auratic experience, looking at how these aesthetics can be integrated into new media screen experiences. Based on this theoretical research, the thesis claims that interactive screen spaces can act as a site for expression and representation, both through a doubling effect between the physical and virtual worlds, and through manifold spatial and temporal mappings with the screen experience. These claims are further supported through exploration of screen-based media installations created by the author since 2003.Ph.D.Committee Chair: Mazalek, Ali; Committee Member: Bolter, Jay David; Committee Member: Do, Ellen Yi-Luen; Committee Member: Nitsche, Michael; Committee Member: Winegarden, Claudia R