98 research outputs found

    Beam scanning by liquid-crystal biasing in a modified SIW structure

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    A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium

    Autonomous Radar-based Gait Monitoring System

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    Features related to gait are fundamental metrics of human motion [1]. Human gait has been shown to be a valuable and feasible clinical marker to determine the risk of physical and mental functional decline [2], [3]. Technologies that detect changes in people’s gait patterns, especially older adults, could support the detection, evaluation, and monitoring of parameters related to changes in mobility, cognition, and frailty. Gait assessment has the potential to be leveraged as a clinical measurement as it is not limited to a specific health care discipline and is a consistent and sensitive test [4]. A wireless technology that uses electromagnetic waves (i.e., radar) to continually measure gait parameters at home or in a hospital without a clinician’s participation has been proposed as a suitable solution [3], [5]. This approach is based on the interaction between electromagnetic waves with humans and how their bodies impact the surrounding and scattered wireless signals. Since this approach uses wireless waves, people do not need to wear or carry a device on their bodies. Additionally, an electromagnetic wave wireless sensor has no privacy issues because there is no video-based camera. This thesis presents the design and testing of a radar-based contactless system that can monitor people’s gait patterns and recognize their activities in a range of indoor environments frequently and accurately. In this thesis, the use of commercially available radars for gait monitoring is investigated, which offers opportunities to implement unobtrusive and contactless gait monitoring and activity recognition. A novel fast and easy-to-implement gait extraction algorithm that enables an individual’s spatiotemporal gait parameter extraction at each gait cycle using a single FMCW (Frequency Modulated Continuous Wave) radar is proposed. The proposed system detects changes in gait that may be the signs of changes in mobility, cognition, and frailty, particularly for older adults in individual’s homes, retirement homes and long-term care facilities retirement homes. One of the straightforward applications for gait monitoring using radars is in corridors and hallways, which are commonly available in most residential homes, retirement, and long-term care homes. However, walls in the hallway have a strong “clutter” impact, creating multipath due to the wide beam of commercially available radar antennas. The multipath reflections could result in an inaccurate gait measurement because gait extraction algorithms employ the assumption that the maximum reflected signals come from the torso of the walking person (rather than indirect reflections or multipath) [6]. To address the challenges of hallway gait monitoring, two approaches were used: (1) a novel signal processing method and (2) modifying the radar antenna using a hyperbolic lens. For the first approach, a novel algorithm based on radar signal processing, unsupervised learning, and a subject detection, association and tracking method is proposed. This proposed algorithm could be paired with any type of multiple-input multiple-output (MIMO) or single-input multiple-output (SIMO) FMCW radar to capture human gait in a highly cluttered environment without needing radar antenna alteration. The algorithm functionality was validated by capturing spatiotemporal gait values (e.g., speed, step points, step time, step length, and step count) of people walking in a hallway. The preliminary results demonstrate the promising potential of the algorithm to accurately monitor gait in hallways, which increases opportunities for its applications in institutional and home environments. For the second approach, an in-package hyperbola-based lens antenna was designed that can be integrated with a radar module package empowered by the fast and easy-to-implement gait extraction method. The system functionality was successfully validated by capturing the spatiotemporal gait values of people walking in a hallway filled with metallic cabinets. The results achieved in this work pave the way to explore the use of stand-alone radar-based sensors in long hallways for day-to-day long-term monitoring of gait parameters of older adults or other populations. The possibility of the coexistence of multiple walking subjects is high, especially in long-term care facilities where other people, including older adults, might need assistance during walking. GaitRite and wearables are not able to assess multiple people’s gait at the same time using only one device [7], [8]. In this thesis, a novel radar-based algorithm is proposed that is capable of tracking multiple people or extracting walking speed of a participant with the coexistence of other people. To address the problem of tracking and monitoring multiple walking people in a cluttered environment, a novel iterative framework based on unsupervised learning and advanced signal processing was developed and tested to analyze the reflected radio signals and extract walking movements and trajectories in a hallway environment. Advanced algorithms were developed to remove multipath effects or ghosts created due to the interaction between walking subjects and stationary objects, to identify and separate reflected signals of two participants walking at a close distance, and to track multiple subjects over time. This method allows the extraction of walking speed in multiple closely-spaced subjects simultaneously, which is distinct from previous approaches where the speed of only one subject was obtained. The proposed multiple-people gait monitoring was assessed with 22 participants who participated in a bedrest (BR) study conducted at McGill University Health Centre (MUHC). The system functionality also was assessed for in-home applications. In this regard, a cloud-based system is proposed for non-contact, real-time recognition and monitoring of physical activities and walking periods within a domestic environment. The proposed system employs standalone Internet of Things (IoT)-based millimeter wave radar devices and deep learning models to enable autonomous, free-living activity recognition and gait analysis. Range-Doppler maps generated from a dataset of real-life in-home activities are used to train deep learning models. The performance of several deep learning models was evaluated based on accuracy and prediction time, with the gated recurrent network (GRU) model selected for real-time deployment due to its balance of speed and accuracy compared to 2D Convolutional Neural Network Long Short-Term Memory (2D-CNNLSTM) and Long Short-Term Memory (LSTM) models. In addition to recognizing and differentiating various activities and walking periods, the system also records the subject’s activity level over time, washroom use frequency, sleep/sedentary/active/out-of-home durations, current state, and gait parameters. Importantly, the system maintains privacy by not requiring the subject to wear or carry any additional devices

    1-D broadside-radiating leaky-wave antenna based on a numerically synthesized impedance surface

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    A newly-developed deterministic numerical technique for the automated design of metasurface antennas is applied here for the first time to the design of a 1-D printed Leaky-Wave Antenna (LWA) for broadside radiation. The surface impedance synthesis process does not require any a priori knowledge on the impedance pattern, and starts from a mask constraint on the desired far-field and practical bounds on the unit cell impedance values. The designed reactance surface for broadside radiation exhibits a non conventional patterning; this highlights the merit of using an automated design process for a design well known to be challenging for analytical methods. The antenna is physically implemented with an array of metal strips with varying gap widths and simulation results show very good agreement with the predicted performance

    In Vivo computation - Where computing meets nanosytem for smart tumor biosensing

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    According to World Health Organization, 13.1 million people will die in the world just because of cancer by 2030. Early tumor detection is very crucial to saving the world from this alarming mortality rate. However, it is an insurmountable challenge for the existing medical imaging techniques with limited imaging resolution to detect microscopic tumors. Hence, the need of the hour is to explore novel cross-disciplinary strategies to solve this problem. The rise of nanotechnologies provides a strong belief to solve complex medical problems such as early tumor detection. Nanoparticles with sizes ranging between 1-100 nanometers can be used as contrast agents. Their small sizes enable them to leak out of blood vessels and accumulate within tumors. Moreover, their chemical, optical, magnetic and electronic properties also change at nanoscale, which make them an ideal probing agent to spatially highlight the tumor site. Though, using nanoparticles to target malignant tumors is a promising concept, only 0.7% of the injected nanoparticles reach the tumor according to the statistical results of last 10 years. In PhD work, we proposed novel in vivo computational frameworks for fast, accurate and robust nanobiosensing. Specifically, the peritumoral region corresponds to the “objective function”; the tumor is the “global optimum”; the region of interest is the “domain” of the objective function; and the nanoswimmers are the “computational agents” (i.e., guesses or optimization variables). First, in externally manipulable in vivo computation, nanoswimmers are used as contrast agents to probe the region of interest. The observable characteristics of these nanoswimmers, under the influence of tumor-induced biological gradients, are utilized by the external tracking system to steer nanoswimmers towards the possible tumor direction. To take it one step ahead, we provide solutions to the real-life constraints of in vivo natural computation such as uniformity of the external steering force and finite life span of the nanoswimmers. To overcome these challenges, we propose a multi-estimate-fusion strategy to obtain a common steering direction for the swarm of nanoswimmers and an iterative memory-driven gradient descent optimization strategy for faster tumor sensitization. Next, we proposed a parallel framework called autonomous in vivo computation, where the tumor sensitization is highly scalable and tracking-free. We demonstrate that the tumor-triggered biophysical gradients can be leveraged by nanoparticles to collectively move toward the potential tumor hypoxic regions without the aid of any external intervention. Although individual nanoparticles have no target-directed locomotion ability due to limited communication and computation capability, we showed that once passive collaboration is achieved, they can successfully avoid obstacles and detect the tumor. Finally, to address the respective limitations of externally manipulable and autonomous settings such as constant monitoring and slow detection, we proposed a semi-autonomous in vivo computational framework. We showed that the spot sampling strategy for an autonomous swarm of nanoswimmers can achieve faster tumor sensitization in complex environments. This approach makes the swarm highly scalable along with giving it the freedom from constant monitoring. The performance of the aforementioned tumor sensitization frameworks is evaluated through comprehensive in silico experiments that mimic the realistic targeting processes in externally manipulable, self-regulatable and semi-autonomous settings. The efficacies of the proposed frameworks are demonstrated through numerical simulations that incorporate various physical constraints with respect to controlling and steering of computational agents, their motion in discretized vascular networks and their motion under the influence of disturbance and noise

    Cyber-Human Systems, Space Technologies, and Threats

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    CYBER-HUMAN SYSTEMS, SPACE TECHNOLOGIES, AND THREATS is our eighth textbook in a series covering the world of UASs / CUAS/ UUVs / SPACE. Other textbooks in our series are Space Systems Emerging Technologies and Operations; Drone Delivery of CBNRECy – DEW Weapons: Emerging Threats of Mini-Weapons of Mass Destruction and Disruption (WMDD); Disruptive Technologies with applications in Airline, Marine, Defense Industries; Unmanned Vehicle Systems & Operations On Air, Sea, Land; Counter Unmanned Aircraft Systems Technologies and Operations; Unmanned Aircraft Systems in the Cyber Domain: Protecting USA’s Advanced Air Assets, 2nd edition; and Unmanned Aircraft Systems (UAS) in the Cyber Domain Protecting USA’s Advanced Air Assets, 1st edition. Our previous seven titles have received considerable global recognition in the field. (Nichols & Carter, 2022) (Nichols, et al., 2021) (Nichols R. K., et al., 2020) (Nichols R. , et al., 2020) (Nichols R. , et al., 2019) (Nichols R. K., 2018) (Nichols R. K., et al., 2022)https://newprairiepress.org/ebooks/1052/thumbnail.jp

    Antenna Development in Brain-Implantable Biotelemetric Systems for Next-Generation of Human Healthcare

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    In the growing efforts of promoting patients’ life quality through health technology solutions, implantable wireless medical devices (IMDs) have been identified as one of the frontrunners. They are bringing compelling wireless solutions for medical diagnosis and treatment through bio-telemetric systems that deliver real-time transmission of in-body physiological data to an external monitoring/control unit. To set up this bidirectional wireless biomedical communication link for the long- term, the IMDs need small and efficient antennas. Designing antenna-enabled biomedical telemetry is a challenging aim, which must fulfill demanding issues and criteria including miniaturization, appropriate radiation performance, bandwidth enhancement, good impedance matching, and biocompatibility. Overcoming the size restriction mainly depends on the resonant frequency of the required applications. Defined frequency bands for biomedical telemetry systems contain the Medical Implant Communication Service (MICS) operating at the frequency band of 402– 405 MHz, Medical Device Radiocommunication Service (MedRadio) resonating at the frequency ranges of 401– 406 MHz, 413 – 419 MHz, 426 – 432 MHz, 438 – 444 MHz, and 451 – 457 MHz, Wireless Medical Telemetry Service (WMTS) operating at frequency specturms of 1395 to 1400 MHz and 1427 to 1432 MHz, and Industrial, Scientific, and Medical (ISM) bands of 433.1–434.8 MHz, 868–868.6 MHz, 902.8–928.0 MHz, and 2.4–2.48 GHz. On the other hand, a single band antenna may not fulfill all requirements of a bio-telemetry system in either MedRadio, WMTS, or ISM bands. As a result, analyzing dual/multi-band implantable antenna supporting wireless power, data transmission, and control signaling can meet the demand for multitasking biotelemetry systems. In addition, among different antenna structures, PIFA has been found a promising type in terms of size-performance balance in lossy human tissues. To overcome the above-mentioned challenges, this thesis, first, starts with a discussion of antenna radiation in a lossy medium, the requirements of implantable antenna development, and numerical modeling of the human head tissues. In the following discussion, we concentrate on approaching a new design for far-field small antennas integrated into brain-implantable biotelemetric systems that provide attractive features for versatile functions in modern medical applications. To this end, we introduce three different implantable antenna structures including a compact dual-band PIFA, a miniature triple-band PIFA and a small quad-band PIFA for brain care applications. The compelling performance of the proposed antennas is analyzed and discussed with simulation results and the triple-band PIFA is evaluated using simulation outcomes compared with the measurement results of the fabricated prototype. Finally, the first concept and platform of in-body and off-body units are proposed for wireless dopamine monitoring as a brain care application. In addition to the main focus of this thesis, in the second stage, we focus on introducing an equivalent circuit model to the electrical connector-line transition. We present a data fitting technique for two transmission lines characterization independent of the dielectric properties of the substrate materials at the ultra-high frequency band (UHF). This approach is a promising solution for the development of wearable and off-body antennas employing textile materials in biomedical telemetry systems. The approach method is assessed with measurement results of several fabricated transmission lines on different substrate materials

    Systematic Approaches for Telemedicine and Data Coordination for COVID-19 in Baja California, Mexico

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    Conference proceedings info: ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologies Raleigh, HI, United States, March 24-26, 2023 Pages 529-542We provide a model for systematic implementation of telemedicine within a large evaluation center for COVID-19 in the area of Baja California, Mexico. Our model is based on human-centric design factors and cross disciplinary collaborations for scalable data-driven enablement of smartphone, cellular, and video Teleconsul-tation technologies to link hospitals, clinics, and emergency medical services for point-of-care assessments of COVID testing, and for subsequent treatment and quar-antine decisions. A multidisciplinary team was rapidly created, in cooperation with different institutions, including: the Autonomous University of Baja California, the Ministry of Health, the Command, Communication and Computer Control Center of the Ministry of the State of Baja California (C4), Colleges of Medicine, and the College of Psychologists. Our objective is to provide information to the public and to evaluate COVID-19 in real time and to track, regional, municipal, and state-wide data in real time that informs supply chains and resource allocation with the anticipation of a surge in COVID-19 cases. RESUMEN Proporcionamos un modelo para la implementación sistemática de la telemedicina dentro de un gran centro de evaluación de COVID-19 en el área de Baja California, México. Nuestro modelo se basa en factores de diseño centrados en el ser humano y colaboraciones interdisciplinarias para la habilitación escalable basada en datos de tecnologías de teleconsulta de teléfonos inteligentes, celulares y video para vincular hospitales, clínicas y servicios médicos de emergencia para evaluaciones de COVID en el punto de atención. pruebas, y para el tratamiento posterior y decisiones de cuarentena. Rápidamente se creó un equipo multidisciplinario, en cooperación con diferentes instituciones, entre ellas: la Universidad Autónoma de Baja California, la Secretaría de Salud, el Centro de Comando, Comunicaciones y Control Informático. de la Secretaría del Estado de Baja California (C4), Facultades de Medicina y Colegio de Psicólogos. Nuestro objetivo es proporcionar información al público y evaluar COVID-19 en tiempo real y rastrear datos regionales, municipales y estatales en tiempo real que informan las cadenas de suministro y la asignación de recursos con la anticipación de un aumento de COVID-19. 19 casos.ICICT 2023: 2023 The 6th International Conference on Information and Computer Technologieshttps://doi.org/10.1007/978-981-99-3236-

    Measuring knowledge sharing processes through social network analysis within construction organisations

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    The construction industry is a knowledge intensive and information dependent industry. Organisations risk losing valuable knowledge, when the employees leave them. Therefore, construction organisations need to nurture opportunities to disseminate knowledge through strengthening knowledge-sharing networks. This study aimed at evaluating the formal and informal knowledge sharing methods in social networks within Australian construction organisations and identifying how knowledge sharing could be improved. Data were collected from two estimating teams in two case studies. The collected data through semi-structured interviews were analysed using UCINET, a Social Network Analysis (SNA) tool, and SNA measures. The findings revealed that one case study consisted of influencers, while the other demonstrated an optimal knowledge sharing structure in both formal and informal knowledge sharing methods. Social networks could vary based on the organisation as well as the individuals’ behaviour. Identifying networks with specific issues and taking steps to strengthen networks will enable to achieve optimum knowledge sharing processes. This research offers knowledge sharing good practices for construction organisations to optimise their knowledge sharing processes

    Treatise on Hearing: The Temporal Auditory Imaging Theory Inspired by Optics and Communication

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    A new theory of mammalian hearing is presented, which accounts for the auditory image in the midbrain (inferior colliculus) of objects in the acoustical environment of the listener. It is shown that the ear is a temporal imaging system that comprises three transformations of the envelope functions: cochlear group-delay dispersion, cochlear time lensing, and neural group-delay dispersion. These elements are analogous to the optical transformations in vision of diffraction between the object and the eye, spatial lensing by the lens, and second diffraction between the lens and the retina. Unlike the eye, it is established that the human auditory system is naturally defocused, so that coherent stimuli do not react to the defocus, whereas completely incoherent stimuli are impacted by it and may be blurred by design. It is argued that the auditory system can use this differential focusing to enhance or degrade the images of real-world acoustical objects that are partially coherent. The theory is founded on coherence and temporal imaging theories that were adopted from optics. In addition to the imaging transformations, the corresponding inverse-domain modulation transfer functions are derived and interpreted with consideration to the nonuniform neural sampling operation of the auditory nerve. These ideas are used to rigorously initiate the concepts of sharpness and blur in auditory imaging, auditory aberrations, and auditory depth of field. In parallel, ideas from communication theory are used to show that the organ of Corti functions as a multichannel phase-locked loop (PLL) that constitutes the point of entry for auditory phase locking and hence conserves the signal coherence. It provides an anchor for a dual coherent and noncoherent auditory detection in the auditory brain that culminates in auditory accommodation. Implications on hearing impairments are discussed as well.Comment: 603 pages, 131 figures, 13 tables, 1570 reference

    Biomedical Sensing and Imaging

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    This book mainly deals with recent advances in biomedical sensing and imaging. More recently, wearable/smart biosensors and devices, which facilitate diagnostics in a non-clinical setting, have become a hot topic. Combined with machine learning and artificial intelligence, they could revolutionize the biomedical diagnostic field. The aim of this book is to provide a research forum in biomedical sensing and imaging and extend the scientific frontier of this very important and significant biomedical endeavor
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