信道質量和服務質量（QoS）是無線體域網的兩個重要挑戰。本文旨在研究信道特性和在保證高吞吐率和低數據弛豫時間前提下探索低功耗WBAN系統策略。本論文的貢獻在於三個方面。首先研究人體信道（HBC）特性。作為IEEE標準802.15.6定義的三種PHY層之一，HBC已經作為體表傳感器通信媒介被廣泛研究。但是，HBC的詳細機理至今仍然不夠明朗，特別是對於那些采用了體內傳感器的應用更少人涉足。因此，我們為此專門預設四種應用場景，並在場景中測量實際信道特性。依據測量結果，我們觀測到數個影響信道質量的因素。其次，我們提出了一種專門針對WBAN的信道建模方法。該方法依賴於對人體組織的直接測量結果，並且此建模方法在建模過程中兼顧體表通信和體內通信。該建模方法包括兩個階段，第一階段是構建人體各部分的子模型，在第二階段調用先前構建之子模型並依賴信號衰減特性來構造上層模型。最終得到的模型包含兩個自變量：頻率和信道長度，從而可應用此模型同時預測不同頻率和不同長度條件下的信道特性。在設計的實驗中，結果表明該模型具有良好的精度，在10 kHz到60 MHz的頻率範圍內，最差的誤差為2.5 dB。除此之外，我們還在一個演示系統中對信道進行了測試，尤其是誤碼率（BER）和信號衰減情形。該測試結果也顯示出該模型所具有的良好預測性。第三，我們提出了一種關註QoS的WBAN系統優化方法。在IEEE標準中定義了數種不同存取模式（Access mode）和存取方式（Access method）。為了提高功率效率，我們著重研究了數據壓縮對系統總功率的影響，另外還對系統吞吐率建立了分析模型。仿真結果顯示，在一定條件下，數據壓縮對功耗降低具有良好功效，另外采用較高數據傳輸速率會對功耗存在改進作用。當數據壓縮模塊的壓縮率超過2倍，而功耗低於收發器的40%時，插入數據壓縮模塊可以確保整個系統消耗更低能源。 / Channel loss and maintaining the Quality of Service (QoS) are two of the major challenges in realizing an effective Wireless Body Area Network (WBAN). This thesis studies the body channel characteristics and proposes a methodology to improve energy efficiency for an entire WBAN system to achieve high throughput and low data latency. Three main contributions are made in this thesis. Firstly, we focus on human body channel (HBC). HBC, as a possible PHY layer for IEEE standards 802.15.6, has been found useful in networking on-body sensors. However, the HBC channel dynamics is not well understood and this is particularly the case when transceivers implanted inside a human body are involved. To this end, channel measurements were performed on real subjects under four different scenarios so that factors affecting channel quality could be identified. Secondly, a channel modelling methodology is proposed for body area network that takes into account the body structure and the dielectric properties of human tissues; this represents the first modelling effort to cover both in-body and on-body communications in vivo. The proposed modelling method composes of two phases: sub-model construction and top-level model construction. The constructed model is a function of two variables, frequency and channel length, enabling channel impedance prediction with respect to either frequency or channel length. Meanwhile, experimental results show that good model accuracy, a maximum error of 2.5 dB, can be achieved in frequencies range from 10 kHz to 60 MHz. In this endeavor, a modified HBC development system was used to measure bit error rate (BER) and signal attenuation during transmission. The measurements show a good match against simulation results and the channel model. Thirdly, a power optimization technique is proposed for the WBAN. The latest IEEE standard 802.15.6 defines several access modes and access methods together with new power management schemes and frame structures. To improve the power efficiency of a body area network, the merit of having data compression was investigated. For this purpose, an analytical model was developed to evaluate the power efficiency of a BAN system. Simulation results show that good power efficiency can be achieved by employing data compression. It is evident that higher data rate can also help improve energy efficiency. When the compression factor is larger than 2, better energy efficiency can be guaranteed by introducing a data processing unit in a sensor node as long as its power consumption is limited to 40% of that of the transceiver unit. / Detailed summary in vernacular field only. / Ai, Yanqing. / Thesis (Ph.D.) Chinese University of Hong Kong, 2014. / Includes bibliographical references (leaves 126-135). / Abstracts also in Chinese.

Traditionally, electrical brain-computer interfaces (BCIs) have required the assembly of two separate components: electrodes for interfacing with tissue and electronics for signal acquisition and stimulation. Furthermore, these electronics required cabled connections to workstations for data processing and control. Efforts to overcome these limitations have made significant progress in the last decade. Now, there are in vivo validated monolithic electrophysiological BCI devices, exemplified by the Neuropixels, that integrate the two components onto a single platform. At the same time, a new generation of fully wireless BCI devices that reside entirely under the skin has been developed. Despite these advancements, the current state-of-the-art BCIs have yet to overcome both challenges simultaneously. Multi-channel, high-bandwidth monolithic BCIs still require percutaneous wired connections, whereas wireless BCIs rely on the assembly of discrete components that result in bulky form factors. The next generation of BCIs calls for a new paradigm that integrates electrodes and electronics into a miniaturized form factor while supporting a fully wireless operation. This thesis contributes to the collaborative effort that presents such a paradigm through the development of a wireless, battery-free micro-electrocorticography (μECoG) device that monolithically integrates electrodes, signal processing, data telemetry, and powering onto a single complementary metal-oxide-semiconductor (CMOS) substrate. The device contains 65,536 recording and 16,384 stimulation channels, from which a programmable subset of up to 1024 channels can berecorded at a given time. Implemented in a mechanically flexible, 50-μm-thick form factor with a total volume of only 7.2 mm³, the device is implanted entirely in the subdural space and conforms to the contour of the cortical tissue surface. A custom "relay station" provides wireless powering and bi-directional communication to the implant from outside the body. The system was validated through a series of proof-of-concept in vivo recordings from different cortical regions of a pig and non-human primates, reliably decoding brain signals at high spatiotemporal resolution. By using a unique, fully integrated architecture, the BCI developed in this work achieves orders-of-magnitude improvements in volumetric efficiency and channel count over existing approaches, setting a milestone for the next generation of BCI devices.

M. Tech. Information Networks / This dissertation reports on a prototype implementation of an architecture that seamlessly integrates Wireless Body Area Networks with Web services for ubiquitous healthcare service provisioning. The prototype ubiquitous monitoring system proactively collects body physiological signals of remote patients to recommend diagnostic services. The technologies that are based upon Wireless Body Area Networks and Web services can provide ubiquitous accessibility to variety of services by allowing distributed healthcare resources to be massively reused. This contributes to improving quality of healthcare services and shields individuals from physically moving to locations where healthcare services are provided, except in a critical situation. In addition, the technology can reduce costs of healthcare services by allowing individuals to remotely access services to support their healthcare. Especially our system is designed for ubiquitous monitoring of elderly and patients in recovery (or rehabilitation). The Wireless Body Area Networks - Web services architecture is at crossroad of embedded engineering of hardware, software and networking protocols. Testing of the prototype was carried out on enthusiastic volunteers and it has shown to be an efficient, reliable and support state-of-art service provisioning of ubiquitous healthcare monitoring in health sector.

This research addresses the need for increased interoperability between the varied access control systems in use today, and for a secure means of providing access to remote physical devices over untrusted networks. The Universal Physical Access Control System (UPACS) is an encryption-enabled security protocol that provides a standard customizable device control mechanism that can be used to control the behavior of a wide variety of physical devices, and provide users the ability to securely access those physical devices over untrusted networks. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2015. / FAU Electronic Theses and Dissertations Collection