Throughput and Collision Analysis of Multi-Channel Multi-Stage Spectrum Sensing Algorithms

Multi-stage sensing is a novel concept that refers to a general class of spectrum sensing algorithms that divide the sensing process into a number of sequential stages. The number of sensing stages and the sensing technique per stage can be used to optimize performance with respect to secondary user throughput and the collision probability between primary and secondary users. So far, the impact of multi-stage sensing on network throughput and collision probability for a realistic network model is relatively unexplored. Therefore, we present the first analytical framework which enables performance evaluation of different multi-channel multi-stage spectrum sensing algorithms for Opportunistic Spectrum Access networks. The contribution of our work lies in studying the effect of the following parameters on performance: number of sensing stages, physical layer sensing techniques and durations per each stage, single and parallel channel sensing and access, number of available channels, primary and secondary user traffic, buffering of incoming secondary user traffic, as well as MAC layer sensing algorithms. Analyzed performance metrics include the average secondary user throughput and the average collision probability between primary and secondary users. Our results show that when the probability of primary user mis-detection is constrained, the performance of multi-stage sensing is, in most cases, superior to the single stage sensing counterpart. Besides, prolonged channel observation at the first stage of sensing decreases the collision probability considerably, while keeping the throughput at an acceptable level. Finally, in realistic primary user traffic scenarios, using two stages of sensing provides a good balance between secondary users throughput and collision probability while meeting successful detection constraints subjected by Opportunistic Spectrum Access communication

Intra-Cortical Microelectrode Arrays for Neuro-Interfacing

Neuro-engineering is an emerging multi-disciplinary domain which investigates the electrophysiological activities of the nervous system. It provides procedures and techniques to explore, analyze and characterize the functions of the different components comprising the nervous system. Neuro-engineering is not limited to research applications; it is employed in developing unconventional therapeutic techniques for treating different neurological disorders and restoring lost sensory or motor functions. Microelectrodes are principal elements in functional electric stimulation (FES) systems used in electrophysiological procedures. They are used in establishing an interface with the individual neurons or in clusters to record activities and communications, as well as modulate neuron behaviour through stimulation. Microelectrode technologies progressed through several modifications and innovations to improve their functionality and usability. However, conventional electrode technologies are open to further development, and advancement in microelectrodes technology will progressively meliorate the neuro-interfacing and electrotherapeutic techniques. This research introduced design methodology and fabrication processes for intra-cortical microelectrodes capable of befitting a wide range of design requirements and applications. The design process was employed in developing and implementing an ensemble of intra-cortical microelectrodes customized for different neuro-interfacing applications. The proposed designs presented several innovations and novelties. The research addressed practical considerations including assembly and interconnection to external circuitry. The research was concluded by exhibiting the Waterloo Array which is a high channel count flexible 3-D neuro-interfacing array. Finally, the dissertation was concluded by demonstrating the characterization, in vitro and acute in vivo testing results of the Waterloo Array. The implemented electrodes were tested and benchmarked against commercial equivalents and the results manifested improvement in the electrode performance compared to conventional electrodes. Electrode testing and evaluation were conducted in the Krembil Neuroscience Centre Research Lab (Toronto Western Hospital), and the Neurosciences & Mental Health Research Institute (the Sick Kids hospital). The research results and outcomes are currently being employed in developing chronic intra-cortical and electrocorticography (ECoG) electrode arrays for the epilepsy research and rodents nervous system investigations. The introduced electrode technologies will be used to develop customized designs for the clinical research labs collaborating with CIRFE Lab.1 yea

Design and Optimization Methodology of Sub-dermal Electroencephalography Dry Spike-Array Electrode

Monitoring bio-electric events is a common procedure, which provides medical data required in clinical and research applications. Electrophysiological measurements are applied in diagnosis as well as evaluation of the performance of different body organs and systems, e. g. the heart, muscles and the nervous system. Furthermore, it is staple feature in operation rooms and extensive care units. The performance of the recording system is affected by the tools and instrumentation used and the bio-electrode is a key-player in electrophysiology, hence, the improvements in the electrode recording technique will be directly reflected in the system?s performance in terms of the signal quality, recording duration as well as patient comfort. In this thesis, a design methodology for micro-spike array dry bio-electrodes is introduced. The purpose of this methodology is to meet the design specifications for portable long-term EEG recording and optimize the electrical performance of the electrodes by maximizing the electrode-skin contact surface area, while fulfilling design constraints including mechanical, physiological and economical limitations. This was followed by proposing a low cost fabrication technique to implement the electrodes. The proposed electrode design has a potential impact in enhancing the performance of the current recording systems, and also suits portable monitoring and long term recording devices. The design process was aided by using a software design and optimization tool, which was specifically created for this application. The application conditions added challenges to the electrode design in order to meet the required performance requirements. On the other hand, the required design specifications are not fulfilled in the current electrode technologies which are designed and customized only for short term clinical recordings. The electrode theory of application was verified using an experimental setup for an electrochemical cell, but the overall performance including measuring the electrode impedance is awaiting a clinical trial

Spatiotemporal Electrochemistry on Flexible Microelectrode Arrays: Progress Towards Smart Contact Lens Integration

We demonstrate a real-speed spatiotemporal electrochemical map showing both time- and position-varying concentration of an analyte in contact with a flexible microelectrode array. A polymer-based device of 11 μm in thickness comprising patterned gold metallisation on a polyimide substrate was fabricated, with eight in- dividually addressable working electrodes (diameter 30 μm) and an integrated counter electrode. We performed a repeated sequence of high-speed chronoamperometric measurements at each electrode and processed the data to generate a spatiotemporal concentration map, in which a number of fluid effects, including bulk flow, dif- fusive mixing and homogenisation of two miscible fluids of different concentration were observed. This device was fabricated using processes compatible with an existing smart contact lens platform, with a view to develop integrated sensors in future work. We believe this technique has significant potential in the field of electro- chemical smart contact lenses, both in introducing new functionality and in improving our ability to draw accurate and clinically-relevant conclusions from measurements made in the tear film

Author’s Declaration

I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis, including any required final revisions, as accepted by my examiners. I understand that my thesis may be made electronically available to the public

Traffic-Aware Multi-Channel Multi-Stage Spectrum Sensing Protocols for Dynamic Spectrum Access

In Dynamic Spectrum Access (DSA) networks, secondary users (SUs) scavenge for unused frequency spectrum by performing spectrum sensing. Multi-stage sensing is a novel concept that refers to a general class of DSA spectrum sensing algorithms that divide the sensing process into a number of sequential stages. The number of sensing stages and the sensing technique per stage can be used to optimize performance with respect to SU throughput, energy consumption per bit, and the probability of collision between licensed (primary) and SUs. In this work, we present the first analytical framework which enables performance evaluation of different multi-channel multi-stage spectrum sensing algorithms for DSA networks. The contribution of our work lies in studying the effect of the following parameters on performance: number of sensing stages, physical layer sensing technique and duration per stage, single and parallel channel sensing and access, number of available channels, primary user (PU) and SU traffic, as well as MAC layer sensing algorithms. Our results emphasize the fact that the performance of multi-stage sensing is superior to the single stage sensing counterpart, where the optimal number of sensing stages and sensing duration per stage depend on the network traffic.For DSA spectrum sensing algorithms in general, and multi-stage spectrum sensing algorithms in specific, DSA systems can assign PU resources to its subscribers more efficiently if knowledge of PU temporal statistics is available. In this work, we explore the benefit of incorporating PU traffic statistics in spectrum sensing algorithms. Moreover, we study the impact of PU traffic parameter estimation errors on algorithm performance. We extend our study to investigate the accuracy bounds on PU traffic parameter estimation. We present a mathematical analysis of the accuracy of estimating the mean PU duty cycle, and the PU mean off- and on-times, where the estimation accuracy is expressed in terms of the mean squared estimation error. The analysis applies for the traffic model assuming exponentially distributed PU off- and on-times. We derive the Cramer-Rao bounds on the estimation error of the mean PU duty cycle, and the mean PU off- and on-times. The bounds are derived for the case when perfect knowledge is assumed for one of the parameters, and the case where all parameters are jointly estimated. Besides, the impact of spectrum sensing errors on the estimation accuracy is studied analytically. Furthermore, we propose a number of estimators for the traffic parameters and quantify their estimation accuracy. Finally, we develop algorithms for the blind estimation of the traffic parameters based on the derived theoretical estimation accuracy expressions. We show that, for a fixed observation window length, the estimation error for all traffic parameters is lower bounded due to the correlation between the traffic samples, while on the other hand, the impact of spectrum sensing errors on the estimation error of the mean PU duty cycle can be eliminated by increasing the number of traffic samples

IEEE Transactions on Neural Systems and Rehabilitation Engineering: Vol. 21, No. 6, November 2013

1. High-Density Intracortical Microelectrode Arrays With Multiple Metallization Layers for Fine-Resolution Neuromonitoring and Neurostimulation / S.R.I. Gabran, et al. 2. Seizure Prediction Using Spike Rate of Intracranial EEG / Shufang Li, et al. 3. L1-Regularized Multiway Canonical Correlation Analysis for SSVEP-Based BCI/ Yu Zhang, et al. 4. The Component Structure of Event-Related Potentials in the P300 Speller Paradigm / Siri-Maria Kamp, Anthony R. Murphy, Emanuel Donchin 5. Automated Detection of Instantaneous Gait Events Using Time Frequency Analysis and Manifold Embedding / Min S.H. Aung, et al. 6. On the Construction of a a Skill-Based Wheelchair Navigation Profile / Cristina Urdiales, et al. 7. A System for Delivering Mechanical Stimulation and Robot-Assited Therapy to the Rat Whisker Pad During Facial Nerve Regeneration / James T. Heaton, et al. 8. Powered Hip Exoskkeletons Can Reduce the User\u27s Hip and Ankle Muscle Activations During Walking / Thommaso Lenzi, Maria Chiara Crroza, Sunil K. Agrawal 9. Real-Time Motor Unit Identification From High-Density Surface EMG / Vojko Glaser, Ales Holobar, Damjan Zazula 10. Assisting Versus Repelling Force-Feedback for Learning of a Line Following Task in a Wheelchair / Xi Chen, Sunil K. Agrawal etc

Comparative mechanical analysis of deep brain stimulation electrodes

Abstract The new field of neuro-prosthetics focuses on the design and implementation of neural prostheses to restore some of the lost neural functions. The electrode-tissue contacts remain one of the major obstacles of neural prostheses microstructure. Recently, Microelectrode fabrication techniques have been developed to have a long-term and stable interface with the brain. In this paper, a comparative analysis of finite element models (FEM) for several electrode layouts is conducted. FEM involves parametric and sensitivity analysis to show the effects of the different design parameters on the electrode mechanical performance. These parameters include electrode dimensions, geometry, and materials. The electrodes mechanical performance is evaluated with various analysis techniques including: linear buckling analysis, stationary analysis with axial and shear loading, and failure analysis for brittle and ductile materials. Finally, a novel figure of merit (FOM) is presented and dedicated to the various electrodes prototypes. The proposed designs take into account mechanical performance, fabrication cost, and cross sectional area of the electrode. The FOM provides important design insights to help the electrodes designers to select the best electrode design parameters that meet their design constraints