Studies on Spinal Fusion from Computational Modelling to ‘Smart’ Implants

Low back pain, the worldwide leading cause of disability, is commonly treated with lumbar interbody fusion surgery to address degeneration, instability, deformity, and trauma of the spine. Following fusion surgery, nearly 20% experience complications requiring reoperation while 1 in 3 do not experience a meaningful improvement in pain. Implant subsidence and pseudarthrosis in particular present a multifaceted challenge in the management of a patient’s painful symptoms. Given the diversity of fusion approaches, materials, and instrumentation, further inputs are required across the treatment spectrum to prevent and manage complications. This thesis comprises biomechanical studies on lumbar spinal fusion that provide new insights into spinal fusion surgery from preoperative planning to postoperative monitoring. A computational model, using the finite element method, is developed to quantify the biomechanical impact of temporal ossification on the spine, examining how the fusion mass stiffness affects loads on the implant and subsequent subsidence risk, while bony growth into the endplates affects load-distribution among the surrounding spinal structures. The computational modelling approach is extended to provide biomechanical inputs to surgical decisions regarding posterior fixation. Where a patient is not clinically pre-disposed to subsidence or pseudarthrosis, the results suggest unilateral fixation is a more economical choice than bilateral fixation to stabilise the joint. While finite element modelling can inform pre-surgical planning, effective postoperative monitoring currently remains a clinical challenge. Periodic radiological follow-up to assess bony fusion is subjective and unreliable. This thesis describes the development of a ‘smart’ interbody cage capable of taking direct measurements from the implant for monitoring fusion progression and complication risk. Biomechanical testing of the ‘smart’ implant demonstrated its ability to distinguish between graft and endplate stiffness states. The device is prepared for wireless actualisation by investigating sensor optimisation and telemetry. The results show that near-field communication is a feasible approach for wireless power and data transfer in this setting, notwithstanding further architectural optimisation required, while a combination of strain and pressure sensors will be more mechanically and clinically informative. Further work in computational modelling of the spine and ‘smart’ implants will enable personalised healthcare for low back pain, and the results presented in this thesis are a step in this direction

A Study on Three Dimensional Spatial Scattering Modulation Systems

With an explosive growth of data traffic demand, the researchers of the mobile communication era forecast that the traffic volume will have a 1000x increase in the forthcoming beyond fifth generation (B5G) network. To satisfy the growing traffic demand, the three-dimensional (3-D) multiple-input-and-multiple-output (MIMO) system is considered as a key technology to enhance spectrum efficiency (SE), which explores degrees of freedom in both the vertical and the horizontal dimensions. Combined with 3-D MIMO technology, index modulation (IM) is proposed to improve both energy efficiency (EE) and SE in the B5G era. Existing IM technologies can be categorized according to the domain in which the additional IM bits are modulated, e.g., the spatial-domain IM, the frequency-domain IM and the beamspace-domain IM etc. As one of the mainstream IM techniques, spatial scattering modulation (SSM) is proposed, which works in the beamspace-domain. For SSM systems, the information bits are denoted by the distinguishable signal scattering paths and the modulated symbols. Therein, two information bit streams are transmitted simultaneously by selections of modulated symbols and scattering paths. However, the existing papers only discuss two-dimensional (2-D) SSM systems. The 2-D SSM system applies linear antenna arrays, which only take the azimuth angles to recognise the direction of scattering paths. Therefore, to take the full advantage of the beamspace-domain resources, this thesis mainly focuses on the 3-D SSM system design and the performance evaluation. Firstly, a novel 3-D SSM system is designed. For the 3-D SSM system, besides the azimuth angles of arrival (AoA) and angles of departure (AoD), the elevation AoA and AoD are considered. Then the optimum detection algorithm is obtained, and the closed-form union upper bound expression on average bit error probability (ABEP) is derived. Moreover, the system performance is evaluated under a typical indoor environment. Numerical results indicate that the novel 3-D SSM system outperforms the conventional 2-D SSM system, which reduces the ABEP by 10 times with the same signal-to-noise ratio (SNR) level under the typical indoor environment. Secondly, for the system equipped with large-scale antenna arrays, hybrid beamforming schemes with several RF-chains have attracted more attention. To further explore the throughput of the 3-D SSM system, a generalised 3-D SSM system is proposed, which generates several RF-chains in a transmission time slot to convey modulated symbols. A system model of generalised 3-D SSM is proposed at first. Then an optimum detection algorithm is designed. Meanwhile, a closed-form expression of the ABEP is also derived and validated by Monte-Carlo simulation. For the performance evaluation, three stochastic propagation environments with randomly distributed scatterers are adopted. The results reveal that the generalised 3-D SSM system has better ABEP performance compared with the system with a single RF-chain. Considering different propagation environments, the SSM system has better ABEP performance under the statical propagation environments than the stochastic propagation environments. Thirdly, to reduce the hardware and computational complexities, two optimisation schemes are proposed for the generalised 3-D SSM systems. The 2-D fast Fourier transform (FFT) based transceivers are designed to improve the hardware friendliness, which replace the analogue phase shift networks by the multi-bit phase shifter networks. To reduce the computational complexity of the optimum detection algorithm, a low-complexity detection scheme is designed based on the linear minimum mean square error (MMSE) algorithm. Meanwhile, to quickly evaluate, the asymptotic ABEP performance and the diversity gain of the generalised 3-D SSM system are obtained

Hierarchical colour-shift-keying aided layered video streaming for the visible light downlink

Colour-shift keying (CSK) constitutes an important modulation scheme conceived for the visible light communications (VLC). The signal constellation of CSK relies on three different-color light sources invoked for information transmission. The CSK constellation has been optimized for minimizing the bit error rate, but no effort has been invested in investigating the feasibility of CSK aided unequal error protection (UEP) schemes conceived for video sources. Hence, in this treatise, we conceive a hierarchical CSK (HCSK) modulation scheme based on the traditional CSK, which is capable of generating interdependent layers of signals having different error probability, which can be readily reconfigured by changing its parameters. Furthermore, we conceived an HCSK design example for transmitting scalable video sources with the aid of a recursive systematic convolutional (RSC) code. An optimization method is conceived for enhancing the UEP and for improving the quality of the received video. Our simulation results show that the proposed optimized-UEP 16-HCSK-RSC system outperforms the traditional equal error protection scheme by ~ 1.7 dB of optical SNR at a peak signal-to-noise ratio of 37 dB, while optical SNR savings of up to 6.5 dB are attained at a lower PSNR of 36 dB

Gesture recognition with application in music arrangement

This thesis studies the interaction with music synthesis systems using hand gestures. Traditionally users of such systems were limited to input devices such as buttons, pedals, faders, and joysticks. The use of gestures allows the user to interact with the system in a more intuitive way. Without the constraint of input devices, the user can simultaneously control more elements within the music composition, thus increasing the level of the system's responsiveness to the musician's creative thoughts. A working system of this concept is implemented, employing computer vision and machine intelligence techniques to recognise the user's gestures.Dissertation (MSc)--University of Pretoria, 2006.Computer ScienceMScunrestricte

A Survey of Positioning Systems Using Visible LED Lights

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.As Global Positioning System (GPS) cannot provide satisfying performance in indoor environments, indoor positioning technology, which utilizes indoor wireless signals instead of GPS signals, has grown rapidly in recent years. Meanwhile, visible light communication (VLC) using light devices such as light emitting diodes (LEDs) has been deemed to be a promising candidate in the heterogeneous wireless networks that may collaborate with radio frequencies (RF) wireless networks. In particular, light-fidelity has a great potential for deployment in future indoor environments because of its high throughput and security advantages. This paper provides a comprehensive study of a novel positioning technology based on visible white LED lights, which has attracted much attention from both academia and industry. The essential characteristics and principles of this system are deeply discussed, and relevant positioning algorithms and designs are classified and elaborated. This paper undertakes a thorough investigation into current LED-based indoor positioning systems and compares their performance through many aspects, such as test environment, accuracy, and cost. It presents indoor hybrid positioning systems among VLC and other systems (e.g., inertial sensors and RF systems). We also review and classify outdoor VLC positioning applications for the first time. Finally, this paper surveys major advances as well as open issues, challenges, and future research directions in VLC positioning systems.Peer reviewe

Advanced signal processing solutions for ATR and spectrum sharing in distributed radar systems

Previously held under moratorium from 11 September 2017 until 16 February 2022This Thesis presents advanced signal processing solutions for Automatic Target Recognition (ATR) operations and for spectrum sharing in distributed radar systems. Two Synthetic Aperture Radar (SAR) ATR algorithms are described for full- and single-polarimetric images, and tested on the GOTCHA and the MSTAR datasets. The first one exploits the Krogager polarimetric decomposition in order to enhance peculiar scattering mechanisms from manmade targets, used in combination with the pseudo-Zernike image moments. The second algorithm employs the Krawtchouk image moments, that, being discrete defined, provide better representations of targets’ details. The proposed image moments based framework can be extended to the availability of several images from multiple sensors through the implementation of a simple fusion rule. A model-based micro-Doppler algorithm is developed for the identification of helicopters. The approach relies on the proposed sparse representation of the signal scattered from the helicopter’s rotor and received by the radar. Such a sparse representation is obtained through the application of a greedy sparse recovery framework, with the goal of estimating the number, the length and the rotation speed of the blades, parameters that are peculiar for each helicopter’s model. The algorithm is extended to deal with the identification of multiple helicopters flying in formation that cannot be resolved in another domain. Moreover, a fusion rule is presented to integrate the results of the identification performed from several sensors in a distributed radar system. Tests performed both on simulated signals and on real signals acquired from a scale model of a helicopter, confirm the validity of the algorithm. Finally, a waveform design framework for joint radar-communication systems is presented. The waveform is composed by quasi-orthogonal chirp sub-carriers generated through the Fractional Fourier Transform (FrFT), with the aim of preserving the radar performance of a typical Linear Frequency Modulated (LFM) pulse while embedding data to be sent to a cooperative system. Techniques aimed at optimise the design parameters and mitigate the Inter-Carrier Interference (ICI) caused by the quasiorthogonality of the chirp sub-carriers are also described. The FrFT based waveform is extensively tested and compared with Orthogonal Frequency Division Multiplexing (OFDM) and LFM waveforms, in order to assess both its radar and communication performance.This Thesis presents advanced signal processing solutions for Automatic Target Recognition (ATR) operations and for spectrum sharing in distributed radar systems. Two Synthetic Aperture Radar (SAR) ATR algorithms are described for full- and single-polarimetric images, and tested on the GOTCHA and the MSTAR datasets. The first one exploits the Krogager polarimetric decomposition in order to enhance peculiar scattering mechanisms from manmade targets, used in combination with the pseudo-Zernike image moments. The second algorithm employs the Krawtchouk image moments, that, being discrete defined, provide better representations of targets’ details. The proposed image moments based framework can be extended to the availability of several images from multiple sensors through the implementation of a simple fusion rule. A model-based micro-Doppler algorithm is developed for the identification of helicopters. The approach relies on the proposed sparse representation of the signal scattered from the helicopter’s rotor and received by the radar. Such a sparse representation is obtained through the application of a greedy sparse recovery framework, with the goal of estimating the number, the length and the rotation speed of the blades, parameters that are peculiar for each helicopter’s model. The algorithm is extended to deal with the identification of multiple helicopters flying in formation that cannot be resolved in another domain. Moreover, a fusion rule is presented to integrate the results of the identification performed from several sensors in a distributed radar system. Tests performed both on simulated signals and on real signals acquired from a scale model of a helicopter, confirm the validity of the algorithm. Finally, a waveform design framework for joint radar-communication systems is presented. The waveform is composed by quasi-orthogonal chirp sub-carriers generated through the Fractional Fourier Transform (FrFT), with the aim of preserving the radar performance of a typical Linear Frequency Modulated (LFM) pulse while embedding data to be sent to a cooperative system. Techniques aimed at optimise the design parameters and mitigate the Inter-Carrier Interference (ICI) caused by the quasiorthogonality of the chirp sub-carriers are also described. The FrFT based waveform is extensively tested and compared with Orthogonal Frequency Division Multiplexing (OFDM) and LFM waveforms, in order to assess both its radar and communication performance

Integrated Data and Energy Communication Network: A Comprehensive Survey

OAPA In order to satisfy the power thirsty of communication devices in the imminent 5G era, wireless charging techniques have attracted much attention both from the academic and industrial communities. Although the inductive coupling and magnetic resonance based charging techniques are indeed capable of supplying energy in a wireless manner, they tend to restrict the freedom of movement. By contrast, RF signals are capable of supplying energy over distances, which are gradually inclining closer to our ultimate goal – charging anytime and anywhere. Furthermore, transmitters capable of emitting RF signals have been widely deployed, such as TV towers, cellular base stations and Wi-Fi access points. This communication infrastructure may indeed be employed also for wireless energy transfer (WET). Therefore, no extra investment in dedicated WET infrastructure is required. However, allowing RF signal based WET may impair the wireless information transfer (WIT) operating in the same spectrum. Hence, it is crucial to coordinate and balance WET and WIT for simultaneous wireless information and power transfer (SWIPT), which evolves to Integrated Data and Energy communication Networks (IDENs). To this end, a ubiquitous IDEN architecture is introduced by summarising its natural heterogeneity and by synthesising a diverse range of integrated WET and WIT scenarios. Then the inherent relationship between WET and WIT is revealed from an information theoretical perspective, which is followed by the critical appraisal of the hardware enabling techniques extracting energy from RF signals. Furthermore, the transceiver design, resource allocation and user scheduling as well as networking aspects are elaborated on. In a nutshell, this treatise can be used as a handbook for researchers and engineers, who are interested in enriching their knowledge base of IDENs and in putting this vision into practice

Cooperative Transmitter-Receiver Arrayed Communications

This thesis is concerned with array processing for wireless communications. In particular, cooperation between the transmitter and receiver or between systems is exploited to further improve the system performance. Based on this idea, three technical chapters are presented in this thesis. Initially in Chapter 1, an introduction including array processing, multiple-input multiple-output (MIMO) communication systems and the background of cognitive radio is presented. In Chapter 2, a novel approach for estimating the direction-of-departure (DOD) is proposed using the cooperative beamforming. This proposed approach is featured by its simplicity (beam rotation at the transmitter) and effectiveness (illustrated in terms of channel capacity). Chapter 3 is concerned with integration of spatio-temporal (ST) processing into an antenna array transmitter, given a joint transmitter-receiver system with ST processing at the receiver but spatial-only processing at the transmitter. The transmit ST processing further improves the system performance in convergence, mean-square error (MSE) and bit error rate (BER). In Chapter 4, a basic system structure for radio coexistence problem is proposed based on the concept of MIMO cognitive radio. Cooperation between the licensed radio and the cognitive radio is exploited. Optimisation of the sum channel capacity is considered as the criterion and it is solved using a multivariable water-filling algorithm. Finally, Chapter 5 concludes this thesis and gives suggestions for future work