High accuracy discrimination of Parkinson's disease participants from healthy controls using smartphones

The aim of this study is to accurately distinguish Parkinson's disease (PD) participants from healthy controls using self-administered tests of gait and postural sway. Using consumer-grade smartphones with in-built accelerometers, we objectively measure and quantify key movement severity symptoms of Parkinson's disease. Specifically, we record tri-axial accelerations, and extract a range of different features based on the time and frequency-domain properties of the acceleration time series. The features quantify key characteristics of the acceleration time series, and enhance the underlying differences in the gait and postural sway accelerations between PD participants and controls. Using a random forest classifier, we demonstrate an average sensitivity of 98.5% and average specificity of 97.5% in discriminating PD participants from controls. © 2014 IEEE.

Analysis of Wiener-Hammerstein equalizer for downlink LTE system

We propose a Wiener-Hammerstein (W-H) channel estimation algorithm for Long-Term Evolution (LTE) systems. The LTE standard provides known data as pilot symbols and exploits them through coherent detection to improve system performance. These drivers are placed in a hybrid way to cover up both time and frequency domain. Our aim is to adapt the W-H equalizer (W-H/E) to LTE standard for compensation of both linear and nonlinear effects induced by power amplifiers and multipath channels. We evaluate the performance of the W-H/E for a Downlink LTE system in terms of BLER, EVM and Throughput versus SNR. Afterwards, we compare the results with a traditional Least-Mean Square (LMS) equalizer. It is shown that W-H/E can significantly reduce both linear and nonlinear distortions compared to LMS and improve LTE Downlink system performance.

Numerically optimized implementations, mitigation and simulations of polarisation mode dispersion in real-time transmission systems

The aim of this thesis is to present numerical investigations of the polarisation mode dispersion (PMD) effect. Outstanding issues on the side of the numerical implementations of PMD are resolved and the proposed methods are further optimized for computational efficiency and physical accuracy. Methods for the mitigation of the PMD effect are taken into account and simulations of transmission system with added PMD are presented. The basic outline of the work focusing on PMD can be divided as follows. At first the widely-used coarse-step method for simulating the PMD phenomenon as well as a method derived from the Manakov-PMD equation are implemented and investigated separately through the distribution of a state of polarisation on the Poincaré sphere, and the evolution of the dispersion of a signal. Next these two methods are statistically examined and compared to well-known analytical models of the probability distribution function (PDF) and the autocorrelation function (ACF) of the PMD phenomenon. Important optimisations are achieved, for each of the aforementioned implementations in the computational level. In addition the ACF of the coarse-step method is considered separately, based on the result which indicates that the numerically produced ACF, exaggerates the value of the correlation between different frequencies. Moreover the mitigation of the PMD phenomenon is considered, in the form of numerically implementing Low-PMD spun fibres. Finally, all the above are combined in simulations that demonstrate the impact of the PMD on the quality factor (Q=factor) of different transmission systems. For this a numerical solver based on the coupled nonlinear Schrödinger equation is created which is otherwise tested against the most important transmission impairments in the early chapters of this thesis.

Formant-frequency variation and its effects on across-formant grouping in speech perception

How speech is separated perceptually from other speech remains poorly understood. In a series of experiments, perceptual organisation was probed by presenting three-formant (F1+F2+F3) analogues of target sentences dichotically, together with a competitor for F2 (F2C), or for F2+F3, which listeners must reject to optimise recognition. To control for energetic masking, the competitor was always presented in the opposite ear to the corresponding target formant(s). Sine-wave speech was used initially, and different versions of F2C were derived from F2 using separate manipulations of its amplitude and frequency contours. F2Cs with time-varying frequency contours were highly effective competitors, whatever their amplitude characteristics, whereas constant-frequency F2Cs were ineffective. Subsequent studies used synthetic-formant speech to explore the effects of manipulating the rate and depth of formant-frequency change in the competitor. Competitor efficacy was not tuned to the rate of formant-frequency variation in the target sentences; rather, the reduction in intelligibility increased with competitor rate relative to the rate for the target sentences. Therefore, differences in speech rate may not be a useful cue for separating the speech of concurrent talkers. Effects of competitors whose depth of formant-frequency variation was scaled by a range of factors were explored using competitors derived either by inverting the frequency contour of F2 about its geometric mean (plausibly speech-like pattern) or by using a regular and arbitrary frequency contour (triangle wave, not plausibly speech-like) matched to the average rate and depth of variation for the inverted F2C. Competitor efficacy depended on the overall depth of frequency variation, not depth relative to that for the other formants. Furthermore, the triangle-wave competitors were as effective as their more speech-like counterparts. Overall, the results suggest that formant-frequency variation is critical for the across-frequency grouping of formants but that this grouping does not depend on speech-specific constraints.

Formant-frequency variation and its effects on across-formant grouping in speech perception

How speech is separated perceptually from other speech remains poorly understood. In a series of experiments, perceptual organisation was probed by presenting three-formant (F1+F2+F3) analogues of target sentences dichotically, together with a competitor for F2 (F2C), or for F2+F3, which listeners must reject to optimise recognition. To control for energetic masking, the competitor was always presented in the opposite ear to the corresponding target formant(s). Sine-wave speech was used initially, and different versions of F2C were derived from F2 using separate manipulations of its amplitude and frequency contours. F2Cs with time-varying frequency contours were highly effective competitors, whatever their amplitude characteristics, whereas constant-frequency F2Cs were ineffective. Subsequent studies used synthetic-formant speech to explore the effects of manipulating the rate and depth of formant-frequency change in the competitor. Competitor efficacy was not tuned to the rate of formant-frequency variation in the target sentences; rather, the reduction in intelligibility increased with competitor rate relative to the rate for the target sentences. Therefore, differences in speech rate may not be a useful cue for separating the speech of concurrent talkers. Effects of competitors whose depth of formant-frequency variation was scaled by a range of factors were explored using competitors derived either by inverting the frequency contour of F2 about its geometric mean (plausibly speech-like pattern) or by using a regular and arbitrary frequency contour (triangle wave, not plausibly speech-like) matched to the average rate and depth of variation for the inverted F2C. Competitor efficacy depended on the overall depth of frequency variation, not depth relative to that for the other formants. Furthermore, the triangle-wave competitors were as effective as their more speech-like counterparts. Overall, the results suggest that formant-frequency variation is critical for the across-frequency grouping of formants but that this grouping does not depend on speech-specific constraints. © Springer Science+Business Media New York 2013.

Slow-phase onset influence on waveform identification and foveation time measure in congenital nystagmus

Congenital nystagmus (CN) is an ocular-motor disorder characterised by involuntary, conjugated ocular oscillations and its pathogenesis is still under investigation. This kind of nystagmus is termed congenital (or infantile) since it could be present at birth or it can arise in the first months of life. Most of CN patients show a considerable decrease of their visual acuity: image fixation on the retina is disturbed by nystagmus continuous oscillations, mainly horizontal. However, the image of a given target can still be stable during short periods in which eye velocity slows down while the target image is placed onto the fovea (called foveation intervals). To quantify the extent of nystagmus, eye movement recording are routinely employed, allowing physicians to extract and analyse nystagmus main features such as waveform shape, amplitude and frequency. Using eye movement recording, it is also possible to compute estimated visual acuity predictors: analytical functions which estimates expected visual acuity using signal features such as foveation time and foveation position variability. Use of those functions extend the information from typical visual acuity measurement (e.g. Landolt C test) and could be a support for therapy planning or monitoring. This study focuses on detection of CN patients' waveform type and on foveation time measure. Specifically, it proposes a robust method to recognize cycles corresponding to the specific CN waveform in the eye movement pattern and, for those cycles, evaluate the exact signal tracts in which a subject foveates. About 40 eyemovement recordings, either infrared-oculographic or electrooculographic, were acquired from 16 CN subjects. Results suggest that the use of an adaptive threshold applied to the eye velocity signal could improve the estimation of slow phase start point. This can enhance foveation time computing and reduce influence of repositioning saccades and data noise on the waveform type identification.