EMD-based time-frequency analysis methods of audio signals

To ensure that any time series data is appropriately interpreted, it should be analyzed with proper signal processing tools. The most common analysis methods are kernel-based transforms, which use base functions and modifications to represent time series data. This work discusses an analysis of audio data and two of those transforms - the Fourier transform and the wavelet transform based on a priori assumptions about the signal\u27s linearity and stationarity. In audio engineering, these assumptions are invalid because the statistical parameters of most audio signals change with time and cannot be treated as an output of the LTI system. That is why recent approaches involve the decomposition of a signal into different modes in a data-dependent and adaptive way, which may provide advantages over kernel-based transforms. Such tools include empirical mode decomposition-based methods and Holo-Hilbert Spectral Analysis. Simulations were performed with speech signal for kernel-based and data-dependent decomposition methods, which revealed that evaluated decomposition methods are promising approaches to analyzing nonstationary and nonlinear audio data

Intelligent strategies for mobile robotics in laboratory automation

In this thesis a new intelligent framework is presented for the mobile robots in laboratory automation, which includes: a new multi-floor indoor navigation method is presented and an intelligent multi-floor path planning is proposed; a new signal filtering method is presented for the robots to forecast their indoor coordinates; a new human feature based strategy is proposed for the robot-human smart collision avoidance; a new robot power forecasting method is proposed to decide a distributed transportation task; a new blind approach is presented for the arm manipulations for the robots

Spatiotemporal brain dynamics induced by propofol and ketamine in humans

Human brain dynamics are radically altered under the influence of anaesthetics. However, despite their widespread clinical use, the whole-brain mechanisms by which anaesthetics alter consciousness are still not fully understood and clinical translation of existing insights is limited. This thesis presents several lines of investigation aimed to improve our understanding of spatiotemporal brain states under the anaesthetics propofol and ketamine. First, slow-wave activity saturation (SWAS) was studied across the brain and in relation to existing depth of anaesthesia markers. Local propofol concentration needed to achieve SWAS in healthy volunteers correlated with GABA-A receptor density (Spearman ρ=-0.69, P=0.0018), providing more evidence for the importance of the neurophysiological state of SWAS. The average Bispectral Index at SWAS across volunteers was 49±4, but its value varied significantly over time. Second, relevant cortico-cardiac interactions were studied. A slow propofol infusion increased heart rate in a dose-dependent manner (increase of +4.2±1.5 bpm / (μg ml-1), P<0.001). Individual cortical slow waves were coupled to the heartbeat (P<0.001), with heartbeat incidence peaking about 450ms before slow-wave onset. A ketamine case study showed decreased amplitude of heartbeat-evoked potentials, suggesting impaired interoceptive signalling may have a part in dissociative phenomenology. Third, novel methodology was developed, validated, and applied throughout the thesis. Iterated Masking Empirical Mode Decomposition was used to identify three types of low-frequency propofol waves with different spatiotemporal maps and dose-responses. Hidden Markov Modelling of propofol showed a shift to anterior alpha states and a reduced switching rate (P<0.01); with ketamine states exhibiting low alpha power and decreased connectivity became more prominent (P<0.001). Fourth, the potential of translating electroencephalographic markers from high- to low- density montages was studied. Posterior montages were best at capturing the reduced state switching under propofol. A patient study of antidepressant ketamine treatment demonstrated reduced temporal lobe alpha and theta power were associated with dissociation (P=0.0109)