Gender identification through handwriting: An online approach

The present study was designed to identify writer's gender trough online handwriting and drawing analysis. Two groups - one of 126 males (mean age 24.65, SD=2.45) and the other of 114 females (mean age 24.51, SD=2.50) participants were recruited in the experiment. They were asked to perform seven writing and drawing tasks utilizing a digitizing tablet and a special writing device. Seventeen writing features grouped into five categories have been considered. The experiment's results show that the set of considered features enable to discriminate between male and female writers investigating their performance while copying a house drawing (task 2), writing words in capital letters (task 3) and writing a complete sentence in cursive letters (task 7), in particular focusing on Ductus (number of strokes) and Time categories of writing features

Extending the Predictive Capabilities of Hand-oriented Behavioural Biometric Systems

The discipline of biometrics may be broadly defined as the study of using metrics related to human characteristics as a basis for individual identification and authentication, and many approaches have been implemented in recent years for many different scenarios. A sub-section of biometrics, specifically known as soft biometrics, has also been developing rapidly, which focuses on the additional use of information which is characteristic of a user but not unique to one person, examples including subject age or gender. Other than its established value in identification and authentication tasks, such useful user information can also be predicted within soft biometrics modalities. Furthermore, some most recent investigations have demonstrated a demand for utilising these biometric modalities to extract even higher-level user information, such as a subject\textsc{\char13}s mental or emotional state. The study reported in this thesis will focus on investigating two soft biometrics modalities, namely keystroke dynamics and handwriting biometrics (both examples of hand-based biometrics, but with differing characteristics). The study primarily investigates the extent to which these modalities can be used to predict human emotions. A rigorously designed data capture protocol is described and a large and entirely new database is thereby collected, significantly expanding the scale of the databases available for this type of study compared to those reported in the literature. A systematic study of the predictive performance achievable using the data acquired is presented. The core analysis of this study, which is to further explore of the predictive capability of both handwriting and keystroke data, confirm that both modalities have the capability for predicting higher level mental states of individuals. This study also presents the implementation of detailed experiments to investigate in detail some key issues (such as amount of data available, availability of different feature types, and the way ground truth labelling is established) which can enhance the robustness of this higher level state prediction technique

Functional Magnetic Resonance Imaging

"Functional Magnetic Resonance Imaging - Advanced Neuroimaging Applications" is a concise book on applied methods of fMRI used in assessment of cognitive functions in brain and neuropsychological evaluation using motor-sensory activities, language, orthographic disabilities in children. The book will serve the purpose of applied neuropsychological evaluation methods in neuropsychological research projects, as well as relatively experienced psychologists and neuroscientists. Chapters are arranged in the order of basic concepts of fMRI and physiological basis of fMRI after event-related stimulus in first two chapters followed by new concepts of fMRI applied in constraint-induced movement therapy; reliability analysis; refractory SMA epilepsy; consciousness states; rule-guided behavioral analysis; orthographic frequency neighbor analysis for phonological activation; and quantitative multimodal spectroscopic fMRI to evaluate different neuropsychological states

Non-spurious correlations between genetic and linguistic diversities in the context of human evolution

This thesis concerns human diversity, arguing that it represents not just some form of noise, which must be filtered out in order to reach a deeper explanatory level, but the engine of human and language evolution, metaphorically put, the best gift Nature has made to us. This diversity must be understood in the context of (and must shape) human evolution, of which the Recent Out-of-Africa with Replacement model (ROA) is currently regarded, especially outside palaeoanthropology, as a true theory. It is argued, using data from palaeoanthropology, human population genetics, ancient DNA studies and primatology, that this model must be, at least, amended, and most probably, rejected, and its alternatives must be based on the concept of reticulation. The relationships between the genetic and linguistic diversities is complex, including interindividual genetic and behavioural differences (behaviour genetics) and inter-population differences due to common demographic, geographic and historic factors (spurious correlations), used to study (pre)historical processes. It is proposed that there also exist nonspurious correlations between genetic and linguistic diversities, due to genetic variants which can bias the process of language change, so that the probabilities of alternative linguistic states are altered. The particular hypothesis (formulated with Prof. D. R. Ladd) of a causal relationship between two human genes and one linguistic typological feature is supported by the statistical analysis of a vast database of 983 genetic variants and 26 linguistic features in 49 Old World populations, controlling for geography and known linguistic history. The general theory of non-spurious correlations between genetic and linguistic diversities is developed and its consequences and predictions analyzed. It will very probably profoundly impact our understanding of human diversity and will offer a firm footing for theories of language evolution and change. More specifically, through such a mechanism, gradual, accretionary models of language evolution are a natural consequence of post-ROA human evolutionary models. The unravellings of causal effects of inter-population genetic differences on linguistic states, mediated by complex processes of cultural evolution (biased iterated learning), will represent a major advance in our understanding of the relationship between cultural and genetic diversities, and will allow a better appreciation of this most fundamental and supremely valuable characteristic of humanity - its intrinsic diversity