Hand gesture recognition for human computer interaction : a comparative study of different image features

Hand gesture recognition for human computer interaction, being a natural way of human computer interaction, is an area of active research in computer vision and machine learning. This is an area with many different possible applications, giving users a simpler and more natural way to communicate with robots/systems interfaces, without the need for extra devices. So, the primary goal of gesture recognition research is to create systems, which can identify specific human gestures and use them to convey information or for device control. For that, vision-based hand gesture interfaces require fast and extremely robust hand detection, and gesture recognition in real time. In this study we try to identify hand features that, isolated, respond better in various situations in human-computer interaction. The extracted features are used to train a set of classifiers with the help of RapidMiner in order to find the best learner. A dataset with our own gesture vocabulary consisted of 10 gestures, recorded from 20 users was created for later processing. Experimental results show that the radial signature and the centroid distance are the features that when used separately obtain better results, with an accuracy of 91% and 90,1% respectively obtained with a Neural Network classifier. These to methods have also the advantage of being simple in terms of computational complexity, which make them good candidates for real-time hand gesture recognition.

Urothelial bladder cancer progression: lessons learned from the bench

Urothelial bladder carcinoma (UBC) is an intricate malignancy with a variable natural history and clinical behavior. Despite developments in diagnosis/prognosis refinement and treatment modalities, the recurrence rate is high, and progression from non-muscle to muscle invasive UBC commonly leads to metastasis. Moreover, patients with muscle-invasive or extra-vesical disease often fail the standard chemotherapy treatment, and overall survival rates are poor. Thus, UBC remains a challenge in the oncology field, representing an ideal candidate for research on biomarkers that could identify patients at increased risk of recurrence, progression, and chemo-refractoriness. However, progress toward personalized medicine has been hampered by the unique genetic complexity of UBC. Recent genome-wide expression and sequencing studies have brought new insights into its molecular features, pathogenesis and clinical diversity, revealing a landscape where classical pathology is intersected by the novel and heterogeneous molecular groups. Hence, it seems plausible to postulate that only an integrated signature of prognostic/predictive biomarkers inherent in different cancer hallmarks will reach clinical validation. In this review, we have summarized ours and others' research into novel putative biomarkers of progression and chemoresistance that encompass several hallmarks of cancer: tumor neovascularization, invasion and metastasis, and energy metabolism reprogramming of the tumor microenvironment.

Chemical features of Ganoderma polysaccharides with antioxidant, antitumor and antimicrobial activities

Review aricle

Systems biology approaches for the design of novel Saccharomyces cerevisiae winemaking strains for enhanced flavour compounds synthesis

Tese de Doutoramento em Biologia Ambiental e Molecular

Mesenchymal stem cells secretome as a modulator of the neurogenic niche: Basic insights and therapeutic opportunities

Neural stem cells (NSCs) and mesenchymal stem cells (MSCs) share few characteristics apart from self-renewal and multipotency. In fact, the neurogenic and osteogenic stem cell niches derive from two distinct embryonary structures; while the later originates from the mesoderm, as all the connective tissues do, the first derives from the ectoderm. Therefore, it is highly unlikely that stem cells isolated from one niche could form terminally differentiated cells from the other. Additionally, these two niches are associated to tissues/systems (e.g., bone and central nervous system) that have markedly different needs and display diverse functions within the human body. Nevertheless they do share common features. For instance, the differentiation of both NSCs and MSCs is intimately associated with the bone morphogenetic protein family. Moreover, both NSCs and MSCs secrete a panel of common growth factors, such as nerve growth factor (NGF), glial derived neurotrophic factor (GDNF), and brain derived neurotrophic factor (BDNF), among others. But it is not the features they share but the interaction between them that seem most important, and worth exploring; namely, it has already been shown that there are mutually beneficially effects when these cell types are co-cultured in vitro. In fact the use of MSCs, and their secretome, become a strong candidate to be used as a therapeutic tool for CNS applications, namely by triggering the endogenous proliferation and differentiation of neural progenitors, among other mechanisms. Quite interestingly it was recently revealed that MSCs could be found in the human brain, in the vicinity of capillaries. In the present review we highlight how MSCs and NSCs in the neurogenic niches interact. Furthermore, we propose directions on this field and explore the future therapeutic possibilities that may arise from the combination/interaction of MSCs and NSCs.

Pre-clinical trials for Machado-Joseph Disease: Hypothesis-based and hypothesis-free therapeutic approaches

Tese de Doutoramento em Ciências da Saúde