5 resultados para Hallucination

em Queensland University of Technology - ePrints Archive


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This study was a phenomenological inquiry of the experience of auditory hallucinations as described by 13 Indonesian people diagnosed with schizophrenia. The interviewees included 6 men and 7 women and they were aged between 19 and 56 years. Four themes emerged from this study: feeling more like a robot than a human being; voices of contradiction - a point of confusion; tattered relationships and family disarray; and normalizing the presence of voices as part of everyday life. The findings of this study have the potential to contribute to new understandings of how people live with and manage auditory hallucinations and so enhance client-centered nursing care.

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Identifying an individual from surveillance video is a difficult, time consuming and labour intensive process. The proposed system aims to streamline this process by filtering out unwanted scenes and enhancing an individual's face through super-resolution. An automatic face recognition system is then used to identify the subject or present the human operator with likely matches from a database. A person tracker is used to speed up the subject detection and super-resolution process by tracking moving subjects and cropping a region of interest around the subject's face to reduce the number and size of the image frames to be super-resolved respectively. In this paper, experiments have been conducted to demonstrate how the optical flow super-resolution method used improves surveillance imagery for visual inspection as well as automatic face recognition on an Eigenface and Elastic Bunch Graph Matching system. The optical flow based method has also been benchmarked against the ``hallucination'' algorithm, interpolation methods and the original low-resolution images. Results show that both super-resolution algorithms improved recognition rates significantly. Although the hallucination method resulted in slightly higher recognition rates, the optical flow method produced less artifacts and more visually correct images suitable for human consumption.

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Characteristics of surveillance video generally include low resolution and poor quality due to environmental, storage and processing limitations. It is extremely difficult for computers and human operators to identify individuals from these videos. To overcome this problem, super-resolution can be used in conjunction with an automated face recognition system to enhance the spatial resolution of video frames containing the subject and narrow down the number of manual verifications performed by the human operator by presenting a list of most likely candidates from the database. As the super-resolution reconstruction process is ill-posed, visual artifacts are often generated as a result. These artifacts can be visually distracting to humans and/or affect machine recognition algorithms. While it is intuitive that higher resolution should lead to improved recognition accuracy, the effects of super-resolution and such artifacts on face recognition performance have not been systematically studied. This paper aims to address this gap while illustrating that super-resolution allows more accurate identification of individuals from low-resolution surveillance footage. The proposed optical flow-based super-resolution method is benchmarked against Baker et al.’s hallucination and Schultz et al.’s super-resolution techniques on images from the Terrascope and XM2VTS databases. Ground truth and interpolated images were also tested to provide a baseline for comparison. Results show that a suitable super-resolution system can improve the discriminability of surveillance video and enhance face recognition accuracy. The experiments also show that Schultz et al.’s method fails when dealing surveillance footage due to its assumption of rigid objects in the scene. The hallucination and optical flow-based methods performed comparably, with the optical flow-based method producing less visually distracting artifacts that interfered with human recognition.

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BACKGROUND: Dystrobrevin binding protein 1 (DTNBP1) is a schizophrenia susceptibility gene involved with neurotransmission regulation (especially dopamine and glutamate) and neurodevelopment. The gene is known to be associated with cognitive deficit phenotypes within schizophrenia. In our previous studies, DTNBP1 was found associated not only with schizophrenia but with other psychiatric disorders including psychotic depression, post-traumatic stress disorder, nicotine dependence and opiate dependence. These findings suggest that DNTBP1 may be involved in pathways that lead to multiple psychiatric phenotypes. In this study, we explored the association between DTNBP1 SNPs (single nucleotide polymorphisms) and multiple psychiatric phenotypes included in the Diagnostic Interview of Psychosis (DIP). METHODS: Five DTNBP1 SNPs, rs17470454, rs1997679, rs4236167, rs9370822 and rs9370823, were genotyped in 235 schizophrenia subjects screened for various phenotypes in the domains of depression, mania, hallucinations, delusions, subjective thought disorder, behaviour and affect, and speech disorder. SNP-phenotype association was determined with ANOVA under general, dominant/recessive and over-dominance models. RESULTS: Post hoc tests determined that SNP rs1997679 was associated with visual hallucination; SNP rs4236167 was associated with general auditory hallucination as well as specific features including non-verbal, abusive and third-person form auditory hallucinations; and SNP rs9370822 was associated with visual and olfactory hallucinations. SNPs that survived correction for multiple testing were rs4236167 for third-person and abusive form auditory hallucinations; and rs9370822 for olfactory hallucinations. CONCLUSION: These data suggest that DTNBP1 is likely to play a role in development of auditory related, visual and olfactory hallucinations which is consistent with evidence of DTNBP1 activity in the auditory processing regions, in visual processing and in the regulation of glutamate and dopamine activity

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Experience suggests that the central anticholinergic action of promethazine is a major element in the toxic effects following overdosage. Physostigmine seems to be a direct antidote at doses within the safe therapeutic range; side-effects, if they become a problem, can be treated with intravenous atropine.