Heart diseases diagnosis using HMM

The bare ear and the stethoscope were until recently of great help in classifying most heart diseases especially those related to valve problems. The newly developed electronic stethoscope and phonocardiography represent useful tools for recording heart sound signals. In this paper a diagnostic technique for heart diseases using heart sounds is suggested. Wavelet decomposition and mel cepstrum are used for feature extraction. Classification of the different heart diseases is then done using hidden Markov models (HMM). Three different techniques have been used and compared. The obtained recognition rates (RR) were 97.3%, 98.2%, and 99.1%

Digital health behaviour change interventions targeting physical activity and diet in cancer survivors: a systematic review and meta-analysis

Purpose: The number of cancer survivors has risen substantially due to improvements in early diagnosis and treatment. Health behaviours such as physical activity (PA) and diet can reduce recurrence and mortality, and alleviate negative consequences of cancer and treatments. Digital behaviour change interventions (DBCIs) have the potential to reach large numbers of cancer survivors. Methods: We conducted a systematic review and meta-analyses of relevant studies identified by a search of Medline, EMBASE, PubMed and CINAHL. Studies which assessed a DBCI with measures of PA, diet and/or sedentary behaviour were included. Results: 15 studies were identified. Random effects meta-analyses showed significant improvements in moderate-vigorous PA (7 studies; mean difference (MD) = 41 minutes per week; 95% CI: 12, 71) and body mass index (BMI)/weight (standardised mean difference (SMD) = -0.23; 95% CI: -0.41, -0.05). There was a trend toward significance for reduced fatigue and no significant change in cancer-specific quality of life (QoL). Narrative synthesis revealed mixed evidence for effects on diet, generic QoL and self-efficacy and no evidence of an effect on mental health. Two studies suggested improved sleep quality. Conclusions: DBCIs may improve PA and BMI among cancer survivors and there is mixed evidence for diet. The number of included studies is small and risk of bias and heterogeneity was high. Future research should address these limitations with large, high-quality RCTs, with objective measures of PA and sedentary time. Implications for cancer survivors: Digital technologies offer a promising approach to encourage health behaviour change among cancer survivors

Reduced Mitochondrial Membrane Potential is a Late Adaptation of Trypanosoma brucei brucei to Isometamidium Preceded by Mutations in the γ Subunit of the F1Fo- ATPase

Background: Isometamidium is the main prophylactic drug used to prevent the infection of livestock with trypanosomes that cause Animal African Trypanosomiasis. As well as the animal infective trypanosome species, livestock can also harbor the closely related human infective subspecies T. b. gambiense and T. b. rhodesiense. Resistance to isometamidium is a growing concern, as is cross-resistance to the diamidine drugs diminazene and pentamidine. Methodology/Principal Findings: Two isometamidium resistant Trypanosoma brucei clones were generated (ISMR1 and ISMR15), being 7270- and 16,000-fold resistant to isometamidium, respectively, which retained their ability to grow in vitro and establish an infection in mice. Considerable cross-resistance was shown to ethidium bromide and diminazene, with minor cross-resistance to pentamidine. The mitochondrial membrane potentials of both resistant cell lines were significantly reduced compared to the wild type. The net uptake rate of isometamidium was reduced 2-3-fold but isometamidium efflux was similar in wild-type and resistant lines. Fluorescence microscopy and PCR analysis revealed that ISMR1 and ISMR15 had completely lost their kinetoplast DNA (kDNA) and both lines carried a mutation in the nuclearly encoded γ subunit gene of F1 ATPase, truncating the protein by 22 amino acids. The mutation compensated for the loss of the kinetoplast in bloodstream forms, allowing near-normal growth, and conferred considerable resistance to isometamidium and ethidium as well as significant resistance to diminazene and pentamidine, when expressed in wild type trypanosomes. Subsequent exposure to either isometamidium or ethidium led to rapid loss of kDNA and a further increase in isometamidium resistance. Conclusions/Significance: Sub-lethal exposure to isometamidium gives rise to viable but highly resistant trypanosomes that, depending on sub-species, are infective to humans and cross-resistant to at least some diamidine drugs. The crucial mutation is in the F1 ATPase γ subunit, which allows loss of kDNA and results in a reduction of the mitochondrial membrane potential

Statistical Signal and Image Processing Techniques in Corneal Modeling

In this thesis, we consider two interrelated problems, which are the enhancement of videokeratoscopic images for more accurate corneal topography estimation and model-order selection of corneal surfaces when expanded using orthogonal Zernike polynomials. Corneal topography estimation that is based on the Placido disk principle relies on good quality of pre-corneal tear film and sufficiently wide eyelid (palpebral) aperture to avoid reflections from eyelashes. However, in practice, these conditions are not always fulfilled resulting in missing regions, smaller corneal coverage, and subsequently poorer estimates of corneal topography. Our aim is to enhance the standard operating range of a Placido disk videokeratoscope to obtain reliable corneal topography estimates in patients with poor tear film quality, such as encountered in those diagnosed with dry eye, and with narrower palpebral apertures as in the case of Asian subjects. This is achieved by incorporating in the instrument's own topography estimation algorithm an image processing technique that comprises of linear adaptive filter (based on Wiener filtering theory) and non-linear filter (based on morphological operations). The experimental results from measurements of test surfaces and real corneas show that the incorporation of the proposed technique results in better estimates of corneal topography and, in many cases, to a significant increase in the estimated coverage area making such an enhanced videokeratoscope a better tool for clinicians. On the other hand, corneal height-data are typically modeled using a set of orthogonal Zernike polynomials. We address the estimation of the number of Zernike polynomials, which is formalized as a model-order selection problem in linear regression. Classical information theoretic criteria tend to overestimate the corneal surface due to the weakness of their penalty functions, while bootstrap-based techniques tend to underestimate the surface or require extensive processing. We propose to use the Efficient Detection Criterion (EDC), which has the same general form of information theoretic-based criteria, as an alternative to estimating the optimal number of Zernike polynomials. We first show, via simulations, that the EDC outperforms a large number of information theoretic criteria and resampling-based techniques. We then illustrate that using the EDC for real corneas results in models that are in closer agreement with clinical expectations and provides means for distinguishing normal corneal surfaces from astigmatic and keratoconic surfaces. The two problems are interrelated in the sense that appropriate modeling for corneal surfaces, regardless of the used functions, requires accurate corneal topography that can be efficiently estimated provided that the videokeratoscopic image is not degraded

A procedure to locate the eyelid position in noisy videokeratoscopic images

In this paper, we propose a new procedure to robustly determine the eyelid position in high-speed videokeratoscopic images. This knowledge is crucial in videokeratoscopy to study the effects of the eyelids on the cornea and on the tear film dynamics. Difficulties arise due to the very low contrast of videokeratoscopic images and because of the occlusions caused by the eyelashes. The proposed procedure uses robust M-estimation to fit a parametric model to a set of eyelid edge candidate pixels. To detect these pixels, firstly, nonlinear image filtering operations are performed to remove the eyelashes. Secondly, we propose an image segmentation approach based on morphological operations and active contours to provide the set of candidate pixels. Subsequently, a verification procedure reduces this set to pixels that are likely to contribute to an accurate fit of the eyelid edge. We propose a complete framework, for which each stage is evaluated using real-world videokeratoscopic images. This methodology allows for automatic localization of the eyelid edges and is applicable to replace the currently used time-consuming manual labeling approach, while maintaining its accuracy