64 research outputs found

    Surface Electromyography Feature Extraction Based on Wavelet Transform

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    Considering the vast variety of EMG signal applications such as rehabilitation of people suffering from some mobility limitations, scientists have done much research on EMG control system. In this regard, feature extraction of EMG signal has been highly valued as a significant technique to extract the desired information of EMG signal and remove unnecessary parts. In this study, Wavelet Transform (WT) has been applied as the main technique to extract Surface EMG (SEMG) features because WT is consistent with the nature of EMG as a nonstationary signal. Furthermore, two evaluation criteria, namely, RES index (the ratio of a Euclidean distance to a standard deviation) and scatter plot are recruited to investigate the efficiency of wavelet feature extraction. The results illustrated an improvement in class separability of hand movements in feature space. Accordingly, it has been shown that only the SEMG features extracted from first and second level of WT decomposition by second order of Daubechies family (db2) yielded the best class separability

    An intelligent system based on fuzzy probabilities for medical diagnosis - a study in aphasia diagnosis

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    Abstract BACKGROUND: Aphasia diagnosis is particularly challenging due to the linguistic uncertainty and vagueness, inconsistencies in the definition of aphasic syndromes, large number of measurements with imprecision, natural diversity and subjectivity in test objects as well as in opinions of experts who diagnose the disease

    Correlation of Circulating Omentin-1 with Bone Mineral Density in Multiple Sclerosis: The Crosstalk between Bone and Adipose Tissue

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    BACKGROUND: Patients with multiple sclerosis (MS) are at increased risk of osteoporosis and fractures. Adipose tissue-derived adipokines may play important roles in the osteoimmunology of MS. In order to determine whether omentin-1 and vaspin may be related to bone health in MS patients, we compared circulating levels of these recently identified adipokines, between MS patients and healthy controls. METHODS: A total of 35 ambulatory MS patients with relapsing-remitting courses were compared with 38 age- and sex-matched healthy controls. Bone mineral density (BMD) was determined for the lumbar spine (L2-L4) and the proximal femur using dual-energy x-ray absorptiometry. Circulating omentin-1, vaspin, osteocalcin, osteopontin, osteoprotegerin, the receptor activator of nuclear factor-κB ligand, matrix metalloproteinase 9, C-reactive protein and 25-hydroxy vitamin D levels were evaluated by highly specific enzyme-linked immunosorbent assay methods. RESULTS: There was no significant difference between the two groups regarding bone-related cytokines, adipocytokines, and the BMD measurements of patients with MS and the healthy controls. However, in multiple regression analysis, serum omentin-1 levels were positively correlated with BMD at the femoral neck (β = 0.49, p = 0.016), total hip (β = 0.42, p = 0.035), osteopontin (β = 0.42, p = 0.030) and osteocalcin (β = 0.53, p = 0.004) in MS patients. No correlations were found between vaspin, biochemical, and BMD measures in both groups. CONCLUSIONS: Elevated omentin-1 serum levels are correlated with BMD at the femoral neck and the serum levels of osteocalcin and osteopontin in MS patients. Therefore, there is crosstalk between adipose tissue and bone in MS

    The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

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    Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe
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