41 research outputs found
Simultaneous EEG-fMRI : novel methods for EEG artefacts reduction at source
This thesis describes the development and application of novel techniques to reduce the EEG artefacts at source during the simultaneous acquisition of EEG and fMRI data. The work described in this thesis was carried out by the author in the Sir Peter Mansfield Magnetic Resonance Centre, School of Physics & Astronomy at the University of Nottingham, between October 2010 and January 2013.
Large artefacts compromise EEG data quality during simultaneous fMRI. These artefact voltages pose heavy demands on the bandwidth and dynamic range of EEG amplifiers and mean that even small fractional variations in the artefact voltages give rise to significant residual artefacts after correction, which can easily swamp signals from brain activity. Therefore any intrinsic reduction in the magnitude of the artefacts would be highly advantageous, allowing data with a higher bandwidth to be acquired without amplifier saturation, and facilitating improved detection of brain activity. This thesis firstly explores a new method for reducing the gradient artefact (GA), which is induced in EEG data recorded during concurrent MRI, by investigating the effects of the cable configuration on the characteristics of the GA. This work showed that the GA amplitude and its sensitivity to movement of the cabling is reduced by minimising wire loop areas in the cabling between the EEG cap and amplifier.
Another novel approach for reducing the magnitude and variability of the artefacts is the use of an EEG cap that incorporates electrodes embedded in a reference layer, which has a similar conductivity to tissue and is electrically isolated from the scalp. With this arrangement, the artefact voltages produced on the reference layer leads are theoretically similar to those induced in the scalp leads, but neuronal signals are not detected in the reference layer. Therefore taking the difference of the voltages in the reference and scalp channels should reduce the artefacts, without affecting sensitivity to neuronal signals. The theoretical efficacy of artefact correction that can be achieved by using this new reference layer artefact subtraction (RLAS) method was investigated. This was done through separate electromagnetic simulations of the artefacts induced in a hemispherical reference layer and a spherical volume conductor in a time-varying magnetic field and the results showed that similar artefacts are induced on the surface of both conductors. Simulations are also performed to find the optimal design for an RLAS system, by varying the geometry of the system.
A simple experimental realisation of the RLAS system was implemented to investigate the degree of artefact attenuation that can be achieved via RLAS. Through a series of experiments on phantoms and human subjects, it is shown here that RLAS significantly reduces the GA, pulse (PA) and motion (MA) artefacts, while allowing accurate recording of neuronal signals. The results indicate that RLAS generally outperforms the standard artefact correction method, average artefact subtraction (AAS), in the removal of the GA and PA when motion is present, while the combination of RLAS and AAS always produces higher artefact attenuation than AAS alone. Additionally, this work demonstrates that RLAS greatly attenuates the unpredictable and highly variable MA that are very hard to remove using post-processing methods
Simultaneous EEG-fMRI : novel methods for EEG artefacts reduction at source
This thesis describes the development and application of novel techniques to reduce the EEG artefacts at source during the simultaneous acquisition of EEG and fMRI data. The work described in this thesis was carried out by the author in the Sir Peter Mansfield Magnetic Resonance Centre, School of Physics & Astronomy at the University of Nottingham, between October 2010 and January 2013.
Large artefacts compromise EEG data quality during simultaneous fMRI. These artefact voltages pose heavy demands on the bandwidth and dynamic range of EEG amplifiers and mean that even small fractional variations in the artefact voltages give rise to significant residual artefacts after correction, which can easily swamp signals from brain activity. Therefore any intrinsic reduction in the magnitude of the artefacts would be highly advantageous, allowing data with a higher bandwidth to be acquired without amplifier saturation, and facilitating improved detection of brain activity. This thesis firstly explores a new method for reducing the gradient artefact (GA), which is induced in EEG data recorded during concurrent MRI, by investigating the effects of the cable configuration on the characteristics of the GA. This work showed that the GA amplitude and its sensitivity to movement of the cabling is reduced by minimising wire loop areas in the cabling between the EEG cap and amplifier.
Another novel approach for reducing the magnitude and variability of the artefacts is the use of an EEG cap that incorporates electrodes embedded in a reference layer, which has a similar conductivity to tissue and is electrically isolated from the scalp. With this arrangement, the artefact voltages produced on the reference layer leads are theoretically similar to those induced in the scalp leads, but neuronal signals are not detected in the reference layer. Therefore taking the difference of the voltages in the reference and scalp channels should reduce the artefacts, without affecting sensitivity to neuronal signals. The theoretical efficacy of artefact correction that can be achieved by using this new reference layer artefact subtraction (RLAS) method was investigated. This was done through separate electromagnetic simulations of the artefacts induced in a hemispherical reference layer and a spherical volume conductor in a time-varying magnetic field and the results showed that similar artefacts are induced on the surface of both conductors. Simulations are also performed to find the optimal design for an RLAS system, by varying the geometry of the system.
A simple experimental realisation of the RLAS system was implemented to investigate the degree of artefact attenuation that can be achieved via RLAS. Through a series of experiments on phantoms and human subjects, it is shown here that RLAS significantly reduces the GA, pulse (PA) and motion (MA) artefacts, while allowing accurate recording of neuronal signals. The results indicate that RLAS generally outperforms the standard artefact correction method, average artefact subtraction (AAS), in the removal of the GA and PA when motion is present, while the combination of RLAS and AAS always produces higher artefact attenuation than AAS alone. Additionally, this work demonstrates that RLAS greatly attenuates the unpredictable and highly variable MA that are very hard to remove using post-processing methods
A new estimate of carbon for Bangladesh forest ecosystems with their spatial distribution and REDD+ implications
In tropical developing countries, reducing emissions from deforestation and forest degradation (REDD+) is becoming an important mechanism for conserving forests and protecting biodiversity. A key prerequisite for any successful REDD+ project, however, is obtaining baseline estimates of carbon in forest ecosystems. Using available published data, we provide here a new and more reliable estimate of carbon in Bangladesh forest ecosystems, along with their geo-spatial distribution. Our study reveals great variability in carbon density in different forests and higher carbon stock in the mangrove ecosystems, followed by in hill forests and in inland Sal (Shorea robusta) forests in the country. Due to its coverage, degraded nature, and diverse stakeholder engagement, the hill forests of Bangladesh can be used to obtain maximum REDD+ benefits. Further research on carbon and biodiversity in under-represented forest ecosystems using a commonly accepted protocol is essential for the establishment of successful REDD+ projects and for the protection of the country’s degraded forests and for addressing declining levels of biodiversity
3D Printed Bioscaffolds for Developing Tissue-Engineered Constructs
Tissue engineering techniques enable the fabrication of tissue substitutes integrating cells, biomaterials, and bioactive compounds to replace or repair damaged or diseased tissues. Despite the early success, current technology is unable to fabricate reproducible tissue-engineered constructs with the structural and functional similarity of the native tissue. The recent development of 3D printing technology empowers the opportunities of developing biofunctional complex tissue substitutes via layer-by-layer fabrication of cell(s), biomaterial(s), and bioactive compound(s) in precision. In this chapter, the current development of fabricating tissue-engineered constructs using 3D bioprinting technology for potential biomedical applications such as tissue replacement therapy, personalized therapy, and in vitro 3D modeling for drug discovery will be discussed. The current challenges, limitations, and role of stakeholders to grasp the future success also will be highlighted
Blind ECG Restoration by Operational Cycle-GANs
Objective: ECG recordings often suffer from a set of artifacts with varying types, severities, and durations, and this makes an accurate diagnosis by machines or medical doctors difficult and unreliable. Numerous studies have proposed ECG denoising; however, they naturally fail to restore the actual ECG signal corrupted with such artifacts due to their simple and naive noise model. In this pilot study, we propose a novel approach for blind ECG restoration using cycle-consistent generative adversarial networks (Cycle-GANs) where the quality of the signal can be improved to a clinical level ECG regardless of the type and severity of the artifacts corrupting the signal. Methods: To further boost the restoration performance, we propose 1D operational Cycle-GANs with the generative neuron model. Results: The proposed approach has been evaluated extensively using one of the largest benchmark ECG datasets from the China Physiological Signal Challenge (CPSC-2020) with more than one million beats. Besides the quantitative and qualitative evaluations, a group of cardiologists performed medical evaluations to validate the quality and usability of the restored ECG, especially for an accurate arrhythmia diagnosis. Significance: As a pioneer study in ECG restoration, the corrupted ECG signals can be restored to clinical level quality. Conclusion: By means of the proposed ECG restoration, the ECG diagnosis accuracy and performance can significantly improve.publishedVersionPeer reviewe
Powerline interference suppression of a textile-insulated capacitive biomedical sensor using digital filters
This research evaluated a textile-insulated capacitive (TEX-C) biomedical sensor insulated by six types of textile materials namely cotton, linen, rayon, nylon, polyester, and PVC-textile. Each textile material creates a unique skin-electrode capacitance and affected the susceptibility of the TEX-C biomedical sensor towards the 50 Hz powerline interference (PLI) and its harmonics. Designing versatile TEX-C biosensor hardware that can tolerate different textile insulators while maintaining an optimum signal measurement quality proves to be a significant challenge. Five digital filters such as notch filter, comb filter, discrete wavelet transform, undecimated wavelet transform, and normalized least mean squares adaptive filter were implemented to compare their performance in suppressing the 50 Hz PLI and its harmonics. The comb filter yielded the best results in suppressing the 50 Hz PLI and its harmonics below -130 dB while improving the correlation coefficient of the EMG signals measured by TEX-C biomedical sensors and the wet contact electrode.This research is financially supported by Universiti Kebangsaan Malaysia (UKM), Grant No. GUP-2021-019 , UKM-TR-011 , and DIP-2020-004 and Qatar National Research Foundation (QNRF) grant no. NPRP12s-0227-190164 and International Research Collaboration Co-Fund (IRCC) grant: IRCC-2021-001 . Open Access publication of this article is supported by Qatar National Library. The statements made herein are solely the responsibility of the authors.Scopu
A new estimate of carbon for Bangladesh forest ecosystems with their spatial distribution and REDD+ implications
Measuring routine childhood vaccination coverage in 204 countries and territories, 1980-2019 : a systematic analysis for the Global Burden of Disease Study 2020, Release 1
Background Measuring routine childhood vaccination is crucial to inform global vaccine policies and programme implementation, and to track progress towards targets set by the Global Vaccine Action Plan (GVAP) and Immunization Agenda 2030. Robust estimates of routine vaccine coverage are needed to identify past successes and persistent vulnerabilities. Drawing from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2020, Release 1, we did a systematic analysis of global, regional, and national vaccine coverage trends using a statistical framework, by vaccine and over time. Methods For this analysis we collated 55 326 country-specific, cohort-specific, year-specific, vaccine-specific, and dosespecific observations of routine childhood vaccination coverage between 1980 and 2019. Using spatiotemporal Gaussian process regression, we produced location-specific and year-specific estimates of 11 routine childhood vaccine coverage indicators for 204 countries and territories from 1980 to 2019, adjusting for biases in countryreported data and reflecting reported stockouts and supply disruptions. We analysed global and regional trends in coverage and numbers of zero-dose children (defined as those who never received a diphtheria-tetanus-pertussis [DTP] vaccine dose), progress towards GVAP targets, and the relationship between vaccine coverage and sociodemographic development. Findings By 2019, global coverage of third-dose DTP (DTP3; 81.6% [95% uncertainty interval 80.4-82 .7]) more than doubled from levels estimated in 1980 (39.9% [37.5-42.1]), as did global coverage of the first-dose measles-containing vaccine (MCV1; from 38.5% [35.4-41.3] in 1980 to 83.6% [82.3-84.8] in 2019). Third- dose polio vaccine (Pol3) coverage also increased, from 42.6% (41.4-44.1) in 1980 to 79.8% (78.4-81.1) in 2019, and global coverage of newer vaccines increased rapidly between 2000 and 2019. The global number of zero-dose children fell by nearly 75% between 1980 and 2019, from 56.8 million (52.6-60. 9) to 14.5 million (13.4-15.9). However, over the past decade, global vaccine coverage broadly plateaued; 94 countries and territories recorded decreasing DTP3 coverage since 2010. Only 11 countries and territories were estimated to have reached the national GVAP target of at least 90% coverage for all assessed vaccines in 2019. Interpretation After achieving large gains in childhood vaccine coverage worldwide, in much of the world this progress was stalled or reversed from 2010 to 2019. These findings underscore the importance of revisiting routine immunisation strategies and programmatic approaches, recentring service delivery around equity and underserved populations. Strengthening vaccine data and monitoring systems is crucial to these pursuits, now and through to 2030, to ensure that all children have access to, and can benefit from, lifesaving vaccines. Copyright (C) 2021 The Author(s). Published by Elsevier Ltd.Peer reviewe
Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021
Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions
