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1.
IEEE Trans Biomed Eng ; 70(3): 800-811, 2023 03.
Article in English | MEDLINE | ID: mdl-36136923

ABSTRACT

OBJECTIVE: In this paper, we present a robust version of the well-known exact low-resolution electromagnetic tomography (eLORETA) technique, named ReLORETA, to localize brain sources in the presence of different forward model uncertainties. METHODS: We first assume that the true lead field matrix is a transformation of the existing lead field matrix distorted by uncertainties and propose an iterative approach to estimate this transformation accurately. Major sources of the forward model uncertainties, including differences in geometry, conductivity, and source space resolution between the real and simulated head models, and misaligned electrode positions, are then simulated to test the proposed method. RESULTS: ReLORETA and eLORETA are applied to simulated focal sources in different regions of the brain and the presence of various noise levels as well as real data from a patient with focal epilepsy. The results show that ReLORETA is considerably more robust and accurate than eLORETA in all cases. CONCLUSION: Having successfully dealt with the forward model uncertainties, ReLORETA proved to be a promising method for real-world clinical applications. SIGNIFICANCE: eLORETA is one of the localization techniques that could be used to study brain activity for medical applications such as determining the epileptogenic zone in patients with medically refractory epilepsy. However, the major limitation of eLORETA is sensitivity to the uncertainties in the forward model. Since this problem can substantially undermine its performance in real-world applications where the exact lead field matrix is unknown, developing a more robust method capable of dealing with these uncertainties is of significant interest.


Subject(s)
Brain , Epilepsies, Partial , Humans , Brain/diagnostic imaging , Electric Conductivity , Electrodes , Uncertainty
2.
Int J Equity Health ; 15: 27, 2016 Feb 17.
Article in English | MEDLINE | ID: mdl-26883742

ABSTRACT

BACKGROUND: Maternal healthcare utilization is a major determinant of maternal mortality. Bangladesh is experiencing a rapid pace of urbanization with all future growth in population expected to be in urban areas. Health care infrastructure is different in urban and rural areas thus warranting an examination of equity in use rates of maternal healthcare. This paper addresses whether the urban-rural and rich-poor gaps in use of selected maternal healthcare indicators have narrowed or widened over the last decade. The paper also explores changes in the service provider environment in urban and rural domains. METHODS: The 2001 and 2010 Bangladesh Maternal Mortality and Health Care Survey data were used to examine trends in use of antenatal care from medically trained providers and in deliveries taking place at health facilities. Separate wealth quintiles were constructed for urban and rural areas. The concentration index was calculated for urban and rural areas to measure equity in distribution of antenatal care (ANC) and facility deliveries across wealth quintiles in urban and rural domains. RESULTS: The gap in use of ANC provided by medically trained personnel narrowed in urban and rural areas between 2001 and 2010 while that in facility deliveries widened. The difference in use of ANC by the rich and the poor was not as pronounced as that in utilization of facilities for deliveries. Over the last decade, equity in utilization of health facilities for deliveries has improved at a faster rate in urban areas. Private sector has surpassed the public sector and appears to be the dominant provider of maternal healthcare in both domains with the share of NGOs increasing in urban areas. CONCLUSIONS: The faster pace of improvement in equity in maternal healthcare utilization in urban areas is reflective of the changing service environment in urban and rural areas, among other factors.


Subject(s)
Health Equity/trends , Maternal Health Services/trends , Rural Population/statistics & numerical data , Urban Population/statistics & numerical data , Adult , Bangladesh , Female , Health Equity/statistics & numerical data , Humans , Maternal Health Services/statistics & numerical data , Pregnancy , Prenatal Care/statistics & numerical data , Socioeconomic Factors
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