1,666 research outputs found

    Design of a wearable sensor system for neonatal seizure monitoring

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    Design of a wearable sensor system for neonatal seizure monitoring

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    Informatics for EEG biomarker discovery in clinical neuroscience

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    Neurological and developmental disorders (NDDs) impose an enormous burden of disease on children throughout the world. Two of the most common are autism spectrum disorder (ASD) and epilepsy. ASD has recently been estimated to affect 1 in 68 children, making it the most common neurodevelopmental disorder in children. Epilepsy is also a spectrum disorder that follows a developmental trajectory, with an estimated prevalence of 1%, nearly as common as autism. ASD and epilepsy co-occur in approximately 30% of individuals with a primary diagnosis of either disorder. Although considered to be different disorders, the relatively high comorbidity suggests the possibility of common neuropathological mechanisms. Early interventions for NDDs lead to better long-term outcomes. But early intervention is predicated on early detection. Behavioral measures have thus far proven ineffective in detecting autism before about 18 months of age, in part because the behavioral repertoire of infants is so limited. Similarly, no methods for detecting emerging epilepsy before seizures begin are currently known. Because atypical brain development is likely to precede overt behavioral manifestations by months or even years, a critical developmental window for early intervention may be opened by the discovery of brain based biomarkers. Analysis of brain activity with EEG may be under-utilized for clinical applications, especially for neurodevelopment. The hypothesis investigated in this dissertation is that new methods of nonlinear signal analysis, together with methods from biomedical informatics, can extract information from EEG data that enables detection of atypical neurodevelopment. This is tested using data collected at Boston Children’s Hospital. Several results are presented. First, infants with a family history of ASD were found to have EEG features that may enable autism to be detected as early as 9 months. Second, significant EEG-based differences were found between children with absence epilepsy, ASD and control groups using short 30-second EEG segments. Comparison of control groups using different EEG equipment supported the claim that EEG features could be computed that were independent of equipment and lab conditions. Finally, the potential for this technology to help meet the clinical need for neurodevelopmental screening and monitoring in low-income regions of the world is discussed

    Seizure Detection, Seizure Prediction, and Closed-Loop Warning Systems in Epilepsy

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    Nearly one-third of patients with epilepsy continue to have seizures despite optimal medication management. Systems employed to detect seizures may have the potential to improve outcomes in these patients by allowing more tailored therapies and might, additionally, have a role in accident and SUDEP prevention. Automated seizure detection and prediction require algorithms which employ feature computation and subsequent classification. Over the last few decades, methods have been developed to detect seizures utilizing scalp and intracranial EEG, electrocardiography, accelerometry and motion sensors, electrodermal activity, and audio/video captures. To date, it is unclear which combination of detection technologies yields the best results, and approaches may ultimately need to be individualized. This review presents an overview of seizure detection and related prediction methods and discusses their potential uses in closed-loop warning systems in epilepsy

    The Love Hormone and Seizure Control: A Review of Oxytocin’s Impact on Epilepsy Management

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    Epilepsy is a neurological disorder characterised by recurrent seizures, which can significantly impact patient’s quality of life. While current management strategies for epilepsy, such as antiepileptic drugs and surgery, are effective for many patients, there is a need for novel therapies that can provide better seizure control and improve patients’ outcomes. Oxytocin, a neuropeptide known for its role in social bonding and trust, has emerged as a promising therapy for epilepsy. Preclinical studies have shown that oxytocin can reduce seizure activity and improve seizure outcomes in animal models of epilepsy. In contrast, clinical studies have suggested that oxytocin may reduce seizure frequency and severity in some epilepsy patients. This chapter reviews the current knowledge of oxytocin and epilepsy, including the potential mechanisms of oxytocin’s antiepileptic effects, the limitations and challenges of clinical studies, and future research directions and implications. The chapter also discusses the broader impact of oxytocin research on understanding social behaviour and neurological disorders. Overall, the chapter highlights the potential of oxytocin as a novel therapy for epilepsy management and underscores the need for further research

    Epilepsy

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    With the vision of including authors from different parts of the world, different educational backgrounds, and offering open-access to their published work, InTech proudly presents the latest edited book in epilepsy research, Epilepsy: Histological, electroencephalographic, and psychological aspects. Here are twelve interesting and inspiring chapters dealing with basic molecular and cellular mechanisms underlying epileptic seizures, electroencephalographic findings, and neuropsychological, psychological, and psychiatric aspects of epileptic seizures, but non-epileptic as well

    Epilepsy

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    Epilepsy is the most common neurological disorder globally, affecting approximately 50 million people of all ages. It is one of the oldest diseases described in literature from remote ancient civilizations 2000-3000 years ago. Despite its long history and wide spread, epilepsy is still surrounded by myth and prejudice, which can only be overcome with great difficulty. The term epilepsy is derived from the Greek verb epilambanein, which by itself means to be seized and to be overwhelmed by surprise or attack. Therefore, epilepsy is a condition of getting over, seized, or attacked. The twelve very interesting chapters of this book cover various aspects of epileptology from the history and milestones of epilepsy as a disease entity, to the most recent advances in understanding and diagnosing epilepsy

    The safety of antipsychotic use during pregnancy

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    Aim: To investigate the patterns of gestational antipsychotics use and whether exposure to antipsychotic medications in pregnancy is associated with gestational diabetes mellitus (GDM) in mothers and seizure, attention deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), preterm birth (PTB) and small for gestational age (SFGA) in subsequent children. Methods: Firstly, a methodological review was conducted to review the methodological characteristics of existing observational studies that investigate the association between prenatal central nervous system (CNS) drugs use and CNS disorders. Secondly, a systematic review and meta-analysis was conducted to evaluate the evidence-based association between gestational antipsychotic use and GDM. Thirdly, a cross-sectional study was conducted to investigate the patterns and trends of antipsychotics use during pregnancy in the United Kingdom (UK) and Hong Kong (HK). Lastly, seven cohort studies were conducted to investigate the association between antipsychotics use in pregnancy and the risk of above-mentioned outcomes, respectively. Results: 4.64% and 0.34% of pregnancies were prescribed at least one prescription of antipsychotic during pregnancy in the UK and HK, respectively. When women who continued using antipsychotics during pregnancy were compared with those who had stopped, there was no evidence to demonstrate an increased risk of GDM. No evidence supported prenatal exposure to antipsychotics can increase the risk of ADHD/ASD/SFGA. Children with prenatal antipsychotics exposure was associated with an increased risk of seizure (HR 1.49, 95% CI 1.11-1.99) and PTB (OR 1.40, 95%CI 1.13-1.75), comparing to those without. However, further sibling-matched analyses and negative control analyses indicated no evidence supported the above-mentioned associations. Conclusion: This PhD project did not suggest an increased risk of GDM in mothers or seizure/ADHD/ASD/PTB/SFGA in children regarding antipsychotics use during pregnancy. Women are not recommended to stop their regular antipsychotic prescription during pregnancy due to the risk of developing GDM or delivering an offspring with seizure/ADHD/ASD/PTB/SFGA
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