Artefact detection and removal algorithms for EEG diagnostic systems

The electroencephalogram (EEG) is a medical technology that is used in the monitoring of the brain and in the diagnosis of many neurological illnesses. Although coarse in its precision, the EEG is a non-invasive tool that requires minimal set-up times, and is suitably unobtrusive and mobile to allow continuous monitoring of the patient, either in clinical or domestic environments. Consequently, the EEG is the current tool-of-choice with which to continuously monitor the brain where temporal resolution, ease-of- use and mobility are important. Traditionally, EEG data are examined by a trained clinician who identifies neurological events of interest. However, recent advances in signal processing and machine learning techniques have allowed the automated detection of neurological events for many medical applications. In doing so, the burden of work on the clinician has been significantly reduced, improving the response time to illness, and allowing the relevant medical treatment to be administered within minutes rather than hours. However, as typical EEG signals are of the order of microvolts (μV ), contamination by signals arising from sources other than the brain is frequent. These extra-cerebral sources, known as artefacts, can significantly distort the EEG signal, making its interpretation difficult, and can dramatically disimprove automatic neurological event detection classification performance. This thesis therefore, contributes to the further improvement of auto- mated neurological event detection systems, by identifying some of the major obstacles in deploying these EEG systems in ambulatory and clinical environments so that the EEG technologies can emerge from the laboratory towards real-world settings, where they can have a real-impact on the lives of patients. In this context, the thesis tackles three major problems in EEG monitoring, namely: (i) the problem of head-movement artefacts in ambulatory EEG, (ii) the high numbers of false detections in state-of-the-art, automated, epileptiform activity detection systems and (iii) false detections in state-of-the-art, automated neonatal seizure detection systems. To accomplish this, the thesis employs a wide range of statistical, signal processing and machine learning techniques drawn from mathematics, engineering and computer science. The first body of work outlined in this thesis proposes a system to automatically detect head-movement artefacts in ambulatory EEG and utilises supervised machine learning classifiers to do so. The resulting head-movement artefact detection system is the first of its kind and offers accurate detection of head-movement artefacts in ambulatory EEG. Subsequently, addtional physiological signals, in the form of gyroscopes, are used to detect head-movements and in doing so, bring additional information to the head- movement artefact detection task. A framework for combining EEG and gyroscope signals is then developed, offering improved head-movement arte- fact detection. The artefact detection methods developed for ambulatory EEG are subsequently adapted for use in an automated epileptiform activity detection system. Information from support vector machines classifiers used to detect epileptiform activity is fused with information from artefact-specific detection classifiers in order to significantly reduce the number of false detections in the epileptiform activity detection system. By this means, epileptiform activity detection which compares favourably with other state-of-the-art systems is achieved. Finally, the problem of false detections in automated neonatal seizure detection is approached in an alternative manner; blind source separation techniques, complimented with information from additional physiological signals are used to remove respiration artefact from the EEG. In utilising these methods, some encouraging advances have been made in detecting and removing respiration artefacts from the neonatal EEG, and in doing so, the performance of the underlying diagnostic technology is improved, bringing its deployment in the real-world, clinical domain one step closer

Study of the Term Neonatal Brain Injury with combined Diffuse Optical Tomography and Electroencephalography

This thesis describes the application of combined diffuse optical tomography (DOT) and electroencephalography (EEG) in the investigation of neonatal term brain injury. With hypoxic ischaemic encephalopathy (HIE) and perinatal stroke being the most frequent contributors to brain injury in the term neonatal population, the first part of the thesis focuses on the description and ongoing requirement for their further investigation. In continuation to that, the characteristics and unique properties of both DOT and EEG are described and explored. The combination of these two modalities was utilised in elucidating the relationship between neuronal activity and cerebral haemodynamics both in physiological processes as well as in disease, by the infant’s cot side. This work differs to previous studies using near-infrared technologies and EEG, as a denser whole head array was used, offering the potential of 3-dimensional image reconstruction of the cortical haemodynamic events in relation to electro-cortical activity. These methods were applied in the study of critically ill infants presenting with seizures in the first few days of life. The relevant results are presented in three separate chapters of the thesis. Distinct neurophysiological phenomena such as seizures and burst suppression were detected and studied in association to underlying HIE. On the grounds of a pre-existing pilot study of our research group, distinct prolonged de-oxygenated cortical areas were identified following electrical seizure activity. Further exploration of infants with seizures provided limited supporting evidence. The investigation of burst suppression in HIE led to the first ever identification of repeated, waveform, cortical haemodynamic events in response to bursts of electrical activity with some spatial correlation to regions of brain injury. Further analysis of the low frequencies within the diffuse optical signal in cases of perinatal stroke, showed a consistent interhemispheric difference between the healthy and stroke-affected brain regions. The limitations, prospects and conclusions are presented in the final chapter. The use of simultaneous DOT and EEG offers a unique neuro-monitoring and neuro-investigating tool in the neonatal intensive care environment, which is safe, portable, and cost-effective, Ongoing research is required for the exploration and development of the methodology and its potential diagnostic properties

Management of Multi Organ Dysfunction in Neonatal Encephalopathy.

Neonatal Encephalopathy (NE) describes neonates with disturbed neurological function in the first post-natal days of life. NE is an overall term that does not specify the etiology of the encephalopathy although it often involves hypoxia-ischaemia. In NE, although neurological dysfunction is part of the injury and is most predictive of long-term outcome, these infants may also have multiorgan injury and compromise, which further contribute to neurological impairment and long-term morbidities. Therapeutic hypothermia (TH) is the standard of care for moderate to severe NE. Infants with NE may have co-existing immune, respiratory, endocrine, renal, hepatic, and cardiac dysfunction that require individualized management and can be impacted by TH. Non-neurological organ dysfunction not only has a negative effect on long term outcome but may also influence the efficacy of treatments in the acute phase. Post resuscitative care involves stabilization and decisions regarding TH and management of multi-organ dysfunction. This management includes detailed neurological assessment, cardio-respiratory stabilization, glycaemic and fluid control, sepsis evaluation and antibiotics, seizure identification, and monitoring and responding to biochemical and coagulation derangements. The emergence of new biomarkers of specific organ injury may have predictive value and improve the definition of organ injury and prognosis. Further evidence-based research is needed to optimize management of NE, prevent further organ dysfunction and reduce neurodevelopmental impairment

Highlights From the Annual Meeting of the American Epilepsy Society 2022

With more than 6000 attendees between in-person and virtual offerings, the American Epilepsy Society Meeting 2022 in Nashville, felt as busy as in prepandemic times. An ever-growing number of physicians, scientists, and allied health professionals gathered to learn a variety of topics about epilepsy. The program was carefully tailored to meet the needs of professionals with different interests and career stages. This article summarizes the different symposia presented at the meeting. Basic science lectures addressed the primary elements of seizure generation and pathophysiology of epilepsy in different disease states. Scientists congregated to learn about anti-seizure medications, mechanisms of action, and new tools to treat epilepsy including surgery and neurostimulation. Some symposia were also dedicated to discuss epilepsy comorbidities and practical issues regarding epilepsy care. An increasing number of patient advocates discussing their stories were intertwined within scientific activities. Many smaller group sessions targeted more specific topics to encourage member participation, including Special Interest Groups, Investigator, and Skills Workshops. Special lectures included the renown Hoyer and Lombroso, an ILAE/IBE joint session, a spotlight on the impact of Dobbs v. Jackson on reproductive health in epilepsy, and a joint session with the NAEC on coding and reimbursement policies. The hot topics symposium was focused on traumatic brain injury and post-traumatic epilepsy. A balanced collaboration with the industry allowed presentations of the latest pharmaceutical and engineering advances in satellite symposia

Epilepsy

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

Towards developing a reliable medical device for automated epileptic seizure detection in the ICU

Abstract. Epilepsy is a prevalent neurological disorder that affects millions of people globally, and its diagnosis typically involves laborious manual inspection of electroencephalography (EEG) data. Automated detection of epileptic seizures in EEG signals could potentially improve diagnostic accuracy and reduce diagnosis time, but there should be special attention to the number of false alarms to reduce unnecessary treatments and costs. This research presents a study on the use of machine learning techniques for EEG seizure detection with the aim of investigating the effectiveness of different algorithms in terms of high sensitivity and low false alarm rates for feature extraction, selection, pre-processing, classification, and post-processing in designing a medical device for detecting seizure activity in EEG data. The current state-of-the-art methods which are validated clinically using large amounts of data are introduced. The study focuses on finding potential machine learning methods, considering KNN, SVM, decision trees and, Random forests, and compares their performance on the task of seizure detection using features introduced in the literature. Also using ensemble methods namely, bootstrapping and majority voting techniques we achieved a sensitivity of 0.80 and FAR/h of 2.10, accuracy of 97.1% and specificity of 98.2%. Overall, the findings of this study can be useful for developing more accurate and efficient algorithms for EEG seizure detection medical device, which can contribute to the early diagnosis and treatment of epilepsy in the intensive care unit for critically ill patients

The TOBY Study. Whole body hypothermia for the treatment of perinatal asphyxial encephalopathy: A randomised controlled trial

<p>Abstract</p> <p>Background</p> <p>A hypoxic-ischaemic insult occurring around the time of birth may result in an encephalopathic state characterised by the need for resuscitation at birth, neurological depression, seizures and electroencephalographic abnormalities. There is an increasing risk of death or neurodevelopmental abnormalities with more severe encephalopathy. Current management consists of maintaining physiological parameters within the normal range and treating seizures with anticonvulsants.</p> <p>Studies in adult and newborn animals have shown that a reduction of body temperature of 3–4°C after cerebral insults is associated with improved histological and behavioural outcome. Pilot studies in infants with encephalopathy of head cooling combined with mild whole body hypothermia and of moderate whole body cooling to 33.5°C have been reported. No complications were noted but the group sizes were too small to evaluate benefit.</p> <p>Methods/Design</p> <p>TOBY is a multi-centre, prospective, randomised study of term infants after perinatal asphyxia comparing those allocated to "intensive care plus total body cooling for 72 hours" with those allocated to "intensive care without cooling".</p> <p>Full-term infants will be randomised within 6 hours of birth to either a control group with the rectal temperature kept at 37 +/- 0.2°C or to whole body cooling, with rectal temperature kept at 33–34°C for 72 hours. Term infants showing signs of moderate or severe encephalopathy +/- seizures have their eligibility confirmed by cerebral function monitoring. Outcomes will be assessed at 18 months of age using neurological and neurodevelopmental testing methods.</p> <p>Sample size</p> <p>At least 236 infants would be needed to demonstrate a 30% reduction in the relative risk of mortality or serious disability at 18 months.</p> <p>Recruitment was ahead of target by seven months and approvals were obtained allowing recruitment to continue to the end of the planned recruitment phase. 325 infants were recruited.</p> <p>Primary outcome</p> <p>Combined rate of mortality and severe neurodevelopmental impairment in survivors at 18 months of age. Neurodevelopmental impairment will be defined as any of:</p> <p>• Bayley mental developmental scale score less than 70</p> <p>• Gross Motor Function Classification System Levels III – V</p> <p>• Bilateral cortical visual impairments</p> <p>Trial Registration</p> <p>Current Controlled Trials ISRCTN89547571</p

Ability of early neurological assessment and continuous EEG to predict long term neurodevelopmental outcome at 5 years in infants following hypoxic-ischaemic encephalopathy

Hypoxic-ischaemic encephalopathy (HIE) symptoms evolve during the first days of life and their monitoring is critical for treatment decisions and long-term outcome predictions. This thesis aims to report the five-year outcome of a HIE cohort born in the pre-therapeutic hypothermia era and to evaluate the predictive value of (a) neonatal neurological and EEG markers and (b) development in the first 24 months, for outcome. Methods: Participants were recruited at age five from two birth cohorts; HIE and Comparison. Repeated neonatal neurological assessments using the Amiel-TisonNeurological-Assessment-at-Term, continuous video EEG monitoring in the first 72 hours, and Sarnat grading at 24 hours were recorded. EEG severity grades were assigned at 6, 12 and 24 hours. Development was assessed in the HIE cohort at 6, 12 and 24 months using the Griffiths Mental Development (0-2) Revised Scales. At age five, intellectual (WPPSI-IIIUK scale), neuropsychological (NEPSY-II scales), neurological and ophthalmic testing was completed. Results: 5-year outcomes were available for 81.5% (n=53) of HIE and 71.4% (n=30) of Comparison cohorts. In HIE, 47.2% (27% mild, 47% moderate, 83% severe Sarnat), had non-intact outcome vs. 3.3% of the Comparison cohort. Non-intact outcome rates by 6-hour EEG-grade were: grade0=3%, grade1=25%, grade2=54%, grade3/4=79%. In HIE, processing speed (p=0.01) and verbal short-term memory (p=0.005) were below test norms. No significant differences were found in IQ, NEPSY-II or ocular biometry scores between children following mild and moderate HIE. Median IQ scores for mild (99(94-112),p=grade 2) at 24hours had superior positive predictive value (74%; AUROC(95%CI)=0.70(0.55-0.85) for non-intact 5-year outcome than abnormal EEG at 6 hours (68%; AUROC(95%CI)=0.71(0.56-0.87). Within-child development scores were inconsistent across the first 24 months. Although all children with intact 24-month Griffiths quotient (n=30) had intact 5-year IQ, 8/30 had non-intact overall outcome. Conclusion: Predictive value of neonatal neurological assessments and an EEG grading system for outcome was confirmed. Intact early childhood outcomes post-HIE may mask subtle adverse neuropsychological sequelae into the school years. This thesis supports emerging evidence that mild-grade HIE is not a benign condition and its inclusion in studies of neuroprotective treatments for HIE is warranted