Neuro-critical multimodal Edge-AI monitoring algorithm and IoT system design and development

In recent years, with the continuous development of neurocritical medicine, the success rate of treatment of patients with traumatic brain injury (TBI) has continued to increase, and the prognosis has also improved. TBI patients' condition is usually very complicated, and after treatment, patients often need a more extended time to recover. The degree of recovery is also related to prognosis. However, as a young discipline, neurocritical medicine still has many shortcomings. Especially in most hospitals, the condition of Neuro-intensive Care Unit (NICU) is uneven, the equipment has limited functionality, and there is no unified data specification. Most of the instruments are cumbersome and expensive, and patients often need to pay high medical expenses. Recent years have seen a rapid development of big data and artificial intelligence (AI) technology, which are advancing the medical IoT field. However, further development and a wider range of applications of these technologies are needed to achieve widespread adoption. Based on the above premises, the main contributions of this thesis are the following. First, the design and development of a multi-modal brain monitoring system including 8-channel electroencephalography (EEG) signals, dual-channel NIRS signals, and intracranial pressure (ICP) signals acquisition. Furthermore, an integrated display platform for multi-modal physiological data to display and analysis signals in real-time was designed. This thesis also introduces the use of the Qt signal and slot event processing mechanism and multi-threaded to improve the real-time performance of data processing to a higher level. In addition, multi-modal electrophysiological data storage and processing was realized on cloud server. The system also includes a custom built Django cloud server which realizes real-time transmission between server and WeChat applet. Based on WebSocket protocol, the data transmission delay is less than 10ms. The analysis platform can be equipped with deep learning models to realize the monitoring of patients with epileptic seizures and assess the level of consciousness of Disorders of Consciousness (DOC) patients. This thesis combines the standard open-source data set CHB-MIT, a clinical data set provided by Huashan Hospital, and additional data collected by the system described in this thesis. These data sets are merged to build a deep learning network model and develop related applications for automatic disease diagnosis for smart medical IoT systems. It mainly includes the use of the clinical data to analyze the characteristics of the EEG signal of DOC patients and building a CNN model to evaluate the patient's level of consciousness automatically. Also, epilepsy is a common disease in neuro-intensive care. In this regard, this thesis also analyzes the differences of various deep learning model between the CHB-MIT data set and clinical data set for epilepsy monitoring, in order to select the most appropriate model for the system being designed and developed. Finally, this thesis also verifies the AI-assisted analysis model.. The results show that the accuracy of the CNN network model based on the evaluation of consciousness disorder on the clinical data set reaches 82%. The CNN+STFT network model based on epilepsy monitoring reaches 90% of the accuracy rate in clinical data. Also, the multi-modal brain monitoring system built is fully verified. The EEG signal collected by this system has a high signal-to-noise ratio, strong anti-interference ability, and is very stable. The built brain monitoring system performs well in real-time and stability. Keywords: TBI, Neurocritical care, Multi-modal, Consciousness Assessment, seizures detection, deep learning, CNN, IoT

Behavioral Comorbidities and Drug Treatments in a Zebrafish scn1lab Model of Dravet Syndrome.

Loss-of-function mutations in SCN1A cause Dravet syndrome (DS), a catastrophic childhood epilepsy in which patients experience comorbid behavioral conditions, including movement disorders, sleep abnormalities, anxiety, and intellectual disability. To study the functional consequences of voltage-gated sodium channel mutations, we use zebrafish with a loss-of-function mutation in scn1lab, a zebrafish homolog of human SCN1A. Homozygous scn1labs552/s552 mutants exhibit early-life seizures, metabolic deficits, and early death. Here, we developed in vivo assays using scn1labs552 mutants between 3 and 6 d postfertilization (dpf). To evaluate sleep disturbances, we monitored larvae for 24 h with locomotion tracking software. Locomotor activity during dark (night phase) was significantly higher in mutants than in controls. Among anticonvulsant drugs, clemizole and diazepam, but not trazodone or valproic acid, decreased distance moved at night for scn1labs552 mutant larvae. To monitor exploratory behavior in an open field, we tracked larvae in a novel arena. Mutant larvae exhibited impaired exploratory behavior, with increased time spent near the edge of the arena and decreased mobility, suggesting greater anxiety. Both clemizole and diazepam, but not trazodone or valproic acid, decreased distance moved and increased time spent in the center of the arena. Counting inhibitory neurons in vivo revealed no differences between scn1labs552 mutants and siblings. Taken together, our results demonstrate conserved features of sleep, anxiety, and movement disorders in scn1lab mutant zebrafish, and provide evidence that a zebrafish model allows effective tests of treatments for behavioral comorbidities associated with DS

The heart of epilepsy: Cardiac comorbidity and sudden death

The research described in this thesis aims to increase understanding of cardiac comorbidities and sudden unexpected death in epilepsy (SUDEP). People with epilepsy have a three-fold increased risk of dying prematurely compared to the general population. Common contributors to this are cardiovascular comorbidities, of which I provide an overview. Cardiovascular conditions and epilepsy can both lead to transient loss of consciousness (TLOC) with overlapping semiology. Particularly, myoclonic jerks which are commonly observed during syncope can be mistaken for signs of epilepsy. A misdiagnosis with detrimental consequences. I provide evidence that a careful analysis of motor phenomena can distinguish the two conditions. SUDEP is the commonest direct epilepsy-related premature death (UK >500 people/year). It typically occurs following convulsive seizures (CS). Most victims are found prone and some suggested people should sleep supine. I assessed video-EEG recordings of 180 CS and demonstrated peri-ictal positions often change, and most ending prone turned during CS. Sleeping supine is thus unlikely to prevent a postictal prone position and reduce risk of SUDEP. Pathomechanisms underlying SUDEP are likely a combination of interacting cardiorespiratory and autonomic factors. People with Dravet syndrome (DS) have a particular high SUDEP risk. I show that 49% of reported deaths in DS are SUDEP cases, most <10 years (78%). In DS, SCN1A mutations are mostly found, encoding a sodium channel expressed in brain and heart. DS mouse models suggest a key role for peri-ictal cardiac arrhythmias in SUDEP. I conducted a multicentre observational study and recorded 547 seizures in 45 DS participants. No major peri-ictal arrhythmias were found. Peri-ictal QTc-lengthening was, however, more common in DS than controls. This may reflect unstable repolarisation and increased propensity for arrhythmias. Prospective data to determine whether these peri-ictal variables can predict SUDEP risk is warranted

Investigating epileptiform activity associated with slow wave sleep

PhD ThesisThe characteristic EEG trait of patients with nocturnal idiopathic epilepsies during childhood is the spike and wave discharge. Cognitive dysfunction is prevalent among these patients and is thought to be linked to disturbances in memory consolidation processes that normally occur during slow wave sleep. Several genetic mutations of nicotinic receptor subunits have been linked to these disorders. However, there is little known about the underlying mechanisms or the spatiotemporal characteristics of this epileptiform activity within the neocortex. This thesis presents a rat in vitro model of the epileptiform activity synonymous with nocturnal childhood epilepsies, that allows for pharmacological manipulation of receptor subunits linked to these disorders. The application of DTC [10 M], a non-selective, competitive nicotinic acetylcholine receptor antagonist, to an in vitro model of the cortical delta rhythm induced two individual forms of paroxysm events - wave discharges and the conventional spike and wave discharges. Pharmacological manipulation of this model suggest that the epileptiform activity is mediated by excitatory currents which is consistent with the use of glutamate antagonists as anticonvulsants. A blanket blockade of inhibition by a GABAA antagonist resulted in severe discharges, hence hugely increasing excitatory response. Only partial disinhibition is suggested to be required to generate epileptiform activity as nicotinic acetylcholine receptors and 5-HT3 receptors are located on dendrite targeting interneurons. Mapping of unit activity revealed the di erence between the two paroxysm events was recruitment of super cial layers with simultaneous paroxysm events in delta frequency-generating Layer V pyramidal cells. It is proposed that the hyperexcitability responsible for the generation of the spike component of a spike and wave discharge is mediated by the lack of excitatory tone in 5-HT3 and nicotinic acetylecholine receptor expressing inhibitory interneuron subtypes. The disinhibition, spike generation and disruption of interplay between deep and super cial layers of the neocortex is thought to be associated with synaptic plastic changes

Characterization and processing of novel neck photoplethysmography signals for cardiorespiratory monitoring

Epilepsy is a neurological disorder causing serious brain seizures that severely affect the patients' quality of life. Sudden unexpected death in epilepsy (SUDEP), for which no evident decease reason is found after post-mortem examination, is a common cause of mortality. The mechanisms leading to SUDEP are uncertain, but, centrally mediated apneic respiratory dysfunction, inducing dangerous hypoxemia, plays a key role. Continuous physiological monitoring appears as the only reliable solution for SUDEP prevention. However, current seizure-detection systems do not show enough sensitivity and present a high number of intolerable false alarms. A wearable system capable of measuring several physiological signals from the same body location, could efficiently overcome these limitations. In this framework, a neck wearable apnea detection device (WADD), sensing airflow through tracheal sounds, was designed. Despite the promising performance, it is still necessary to integrate an oximeter sensor into the system, to measure oxygen saturation in blood (SpO2) from neck photoplethysmography (PPG) signals, and hence, support the apnea detection decision. The neck is a novel PPG measurement site that has not yet been thoroughly explored, due to numerous challenges. This research work aims to characterize neck PPG signals, in order to fully exploit this alternative pulse oximetry location, for precise cardiorespiratory biomarkers monitoring. In this thesis, neck PPG signals were recorded, for the first time in literature, in a series of experiments under different artifacts and respiratory conditions. Morphological and spectral characteristics were analyzed in order to identify potential singularities of the signals. The most common neck PPG artifacts critically corrupting the signal quality, and other breathing states of interest, were thoroughly characterized in terms of the most discriminative features. An algorithm was further developed to differentiate artifacts from clean PPG signals. Both, the proposed characterization and classification model can be useful tools for researchers to denoise neck PPG signals and exploit them in a variety of clinical contexts. In addition to that, it was demonstrated that the neck also offered the possibility, unlike other body parts, to extract the Jugular Venous Pulse (JVP) non-invasively. Overall, the thesis showed how the neck could be an optimum location for multi-modal monitoring in the context of diseases affecting respiration, since it not only allows the sensing of airflow related signals, but also, the breathing frequency component of the PPG appeared more prominent than in the standard finger location. In this context, this property enabled the extraction of relevant features to develop a promising algorithm for apnea detection in near-real time. These findings could be of great importance for SUDEP prevention, facilitating the investigation of the mechanisms and risk factors associated to it, and ultimately reduce epilepsy mortality.Open Acces

Comparison of the Effects of Sensorimotor Rhythm and Slow Cortical Potential Neurofeedback in Epilepsy

Current conventional epilepsy treatments do not always aim to improve epilepsy comorbidities. For a treatment to be effective, is not necessary for it to keep the patient seizure-free; it is sufficient to show improvement in functions to help people who suffer from epilepsy to become more independent and productive in life. There is an urgent need to explore non- pharmaceutical/non-invasive interventions that can help in that regard. The earlier patients are treated with this condition, the more likely it is to prevent severe disabilities over time. Neurofeedback is a self-modulatory brain activity oscillatory intervention that previous researchers have found to reduce seizure frequency in patients with epilepsy. The aim of this work was to compare two Neurofeedback techniques that have shown some efficacy in improving symptoms in epilepsy. The novelty of this study is to explore further and included clinical, neurophysiological and cognitive outcomes in order to assess in more detail the effectiveness of epilepsy comorbidities. Forty-four patients, between the ages of 12 and 18 years, and diagnosed with focal epilepsy, divided randomly into three groups: sensorimotor rhythm (SMR) training, slow cortical potential (SCP) training, and control. The patients completed 25 sessions of intervention. The results showed that the SMR group training had an advantage in improving reaction time compared with SCP and control. Regression analysis revealed a significant correlation between the patients who learned to modify their brain activity in the SMR group and improving reaction time in two different tasks. In addition, the quality of life scale significantly improved in all three groups. The study supplies preliminary data to support that SMR neurofeedback training as an intervention should further be explored as a therapeutic option for children who suffer from focal epilepsy.CONACYT (Mexican Council of science and technology

"Investigation on the role of Cl- homeostasis and GABAergic transmission in sleep disorders of Down syndrome and in Prader Willi syndrome: a possible contributor to cognitive impairment"

GABA is the main inhibitory neurotransmitter of the central nervous system (CNS). Recently, GABAergic transmission has been reported to be depolarizing and possibly excitatory rather than inhibitory in a number of neurodevelopmental disorders both in patients and mouse models. In particular, the Ts65Dn mouse model of Down syndrome (DS) exhibits depolarizing GABA due to upregulation of the Cl- importer NKCC1 both in the hippocampus and in the cortex. Moreover, NKCC1 inhibition by the FDA-approved diuretic bumetanide is able to rescue inhibitory GABAergic transmission, synaptic plasticity and cognitive functions in Ts65Dn mice. Beside cognitive impairment, DS mice and people with DS show sleep disturbaces. Since sleep pattern is regulated by GABAergc transmission, we reasoned that the alteration of GABAergic transmission due to upregulation of NKCC1 might be underlying at least some of the sleep disturbances in DS mice. So, we characterized sleep in Ts65Dn mice and investigated the effects of a chronic treatment with bumetanide. We found that bumetanide ameliorates the quality of sleep in NREM and REM sleep phases before and after sleep deprivation and decreases abnormal wakefulness during light phase at baseline in Ts65Dn mice. Moreover, we also found abnormalities in other parameters, which could contribute to sleep abnormalities of Ts65Dn mice: an increase of food intake and activity (partially rescued by bumetanide) with a reduction of body temperature during dark phase. Because of the association of altered GABAergic signaling by dysregulation of the expression of NKCC1 (but also of the Cl- exporter KCC2) in many neurodevelopmental disorders characterized by cognitive or social impairment, and sleep disorders, we extended our studies to Prader Willi syndrome (PWS). PWS is a neurodevelopmental disorder, caused by defects of genomic imprinting and characterized by cognitive, social and sleep abnormalities. Here, we observed that the Snord116 5 mutant mouse model of PWS, PWScrm+/p 12 show an increased expression of NKCC1, specifically in the hippocampus in comparison to their wild-type mice. Moreover, we report that PWS mice have altered cognition and the circadian period in free-running conditions. In particular, mutant mice present defects of long-term memory and a reduced shortening of their circadian period together with an increase of alpha activity in dark-dark (DD). Moreover, they also show alteration of pain sensitivity, that could be linked to defects in the thermoregulation. Interestingly, in constrast with PWS people, Snord116 mutant mice showed no alterations of anxiety, repetivive, obsessive and social behaviors. In an effort to rescue cognition and the circadian phenotype by rescuing NKCC1 inhibition, we treated Snord116 mutant mice with bumetanide. Remarkably, bumetanide treatment resulted in a complete rescue of the cognitive defects and circadian alteration in DD, with no effects in controls. Our results suggest an important link between GABA transmission and the regulation of cognition and the circadian clock in PWS. In addition, the current study extends the repertoire of disorders in which NKCC1 inhibition attenuates behavioural deficits and proposes a new potential mechanism for the investigation of PWS