Focal Impaired Awareness Seizure Detection Using a Smartwatch

Epileptic seizures are commonly classified as either generalized (originating simultaneously in cortical neurons across the entire brain) or focal (originating in a subpopulation of cortical neurons in a focal brain region). Focal seizures are further subdivided according to whether the seizure causes impaired awareness (focal impaired), or does not (focal aware). Focal impaired awareness seizures cause more disability because patients cannot adequately react to their surroundings, increasing the risk of car crashes, burns, and other accidents. FIA seizures can also be accompanied by automatic behaviors, such as undressing or running, which can be embarrassing or dangerous. While treatments exist for epileptic patients with FIA seizures, tracking the efficacy of treatments can be difficult since patients often will not remember the episodes or recognize that one has occurred. In order to effectively track FIA seizures in epileptic patients, active detection that does not hinder daily life is needed. FIA seizures may originate in different regions of the brain and thus may have very different clinical manifestations across individuals. However, most cause an increase in heart rate, likely through stimulation of sympathetic efferents in the hypothalamus, without a commensurate increase in physical activity. Using a common consumer-grade smartwatch, the Apple Watch, we used a refined set of engineered features derived from the photoplethysmogram (PPG) heart rate sensor date and tri-axial accelerometer data to train neural networks to detect FIA seizures associated with an increase in heart rate. This strategy was based on our judgment that FIA seizures without an increase in heart rate are not sufficiently stereotyped across patients to detect with any of the available sensors in consumer wearable devices. A binary classification, artificial neural network was trained using leave-one-out cross-validation (LOOCV). Each of the models correctly identified the left-out FIA seizure within 30 seconds, but high false alarm rates prompted further development. Further training and the use of accumulation filtering allowed for a neural network model with 90% specificity, identifying 27 out of 30 total FIA seizures, and an overall false alarm rate of 1.65/hour with no false alarms during resting, running, or household chores

Hilbert-Huang Transform: biosignal analysis and practical implementation

Any system, however trivial, is subjected to data analysis on the signals it produces. Over the last 50 years the influx of new techniques and expansions of older ones have allowed a number of new applications, in a variety of fields, to be analysed and to some degree understood. One of the industries that is benefiting from this growth is the medical field and has been further progressed with the growth of interdisciplinary collaboration. From a signal processing perspective, the challenge comes from the complex and sometimes chaotic nature of the signals that we measure from the body, such as those from the brain and to some degree the heart. In this work we will make a contribution to dealing with such systems, in the form of a recent time-frequency data analysis method, the Hilbert-Huang Transform (HHT), and extensions to it. This thesis presents an analysis of the state of the art in seizure and heart arrhythmia detection and prediction methods. We then present a novel real-time implementation of the algorithm both in software and hardware and the motivations for doing so. First, we present our software implementation, encompassing realtime capabilities and identifying elements that need to be considered for practical use. We then translated this software into hardware to aid real-time implementation and integration. With these implementations in place we apply the HHT method to the topic of epilepsy (seizures) and additionally make contributions to heart arrhythmias and neonate brain dynamics. We use the HHT and some additional algorithms to quantify features associated with each application for detection and prediction. We also quantify significance of activity in such a way as to merge prediction and detection into one framework. Finally, we assess the real-time capabilities of our methods for practical use as a biosignal analysis tool

Classification of Epileptic Motor Manifestations and Detection of Tonic-Clonic Seizures With Acceleration Norm Entropy

International audienceIn this paper, three triaxis accelerometers positioned on the wrists and the head of epileptic patients submitted to long-term video electroencephalographic monitoring as part of presurgical investigation are evaluated to characterize the different classes of motor manifestations observed during seizures. Quadratic discriminant classifiers are trained on features extracted from 1 or 4 s windows. It is shown that a simple rule applied to the acceleration norm entropy HnA produces the best performances compared to other classifiers trained on other feature sets. The simple rule is as follows with values given in bits: (0 <; HnA <; 1.34), no movement; (1.34 <; HnA <; 3.87), tonic manifestations; (3.87 <; HnA), tonic-clonic manifestations. For this classifier, features are extracted from 1 s windows and the misclassification rate is 11% evaluated on 5 607 s of epileptic motor manifestations obtained from 58 seizures in 30 patients. A quantile normalization can improve the results with features based on absolute power spectral density but performances are not as good as the ones obtained with HnA. Based on the classifier using only HnA, a simple tonic-clonic seizure detector is proposed and produces a 80% sensitivity with a 95% specificity

Augmentation of Brain Function: Facts, Fiction and Controversy. Volume III: From Clinical Applications to Ethical Issues and Futuristic Ideas

The final volume in this tripartite series on Brain Augmentation is entitled “From Clinical Applications to Ethical Issues and Futuristic Ideas”. Many of the articles within this volume deal with translational efforts taking the results of experiments on laboratory animals and applying them to humans. In many cases, these interventions are intended to help people with disabilities in such a way so as to either restore or extend brain function. Traditionally, therapies in brain augmentation have included electrical and pharmacological techniques. In contrast, some of the techniques discussed in this volume add specificity by targeting select neural populations. This approach opens the door to where and how to promote the best interventions. Along the way, results have empowered the medical profession by expanding their understanding of brain function. Articles in this volume relate novel clinical solutions for a host of neurological and psychiatric conditions such as stroke, Parkinson’s disease, Huntington’s disease, epilepsy, dementia, Alzheimer’s disease, autism spectrum disorders (ASD), traumatic brain injury, and disorders of consciousness. In disease, symptoms and signs denote a departure from normal function. Brain augmentation has now been used to target both the core symptoms that provide specificity in the diagnosis of a disease, as well as other constitutional symptoms that may greatly handicap the individual. The volume provides a report on the use of repetitive transcranial magnetic stimulation (rTMS) in ASD with reported improvements of core deficits (i.e., executive functions). TMS in this regard departs from the present-day trend towards symptomatic treatment that leaves unaltered the root cause of the condition. In diseases, such as schizophrenia, brain augmentation approaches hold promise to avoid lengthy pharmacological interventions that are usually riddled with side effects or those with limiting returns as in the case of Parkinson’s disease. Brain stimulation can also be used to treat auditory verbal hallucination, visuospatial (hemispatial) neglect, and pain in patients suffering from multiple sclerosis. The brain acts as a telecommunication transceiver wherein different bandwidth of frequencies (brainwave oscillations) transmit information. Their baseline levels correlate with certain behavioral states. The proper integration of brain oscillations provides for the phenomenon of binding and central coherence. Brain augmentation may foster the normalization of brain oscillations in nervous system disorders. These techniques hold the promise of being applied remotely (under the supervision of medical personnel), thus overcoming the obstacle of travel in order to obtain healthcare. At present, traditional thinking would argue the possibility of synergism among different modalities of brain augmentation as a way of increasing their overall effectiveness and improving therapeutic selectivity. Thinking outside of the box would also provide for the implementation of brain-to-brain interfaces where techniques, proper to artificial intelligence, could allow us to surpass the limits of natural selection or enable communications between several individual brains sharing memories, or even a global brain capable of self-organization. Not all brains are created equal. Brain stimulation studies suggest large individual variability in response that may affect overall recovery/treatment, or modify desired effects of a given intervention. The subject’s age, gender, hormonal levels may affect an individual’s cortical excitability. In addition, this volume discusses the role of social interactions in the operations of augmenting technologies. Finally, augmenting methods could be applied to modulate consciousness, even though its neural mechanisms are poorly understood. Finally, this volume should be taken as a debate on social, moral and ethical issues on neurotechnologies. Brain enhancement may transform the individual into someone or something else. These techniques bypass the usual routes of accommodation to environmental exigencies that exalted our personal fortitude: learning, exercising, and diet. This will allow humans to preselect desired characteristics and realize consequent rewards without having to overcome adversity through more laborious means. The concern is that humans may be playing God, and the possibility of an expanding gap in social equity where brain enhancements may be selectively available to the wealthier individuals. These issues are discussed by a number of articles in this volume. Also discussed are the relationship between the diminishment and enhancement following the application of brain-augmenting technologies, the problem of “mind control” with BMI technologies, free will the duty to use cognitive enhancers in high-responsibility professions, determining the population of people in need of brain enhancement, informed public policy, cognitive biases, and the hype caused by the development of brain- augmenting approaches