scholarly journals Seizure Diaries and Forecasting With Wearables: Epilepsy Monitoring Outside the Clinic

2021 ◽  
Vol 12 ◽  
Author(s):  
Benjamin H. Brinkmann ◽  
Philippa J. Karoly ◽  
Ewan S. Nurse ◽  
Sonya B. Dumanis ◽  
Mona Nasseri ◽  
...  

It is a major challenge in clinical epilepsy to diagnose and treat a disease characterized by infrequent seizures based on patient or caregiver reports and limited duration clinical testing. The poor reliability of self-reported seizure diaries for many people with epilepsy is well-established, but these records remain necessary in clinical care and therapeutic studies. A number of wearable devices have emerged, which may be capable of detecting seizures, recording seizure data, and alerting caregivers. Developments in non-invasive wearable sensors to measure accelerometry, photoplethysmography (PPG), electrodermal activity (EDA), electromyography (EMG), and other signals outside of the traditional clinical environment may be able to identify seizure-related changes. Non-invasive scalp electroencephalography (EEG) and minimally invasive subscalp EEG may allow direct measurement of seizure activity. However, significant network and computational infrastructure is needed for continuous, secure transmission of data. The large volume of data acquired by these devices necessitates computer-assisted review and detection to reduce the burden on human reviewers. Furthermore, user acceptability of such devices must be a paramount consideration to ensure adherence with long-term device use. Such devices can identify tonic–clonic seizures, but identification of other seizure semiologies with non-EEG wearables is an ongoing challenge. Identification of electrographic seizures with subscalp EEG systems has recently been demonstrated over long (>6 month) durations, and this shows promise for accurate, objective seizure records. While the ability to detect and forecast seizures from ambulatory intracranial EEG is established, invasive devices may not be acceptable for many individuals with epilepsy. Recent studies show promising results for probabilistic forecasts of seizure risk from long-term wearable devices and electronic diaries of self-reported seizures. There may also be predictive value in individuals' symptoms, mood, and cognitive performance. However, seizure forecasting requires perpetual use of a device for monitoring, increasing the importance of the system's acceptability to users. Furthermore, long-term studies with concurrent EEG confirmation are lacking currently. This review describes the current evidence and challenges in the use of minimally and non-invasive devices for long-term epilepsy monitoring, the essential components in remote monitoring systems, and explores the feasibility to detect and forecast impending seizures via long-term use of these systems.

2020 ◽  
Vol 116 (13) ◽  
pp. 2040-2054 ◽  
Author(s):  
Evangelos K Oikonomou ◽  
Musib Siddique ◽  
Charalambos Antoniades

Abstract Rapid technological advances in non-invasive imaging, coupled with the availability of large data sets and the expansion of computational models and power, have revolutionized the role of imaging in medicine. Non-invasive imaging is the pillar of modern cardiovascular diagnostics, with modalities such as cardiac computed tomography (CT) now recognized as first-line options for cardiovascular risk stratification and the assessment of stable or even unstable patients. To date, cardiovascular imaging has lagged behind other fields, such as oncology, in the clinical translational of artificial intelligence (AI)-based approaches. We hereby review the current status of AI in non-invasive cardiovascular imaging, using cardiac CT as a running example of how novel machine learning (ML)-based radiomic approaches can improve clinical care. The integration of ML, deep learning, and radiomic methods has revealed direct links between tissue imaging phenotyping and tissue biology, with important clinical implications. More specifically, we discuss the current evidence, strengths, limitations, and future directions for AI in cardiac imaging and CT, as well as lessons that can be learned from other areas. Finally, we propose a scientific framework in order to ensure the clinical and scientific validity of future studies in this novel, yet highly promising field. Still in its infancy, AI-based cardiovascular imaging has a lot to offer to both the patients and their doctors as it catalyzes the transition towards a more precise phenotyping of cardiovascular disease.


2017 ◽  
Vol 37 (05) ◽  
pp. 485-502 ◽  
Author(s):  
Camille Chatelle ◽  
Brian Edlow ◽  
Yelena Bodien

AbstractSevere brain injury may cause disruption of neural networks that sustain arousal and awareness, the two essential components of consciousness. Despite the potentially devastating immediate and long-term consequences, disorders of consciousness (DoC) are poorly understood in terms of their underlying neurobiology, the relationship between pathophysiology and recovery, and the predictors of treatment efficacy. Recent advances in neuroimaging techniques have enabled the study of network connectivity, providing great potential to improve the clinical care of patients with DoC. Initial discoveries in this field were made using positron emission tomography (PET). More recently, functional magnetic resonance (fMRI) techniques have added to our understanding of functional network dynamics in this population. Both methods have shown that whether at rest or performing a goal-oriented task, functional networks essential for processing intrinsic thoughts and extrinsic stimuli are disrupted in patients with DoC compared with healthy subjects. Atypical connectivity has been well established in the default mode network as well as in other cortical and subcortical networks that may be required for consciousness. Moreover, the degree of altered connectivity may be related to the severity of impaired consciousness, and recovery of consciousness has been shown to be associated with restoration of connectivity. In this review, we discuss PET and fMRI studies of functional and effective connectivity in patients with DoC and suggest how this field can move toward clinical application of functional network mapping in the future.


Nutrients ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 194
Author(s):  
Hong Tang ◽  
Hope Hui Rising ◽  
Manoranjan Majji ◽  
Robert D. Brown

This scoping review aimed to identify current evidence and gaps in the field of long-term space nutrition. Specifically, the review targeted critical nutritional needs during long-term manned missions in outer space in addition to the essential components of a sustainable space nutrition system for meeting these needs. The search phrase “space food and the survival of astronauts in long-term missions” was used to collect the initial 5432 articles from seven Chinese and seven English databases. From these articles, two independent reviewers screened titles and abstracts to identify 218 articles for full-text reviews based on three themes and 18 keyword combinations as eligibility criteria. The results suggest that it is possible to address short-term adverse environmental factors and nutritional deficiencies by adopting effective dietary measures, selecting the right types of foods and supplements, and engaging in specific sustainable food production and eating practices. However, to support self-sufficiency during long-term space exploration, the most optimal and sustainable space nutrition systems are likely to be supported primarily by fresh food production, natural unprocessed foods as diets, nutrient recycling of food scraps and cultivation systems, and the establishment of closed-loop biospheres or landscape-based space habitats as long-term life support systems.


Medicina ◽  
2021 ◽  
Vol 57 (8) ◽  
pp. 792
Author(s):  
Eva Burkhardt ◽  
Andrea Pfennig ◽  
Karolina Leopold

The early recognition of psychiatric disorders has been a focus of research in the last decades and has led to improvements in clinical care, especially in the area of early psychosis. Like non-affective psychosis, bipolar disorders are often diagnosed with a delay that can lead to long periods of untreated illness and impact long-term outcomes. This article presents the rationale for early recognition in bipolar disorder and presents the current evidence for the identification of risk factors, their assessment and validity in predicting the onset of bipolar disorder.


2017 ◽  
Vol 14 (4) ◽  
pp. 441-452 ◽  
Author(s):  
Sofia Wenzler ◽  
Christian Knochel ◽  
Ceylan Balaban ◽  
Dominik Kraft ◽  
Juliane Kopf ◽  
...  

Depression is a common neuropsychiatric manifestation among Alzheimer’s disease (AD) patients. It may compromise everyday activities and lead to a faster cognitive decline as well as worse quality of life. The identification of promising biomarkers may therefore help to timely initiate and improve the treatment of preclinical and clinical states of AD, and to improve the long-term functional outcome. In this narrative review, we report studies that investigated biomarkers for AD-related depression. Genetic findings state AD-related depression as a rather complex, multifactorial trait with relevant environmental and inherited contributors. However, one specific set of genes, the brain derived neurotrophic factor (BDNF), specifically the Val66Met polymorphism, may play a crucial role in AD-related depression. Regarding neuroimaging markers, the most promising findings reveal structural impairments in the cortico-subcortical networks that are related to affect regulation and reward / aversion control. Functional imaging studies reveal abnormalities in predominantly frontal and temporal regions. Furthermore, CSF based biomarkers are seen as potentially promising for the diagnostic process showing abnormalities in metabolic pathways that contribute to AD-related depression. However, there is a need for standardization of methodological issues and for replication of current evidence with larger cohorts and prospective studies.


2021 ◽  
Vol 13 ◽  
pp. 1759720X2110069
Author(s):  
Rebecca J. Moon ◽  
Elizabeth M. Curtis ◽  
Stephen J. Woolford ◽  
Shanze Ashai ◽  
Cyrus Cooper ◽  
...  

Optimisation of skeletal mineralisation in childhood is important to reduce childhood fracture and the long-term risk of osteoporosis and fracture in later life. One approach to achieving this is antenatal vitamin D supplementation. The Maternal Vitamin D Osteoporosis Study is a randomised placebo-controlled trial, the aim of which was to assess the effect of antenatal vitamin D supplementation (1000 IU/day cholecalciferol) on offspring bone mass at birth. The study has since extended the follow up into childhood and diversified to assess demographic, lifestyle and genetic factors that determine the biochemical response to antenatal vitamin D supplementation, and to understand the mechanisms underpinning the effects of vitamin D supplementation on offspring bone development, including epigenetics. The demonstration of positive effects of maternal pregnancy vitamin D supplementation on offspring bone development and the delineation of underlying biological mechanisms inform clinical care and future public-health policies.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Aaro Salosensaari ◽  
Ville Laitinen ◽  
Aki S. Havulinna ◽  
Guillaume Meric ◽  
Susan Cheng ◽  
...  

AbstractThe collection of fecal material and developments in sequencing technologies have enabled standardised and non-invasive gut microbiome profiling. Microbiome composition from several large cohorts have been cross-sectionally linked to various lifestyle factors and diseases. In spite of these advances, prospective associations between microbiome composition and health have remained uncharacterised due to the lack of sufficiently large and representative population cohorts with comprehensive follow-up data. Here, we analyse the long-term association between gut microbiome variation and mortality in a well-phenotyped and representative population cohort from Finland (n = 7211). We report robust taxonomic and functional microbiome signatures related to the Enterobacteriaceae family that are associated with mortality risk during a 15-year follow-up. Our results extend previous cross-sectional studies, and help to establish the basis for examining long-term associations between human gut microbiome composition, incident outcomes, and general health status.


Diagnostics ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 900
Author(s):  
Krasimir Kostov ◽  
Alexander Blazhev

Thickening of the vascular basement membrane (BM) is a fundamental structural change in the small blood vessels in diabetes. Collagen type IV (CIV) is a major component of the BMs, and monitoring the turnover of this protein in type 2 diabetes (T2D) can provide important information about the mechanisms of vascular damage. The aim of the study was through the use of non-invasive biomarkers of CIV (autoantibodies, derivative peptides, and immune complexes) to investigate vascular turnover of CIV in patients with long-term complications of T2D. We measured serum levels of these biomarkers in 59 T2D patients with micro- and/or macrovascular complications and 20 healthy controls using an ELISA. Matrix metalloproteinases-2 and -9 (MMP-2 and MMP-9) were also tested. In the T2D group, significantly lower levels of CIV markers and significantly higher levels of MMP-2 and MMP-9 were found compared to controls. A significant positive correlation was found between IgM antibody levels against CIV and MMP-2. These findings suggest that vascular metabolism of CIV is decreased in T2D with long-term complications and show that a positive linear relationship exists between MMP-2 levels and CIV turnover in the vascular wall.


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