EpilConNet: A Novel Multi-Class Epileptic Seizure Classification Model

Clinical Neurophysiology: EEG–Video Monitoring

Diet and nutrition apps are among the most popular health and fitness apps used by an increasing number of mobile device users. Undeniably, health and nutrition are some of the valuable aspects of life. With the introduction of mobile computing, health knowledge became much easier to understand due to its mobility and usability. A vast range of smartphone apps is emerging for tracking health and food. However, the existing mobile applications in Malaysia are lacking some important features. To address this limitation, the present mobile application responds by attempting to design and develop a Malaysian mobile nutrition application known as EatNTrack. EatNTrack is a mobile nutrition application that provides crucial features such as the ability to capture the food especially Malaysian foods, scanning food barcode, set the goal and calories of the day, a reminder for the user to capture the food, monthly progress of user, and integration with a wearable device. The needs of these features will give insight into many aspects of a user's eating habits. The more specific and accurate users with reporting, the more accurate their information will be. The aim of the study was to establish an innovative mobile-based dietary awareness tool that could be used to monitor target users' food intake.
 Keywords: nutrition, mobile application, food calories, track calories, health

Youth with chronic illnesses are at risk for decreased overall quality of life. A key component to enhancing quality of life is recognizing that comprehensive care addressing psychosocial factors is critical. Therefore, health professionals, parents/guardians, teachers, and other supportive adults should aim to incorporate strategies presented in this review in existing treatment plans. This review addresses specific strategies health professionals can use to improve the quality of life of youth with chronic illnesses. Specifically the following questions were explored: 1) What are hospital-based strategies that can enhance the overall quality of life of youth with chronic illnesses? 2) What are school-based strategies that can enhance the overall quality of life of youth with chronic illnesses? 3) What are community-based strategies that can enhance the overall quality of life of youth with chronic illnesses? This review outlines effective strategies for ensuring youth with chronic illnesses receive the proper care they need in hospital, school, and community settings.

Do recurrent seizures cause neuronal damage? A series of studies with MRI volumetry in adults with partial epilepsy

The Effectiveness of Internet and Mobile Applications in English Language Learning for Health Sciences’ Students in a University in the United Arab Emirates

Sleep quality refers to how well a person sleeps during the night. There are many factors that can affect sleep quality, including stress, anxiety, diet, exercise, and environmental factors such as noise and light levels. Good sleep quality is essential for overall quality of life. Poor sleep quality can have a number of detrimental impacts on one's physical as well as mental health. To improve sleep quality, it is important to establish a consistent sleep routine. There are many existing works on sleep quality prediction from wearable device data. Few of those analyzed sleep quality using the same algorithms used in this study. Several machine learning algorithms, however, have been proposed to reach great accuracy. Overfitting and insufficient data availability are common problems for these models. This research aims to increase the accuracy and performance of models for predicting sleep quality using wearable device data. To overcome these challenges, the objective of proposed work is to develop a sleep quality prediction system using a combination of feature selection techniques and machine learning models. The methodology is divided into three parts: data preprocessing, model building, and model evaluation. Three types of models were proposed in this study: single models, hybrid models, and an ensemble model for training and validation. The data acquired from a wearable IoT device was preprocessed by eliminating outliers and normalizing the data. The models were trained and evaluated based on accuracy, precision, recall, and F1-Score. The results show that the ensemble model was superior to all other models in terms of accuracy and F1-Score of 0.9897 and 0.9745 respectively. The hybrid models had lower performance metrics compared to the ensemble model, but still performed better than the individual models. This research provides insights into the potential of using wearable devices for sleep quality prediction and demonstrates the effectiveness of combining different models for improved accuracy and performance.

Objectives: To investigate the use of whole brain voxel based morphometry (VBM) and stereological analysis to study brain morphology in patients with medically intractable temporal lobe epilepsy; and to determine...

Approximately one third of patients with epilepsy continue to experience seizure despite the prescription of appropriate doses of anti-epileptic drugs. The objective of this study was to assess treatment outcomes and associated factors for poor treatment outcomes among patients taking anti-epileptic drugs at Ambo Hospital, West Shewa, Ethiopia. A hospital based cross–sectional study was conducted. Verbal consent from participants was taken before interview. Fifty-nine patients (44.7%) had poor seizure control. The most common seizure triggering factors were emotional stress (97.4%), sleep deprivation (78.1%), missing meal (29.8%)and missing medication (21.9%). Seventy one patients (53.8%) were non-adherent to medication. Therefore there is significant association between level of adherence (P=0.001), number of seizure attacks before anti-epileptic drugs initiation (p=0.028), electroencephalogram(neurologic abnormality) (p=0.04) and age at onset of seizure (diagnosis) (p=0.026). Poor treatment outcomes among epileptic patients is associated with level of adherence, number of seizure attacks before anti-epileptic drugs initiations, electroencephalogram(neurologic abnormality) and age at onset of seizure (diagnosis). The most common seizure triggering factors were emotional distress, sleep deprivation, missing meal, missing medication and noise. Strict medication adherence evaluation and enhancement through continues health education, close follow up with multidisciplinary approach are fundamental to the successful management of epileptic patients.

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI-COLUMBIA AT REQUEST OF AUTHOR.] The use of opt-in panel for health research and smartphones are still in their infancy, and the impact of how opt-in panel members share their health data for a different purpose for research is not yet well explored more specifically data from consumer wearable devices. Thus, we implemented the eCaregiving study, a two-phase feasibility study, to assesses opt-in panel members' behavior to share their health data with researchers and establish a linkage between consumer wearable devices data and self-reported outcome. The first phase was about assessing opt-in panel members to share their patient health data and their interest to participate in sharing their wearable devices' data using a survey questionnaire -- the panel is composed of healthy non-Hispanic white mothers. The second phase of eCaregiving was to recruit those who expressed interest in sharing their wearable device data and participate in the self-reported outcome mobile survey questionnaire. We grouped our participants into those who use Fitbit and those who do not use any wearable devices, and the later was given a Fitbit Charger HR as an incentive for their participation. Although we targeted fifty participants from each group, we were able to recruit only five participants from those who use Fitbit, and we achieved our target for those who never used any wearable device. The feasibility study showed that the interest to participate in the study did not translate into actual participation. Although we gave incentives to these participants, we found a discrepancy in the actual participation, and this discrepancy warranted further studies to determine the exact reasons for non-participation. Throughout this study, our participants received minimal guidance and training on how to use wearables devices or how to synchronize their device with the mobile application -- e4 research app. We found that mobile survey has better participation, attrition, and completion rate and completion time than the traditional surveys. We also investigated the data quality from the consumer wearable device, and we found that number of days captured of step count is significant. We also found that the number of sleep hours captured is low, but they are better than another controlled study where the participants have trained to use these consumer wearable devices. All in all, our study can be used as a guideline for future studies on mhealth and wearable devices to develop efficient protocols to maximize data quality from wearable devices and mobile surveys. The study provides a systematic approach to recruit and link subjective and objective data for more actionable insight. Besides, we reported the impact of incentives on the participation rate and the attrition rate in mobile surveys. Overall, mobile surveys and wearable devices can complement each other and enhance our understanding of the overall daily activity of our participants. The remaining of this thesis is structured as follows; the first chapter introduces the first paper entitled non-Hispanic white mothers' willingness to share personal health data with researchers: survey results from an opt-in panel. The final chapter introduces the second paper entitled study on the feasibility of collecting consumer wearable and mobile survey data to assess physical and mental health status -- data quality and study chall

ForeSeiz: An IoMT based headband for Real-time epileptic seizure forecasting

A proposal for a machine-learning algorithm for the prediction of seizure recurrence risk at 2 years after discontinuation of anti-seizure medications.

Seizure frequency affects event-related potentials(P300) in epilepsy

Magnetic resonance-guided laser interstitial thermal therapy (MRgLITT) is a minimally invasive alternative to open resection for pediatric drug-resistant epilepsy (DRE). This systematic review and individual participant data meta-analysis aimed to identify independent predictors of seizure outcomes and operative and neurological complications following MRgLITT. Uni- and multivariable mixed-effects Cox proportional-hazards regressions models were used to identify independent predictors of time to seizure recurrence following MRgLITT. Among patients with at least 12 months of follow-up, uni- and multivariable mixed-effects logistic regression analyses were conducted to ascertain the independent risk factors associated with seizure recurrence at last follow-up, operative complications, and postoperative neurological complications. A literature review identified 354 pediatric patients with a mean epilepsy duration of 7.5 (SD 5.3) years prior to MRgLITT. The mean age at seizure onset was 4.52 (SD 4.69) years, and focal seizures were more common (85.5%) than generalized seizures (14.5%). Lesions were detected on MRI in 82.1% of cases. The most common epilepsy etiologies were hypothalamic hamartoma (HH; 23.7%) and malformations of cortical development (23.7%). The mean follow-up duration after MRgLITT was 16.02 (SD 11.63) months. Engel class I outcomes were achieved in 57% of patients. In 205 cases where information was available regarding postoperative neurological complications, 35 patients (17.1%) experienced postoperative neurological complications, with hemiparesis as the most frequent complication (n = 16 patients). Of the 354 total patients who underwent MRgLITT, 8.2% underwent revision epilepsy surgery. No operative or clinical characteristics were associated with seizure recurrence. Seizure freedom probability was significantly higher among patients with HH compared to those with nonlesional MRI (p = 0.012). Patients with mesial temporal sclerosis experienced earlier seizure recurrence (p = 0.023), and an extratemporal surgical location was associated with longer seizure freedom probability (p = 0.034). Lesional MRI was associated with reduced odds of postoperative neurological complications (p = 0.031). MRgLITT may be a safe and effective alternative option for pediatric DRE. Further prospective studies are warranted to elucidate MRgLITT strategies in pediatric DRE.

In its classic presentation, Hashimoto's encephalopathy is an acute-subacute complex neuropsychiatric syndrome with cognitive impairment, hallucinations, myoclonus, tremor or ataxia, associated with elevated anti-thyroid antibodies. Corticoids and immunotherapy are dramatically effective. However, in some cases, not all the associated features are presented and this delays diagnosis and appropriate treatment. We describe a man with abrupt onset of recurrent auditory seizures resulting in refractory non-convulsive status epilepticus. The patient was diagnosed with an autoimmune encephalopathy with elevated serum and CSF anti-thyroid antibodies. None of the antiepileptic drugs were successful, however, following immune-modulating therapy, the refractory non-convulsive status epilepticus dramatically improved, as did the patient overall. We suggest that Hashimoto's encephalopathy should be suspected in otherwise healthy patients with unexplained new-onset focal recurrent auditory seizures which do not respond to antiepileptic drugs. The presence of anti-thyroid antibodies in the CSF supports this diagnosis.

Persons with chronic disease such as epilepsy, where a cure is not attainable and therapy may be prolonged, quality of life (QoL) has come to be seen as an important goal. The objective of this study was to identify scores of quality of life (QoL related to clinical factors. A cross-sectional study using QOLIE-31 instrument to identify quality of life among ambulatory epileptic patients at Epileptic Clinic of Department of Neurology-Cipto Mangunkusumo Hospital. Samples were taken consecutively from August 2005 to December 2005. Several demographic data as well as clinical were collected. QOLIE-31 components consisted of seizure worry, overall quality of life, emotional well-being, energy/fatigue, cognitive function, medication effect and social function. We found among 145 subjects the total score of QOLIE-31 ranged from 28-95 (mean = 67.6; standard of deviation = 14.55). The total score of QOLIE-31was corelated with low education, more frequent of seizures, antiepileptic drug politherapy and type of generalized seizure. antiepileptic drug politherapy was the most dominant risk factor for lowering total score of QOLIE-31. Our finding was in accordance with previous studies in India, Georgia, South Korea. In additioin we found that education was also a risk factor for total score of QOLIE-31. (Med J Indones 2007; 16:101-3) Keyword: epilepsy, quality of life, QOLIE-31, risk factors