Andrea Biondi

King's College London | KCL · Department of Clinical Neuroscience

Background: The health management of patients with epilepsy could be improved by wearing devices that reliably detect when epileptic seizures happen. For the devices to be widely adopted, they must be acceptable and easy to use for patients, and their views are very important. Previous studies have collected feedback from patients on hypothetical...

Robust biomarkers for anti-epileptic drugs (AEDs) activity in the human brain are essential to increase the probability of successful drug development. The frequency analysis of electroencephalographic (EEG) activity, either spontaneous or evoked by transcranial magnetic stimulation (TMS-EEG) can provide cortical readouts for AEDs. However, a syste...

In the last two decades new noninvasive mobile electroencephalography (EEG) solutions have been developed to overcome limitations of conventional clinical EEG and to improve monitoring of patients with long‐term conditions. Despite the availability of mobile innovations, their adoption is still very limited. The aim of this study is to review the c...

Background Epileptic seizures are spontaneous events that severely affect the lives of patients due to their recurrence and unpredictability. The integration of new wearable and mobile technologies to collect electroencephalographic (EEG) and extracerebral signals in a portable system might be the solution to prospectively identify times of seizure...

Objective Novel subcutaneous electroencephalography (sqEEG) systems enable prolonged, near-continuous cerebral monitoring in real-world conditions. Nevertheless, the feasibility, acceptability and overall clinical utility of these systems remains unclear. We report on the longest observational study using ultra long-term sqEEG to date. Methods We c...

Objective Wearable nonelectroencephalographic biosignal recordings captured from the wrist offer enormous potential for seizure monitoring. However, signal quality remains a challenging factor affecting data reliability. Models trained for seizure detection depend on the quality of recordings in peri‐ictal periods in performing a feature‐based sepa...

Background: Novel mobile and portable EEG solutions, designed for short and long-term monitoring of individuals with epilepsy have been developed in recent years but, they are underutilized, lacking full integration into clinical routine. Exploring the opinions of hospital-based healthcare professionals regarding their potential application, techni...

People with epilepsy frequently under- or inaccurately report their seizures, which poses a challenge for evaluating their treatment. The introduction of epilepsy health apps provides a novel approach that could improve seizure documentation. This study assessed the documentation performance of an app-based seizure diary and a conventional paper se...

Objective: This paper aims to investigate the possibility of detecting tonic-clonic seizures (TCSs) with behind-the-ear, two-channel wearable electroencephalography (EEG), and to evaluate its added value to non-EEG modalities in TCS detection. Methods: We included 27 participants with a total of 44 TCSs from the European multicenter study SeizeIT2....

Background Wearable devices and smartphone apps can record multiple signals relating to seizure cycles and other outcomes in epilepsy. We developed EEG@HOME to incorporate mobile EEG into a monitoring system. We report here one representative participant. Materials & Methods A 64-year-old woman with epilepsy used a FitBit continuously, collected 10...

Purpose: Electroencephalography (EEG) can be considered the gold standard diagnostic technique for selflimited epilepsy with centrotemporal spikes (SeLECTS). Recent studies built functional brain networks from EEG recordings to understand patterns of connectivity between brain areas of interest. In this study, we applied graph theory metrics to fu...

Wearable recordings of neurophysiological signals captured from the wrist offer enormous potential for seizure monitoring. Yet, data quality remains one of the most challenging factors that impact data reliability. We suggest a combined data quality assessment tool for the evaluation of multimodal wearable data. We analyzed data from patients with...

Epilepsy is one of the most common neurological disorders, characterized by the occurrence of repeated seizures. Given that epilepsy is considered a network disorder, tools derived from network neuroscience may confer the valuable ability to quantify the properties of epileptic brain networks. In this study, we use well-established brain network me...

Epilepsy is one of the most common neurological disorders, characterized by the occurrence of repeated seizures. Given that epilepsy is considered a network disorder, tools derived from network neuroscience may confer the valuable ability to quantify properties of epileptic brain networks. In this study we use well-established brain network metrics...

Background Several studies have shown that in people with epilepsy, brain network features computed from interictal scalp EEG recordings could serve as potential biomarkers for epilepsy diagnosis. In addition, evolving brain networks derived from intracranial EEG recordings have shown topological changes prior to seizure occurrence. Question Here...

This study describes a generalized cross‐patient seizure‐forecasting approach using recurrent neural networks with ultra‐long‐term subcutaneous EEG (sqEEG) recordings. Data from six patients diagnosed with refractory epilepsy and monitored with an sqEEG device were used to develop a generalized algorithm for seizure forecasting using long short‐ter...

Objective One of the most disabling aspects of living with chronic epilepsy is the unpredictability of seizures. Cumulative research in the past decades has advanced our understanding of the dynamics of seizure risk. Technological advances have recently made it possible to record pertinent biological signals, including electroencephalogram (EEG), c...

Background: Transcranial magnetic stimulation can be combined with electromyography (TMS-EMG) and electroencephalography (TMS-EEG) to evaluate the excitatory and inhibitory functions of the cerebral cortex in a standardized manner. It has been postulated that schizophrenia is a disorder of functional neural connectivity underpinned by a relative i...

People with drug-resistant focal epilepsy often undergo epilepsy surgery with the aim to become seizure free. Part of the presurgical evaluation is the patient admission to the hospital for a multiday video-EEG monitoring where the patient is expected to manifest multiple seizures. The correct lateralization of the seizure focus is enhanced by the...

Purpose: Evaluate the acceptability and feasibility of a procedure (EEG@HOME) that allows patients with epilepsy to independently, remotely, and continuously acquire non-invasive variables at home. Method: Adults with pharmaco-resistant epilepsy were recruited at King’s College Hospital, London. Participants were trained for one week to self-apply...

The Wearables for Epilepsy And Research (WEAR) International Study Group identified a set of methodology standards to guide research on wearable devices for seizure detection. We formed an international consortium of experts from clinical research, engineering, computer science, and data analytics at the beginning of 2020. The study protocols and p...

Purpose: Focal seizures constitute the most common seizure type and are associated with poor control. One of the major difficulties in detecting focal onset with wearable devices seizures is related to their phenomenological complexity. We aimed at capturing focal onset seizures with motor manifestations with a multimodal wearable device to identif...

Background In recent years, a growing body of literature has highlighted the role of wearable and mobile remote measurement technology (RMT) applied to seizure detection in hospital settings, whereas more limited evidence has been produced in the community setting. In clinical practice, seizure assessment typically relies on self-report, which is k...

The frequency analysis of electroencephalographic (EEG) activity, either spontaneous or evoked by transcranial magnetic stimulation (TMS-EEG), is a powerful tool to investigate changes in brain activity and excitability following the administration of antiepileptic drugs (AEDs). However, a systematic evaluation of the effect of AEDs on spontaneous...

Purpose Wearable devices are progressively becoming an available tool for continuous seizure detection. Motivation to use wearables is not only driven by the accuracy and reliability of the performance but also by the form factor, comfort, and stability on the body. We collected direct feedback and device placement-related issues experienced by a c...

BACKGROUND Epileptic seizures are spontaneous events that severely affect the lives of patients due to their recurrence and unpredictability. The integration of new wearable and mobile technology to collect EEG and extra-cerebral signals into a portable system might be the solution to prospectively identify times of seizure occurrence or propensity...

Purpose wearable devices aimed at detecting seizures are rapidly emerging. Continuous collection and optimal data quality are paramount to guarantee the acquisition of clinically meaningful data. It is still unknown how successfully patients can self-manage new technologies and which factors have an impact on this. We assessed the performance of pa...

BACKGROUND In recent years, a growing body of literature has highlighted the role of wearable and mobile remote measurement technology (RMT) applied to seizure detection in hospital settings, whereas more limited evidence has been produced in the community setting. In clinical practice, seizure assessment typically relies on self-report, which is k...

Noninvasive wearable devices have great potential to aid the management of epilepsy, but these devices must have robust signal quality, and patients must be willing to wear them for long periods of time. Automated machine learning classification of wearable biosensor signals requires quantitative measures of signal quality to automatically reject p...

Objective Movement‐based wearable sensors are used for detection of convulsive seizures. The identification of the absence of motion following a seizure, known as post‐ictal immobility (PI), may represent a potential additional application of wearables. PI has been associated with potentially life‐threatening complications and with sudden unexpecte...

Mental health disturbances are common after stroke and linked to a slower recovery. Current face-to-face treatment options are costly and often inaccessible. Technology advances have made it possible to overcome some of these barriers to deliver technology-based mental health interventions remotely, but we do not know how acceptable and feasible th...

Background: The health management of patients with epilepsy could be improved by wearing devices that reliably detect when epileptic seizures happen Developing a wearable device acceptable and usable from the patients’ viewpoint is crucial In previous studies feedback from people with epilepsy (has largely stemmed from discussing theoretical device...

Background: Innovative uses of mobile health (mHealth) technology for real-time measurement and management of epilepsy may improve the care provided to patients. For instance, seizure detection and quantifying related problems will have an impact on quality of life and improve clinical management for people experiencing frequent and uncontrolled s...

Purpose: To estimate the incidence of ictal hypoxemia (IH) and to identify clinical and study-related factors modulating the estimate. Methods: We searched articles recording concurrent peri-ictal and ictal EEG and Sp02 in adults and children with epilepsy. Studies reporting the total number of seizures recorded and the number of seizures with I...

Purpose: To estimate the incidence of pre-ictal heart rate (HR) manifestations and to identify clinical and study-related factors modulating the estimate. Methods: We searched articles recording concurrent pre-ictal EEG and HR in adults and children with epilepsy. Pre-ictal HR changes were classified as HR reduction (HRR) or increase (HRI). Stud...

The combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) has uncovered underlying mechanisms of two anti-epileptic medications: levetiracetam and lamotrigine. Despite their different mechanism of action, both drugs modulated TMS-evoked EEG potentials (TEPs) in a similar way. Since both medications increase resting m...

Brain responses to transcranial magnetic stimulation (TMS) as measured with electroencephalography (EEG) have so far been assessed either by TMS-evoked EEG potentials (TEPs), mostly reflecting phase-locked neuronal activity, or time-frequency-representations (TFRs), reflecting oscillatory power arising from a mixture of both evoked (i.e., phase-loc...

Objective: Antiepileptic drug (AED) treatment failures may occur because there is insufficient drug in the brain or because of a lack of relevant therapeutic response. Until now it has not been possible to measure these factors. It has been recently shown that the combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG...