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To be announced
Prof. Dr. Elsa Kirchner
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To be announced.
Prof. Dr. Patrique Fiedler
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Decoding Social Touch: EEG Signals Reveal Interdependent Somatosensory Pathways Relevant to Human Affect
Prof. Dr. Annett Schirmer
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Assessing the impact of analytical choices on EEG results: Insights from the EEGManyPipelines project
Prof. Dr. Claudia Gianelli & Dr. Elena Cesnaite
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Deep brain ultrasound stimulation : state of the art transcranial focusing and clinical applications
Prof. Jean-Francois Aubry
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Contribution of new methods for combined EEG/MEG source analysis and optimized mc-TES to focal medication-resistant epilepsy
Prof. Dr. Carsten Wolters
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To be announced.
Michael Funke, MD PhD
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Neuroplastic effects of EEG neurofeedback
Dr. Tomas Ros
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To be announced
Prof. Giorgio di Lorenzo
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Performance monitoring, post-error adjustments, and acetylcholine
Prof. Dr. med. habil. Markus Ullsperger
Andrea is a neuroscientist and psychologist with expertise in wearable technology, digital health, and psychophysiology. He currently manages the UK MND Register and King's MND Biobank, focusing on administrative operations, NHS site recruitment, research ethics, and data collection governance.
Previously, Andrea was a research associate at King’s College London on the IMPARTS project, supervised by Prof Mark Richardson and Prof Deb Pal. The project aimed to bridge the gap between mental and physical health care in epilepsy management. During his PhD in Clinical Neuroscience, Andrea led the EEG@HOME project, which developed a wearable EEG cap for epilepsy patients to collect daily data at home. This data, combined with smartwatches and smartphone apps, aims to model periods of heightened seizure risk. Andrea’s research focuses on integrating digital mental health interventions in epilepsy care and creating innovative digital solutions for monitoring physiological and behavioral variables. His goal is to advance remote health monitoring and improve symptom management for patients with epilepsy and other neurological disorders.
The EEG@HOME study aimed to develop a feasible method for people with epilepsy (PWE) to collect non-invasive physiological data at home and assess its association with seizure occurrence. Long-term monitoring using wearable devices can provide essential insights into high-risk seizure periods and improve epilepsy management.
In the EEG@HOME study, PWE used a portable EEG cap (ANT neuro 8 channels easy cap) to record scalp EEG twice daily, a wrist-worn device (Fitbit Charge 3) to collect heart rate, sleep, and activity data, and a smartphone app (SeerMedicalApp) to log seizure events, medication, sleep quality, stress, and mood. Remote monitoring took place over six months, with qualitative and quantitative feedback gathered through surveys, semi-structured interviews, and standardized questionnaires (SSPQ & SUS).
The results demonstrated that while the EEG cap was generally tolerated, the smartwatch and e-seizure diary were preferred for daily use. Compliance was generally high, and participants found the integration of multiple technologies smooth, with no privacy concerns. The analysis of physiological and behavioral data helped track the temporal evolution of patients' activities before and after seizures, offering valuable insight into seizure triggers. Furthermore, combining these data points can enabled the creation of individualized models that identified periods of higher or lower seizure risk. Repeated unsupervised EEG recordings were evaluated for their ability to detect seizures, and the data quality was examined, especially in a patient who experienced a seizure during recording.
In conclusion, wearable technologies and mobile solutions are well-accepted by PWE and hold great potential for advancing epilepsy monitoring, management, and seizure detection. Further studies should focus on balancing user acceptability with high-quality data collection to refine seizure forecasting models.