Concept

National Institute of Neurological Disorders and Stroke

Related publications (62)

Resource-Efficient Continual Learning for Personalized Online Seizure Detection

David Atienza Alonso, Giovanni Ansaloni, José Angel Miranda Calero, Jonathan Dan, Amirhossein Shahbazinia, Flavio Ponzina

Epilepsy, a major neurological disease, requires careful diagnosis and treatment. However, the detection of epileptic seizures remains a significant challenge. Current clinical practice relies on expert analysis of EEG signals, a process that is time-consu ...

2024

Harmonization of multi-scanner in vivo magnetic resonance spectroscopy: ENIGMA consortium task group considerations

Cristina Ramona Cudalbu

Magnetic resonance spectroscopy is a powerful, non-invasive, quantitative imaging technique that allows for the measurement of brain metabolites that has demonstrated utility in diagnosing and characterizing a broad range of neurological diseases. Its impa ...

FRONTIERS MEDIA SA2023

EpilepsyNet: Interpretable Self-Supervised Seizure Detection for Low-Power Wearable Systems

David Atienza Alonso, Amir Aminifar, Renato Zanetti

Epilepsy is one of the most common neurological disorders that is characterized by recurrent and unpredictable seizures. Wearable systems can be used to detect the onset of a seizure and notify family members and emergency units for rescue. The majority of ...

2023

Current propagation type self-consistent leader-return stroke model

Marcos Rubinstein

A current propagation type return stroke model which is consistent with the estimated distribution of the charge on the leader channel is described. The model takes into account the dispersion of the return stroke current along the return stroke channel. T ...

2023

Molecular reconstruction and simulation of the Neuron-Glia-Vasculature system

Polina Shichkova

The outstanding information processing capacity of the brain relies on numerous molecular mechanisms. It is an extremely energy-expensive function, which involves specialization and collaboration of different cell types. A common framework to study the com ...

EPFL2023

An immersive virtual reality system for ecological assessment of peripersonal and extrapersonal unilateral spatial neglect

Olaf Blanke, Andrea Serino, Roberta Ronchi

BackgroundUnilateral spatial neglect (USN) is a debilitating neuropsychological syndrome that often follows brain injury, in particular a stroke affecting the right hemisphere. In current clinical practice, the assessment of neglect is based on old-fashion ...

BMC2023

Impact of interhemispheric inhibition on bimanual movement control in young and old

Friedhelm Christoph Hummel, Takuya Morishita

Interhemispheric interactions demonstrate a crucial role for directing bimanual movement control. In humans, a well-established paired-pulse transcranial magnetic stimulation paradigm enables to assess these interactions by means of interhemispheric inhibi ...

SPRINGER2022

Towards patient-tailored interventions for stroke recovery: graph theoretical approaches and modeling of non-invasive brain stimulation

Giorgia Giulia Evangelista

Stroke is a disease that causes the death of precious brain cells that will never grow back and which will affect one in four humans at some point in their life. While therapies and treatments for this debilitating condition are fairly standard, their outc ...

EPFL2022

Fabrication of a planar Dielectric Elastomer Actuator and Characterization of its self-discharge rate

Facial paralysis is a very challenging condition that can affect all age groups. It impacts facial movement, appearance, emotional expression, social interactions, and critical functions such as smiling, eating, speaking, or blinking. There are a wide vari ...

2022

Unsupervised Domain Adaptation for Cross-Subject Few-Shot Neurological Symptom Detection

Mahsa Shoaran, Bingzhao Zhu

Modern machine learning tools have shown promise in detecting symptoms of neurological disorders. However, current approaches typically train a unique classifier for each subject. This subject-specific training scheme requires long labeled recordings from ...

IEEE2021

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