In the last twenty years, advances in real-time functional magnetic resonance imaging (rt-fMRI) have offered exciting new tools to study the human brain. One of them, termed rt-fMRI neurofeedback (NF), has turned the MRI scanner environment into an interac ...
Weber et al. provide evidence in support of a stress-diathesis model of functional neurological disorders. They identify trauma history in the form of emotional neglect as a psychological risk factor, and reduced hippocampus and amygdala volume as a predis ...
The main theme of my thesis will be to use neuro-muscular modeling techniques to study locomotion of terrestrial mammals. Locomotion is the ability of animals to interact with the environment to propel themselves in space. It involves co-ordination and pre ...
Mobility impairments are a common symptom of age-related degenerative diseases. Gait features can discriminate those with mobility disorders from healthy individuals, yet phenotyping specific pathologies remains challenging. This study aims to identify if ...
Although hallucinations are important and frequent symptoms in major psychiatric and neurological diseases, little is known about their brain mechanisms. Hallucinations are unpredictable and private experiences, making their investigation, quantification a ...
Spinal Cord Injury (SCI) disrupts the communication between the brain and spinal circuits below the lesion, leading to a plethora of neurological impairments, including the loss of motor function. At present, the only medical practices to enhance recovery ...
Neuroprosthetics is a discipline that aims at restoring lost functions to people affected by a variety of neurological disorders or neuro-traumatic lesions. It combines the expertise of computer science and electrical, mechanical, and micro/nanotechnology ...
In this thesis, we contribute to the field of rehabilitation robotics by designing haptic-enabled
tangible robot-based activities and exploring their added value for therapy and assistance.
The research specifically focuses on the design and development of ...
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 ...
