Tools for brain-computer interaction: a general concept for a hybrid BCI
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The ability to notice erroneous behavior is crucial for effective training. Within the framework of neuroprosthetics, numerous studies in electroencephalography (EEG) confirm the existence of neural correlates when humans perceive the erroneous actions of ...
The 2020's decade will likely witness an unprecedented development and deployment of neurotechnologies for human rehabilitation, personalized use, and cognitive or other enhancement. New materials and algorithms are already enabling active brain monitoring ...
Over the last 20 years, the field of Smart Dust has been proposed and demonstrated. Almost in the same period, implantable and wearable sensors for human monitoring have been actually successfully introduced in the market. The present research about Smart ...
Brain-computer interfaces (BCIs) are neural prosthetics that enable closed-loop electrophysiology procedures. These devices are currently used in fundamental neurophysiology research, and they are moving toward clinical viability for neural rehabilitation. ...
One of the goals of the Neural Engineering System Design (NESD) program in the United States and of similar programs around the world is to develop an interface able to read from one million neurons in parallel. This is well beyond the capabilities of trad ...
Implanted microelectrode arrays sense local neuronal activity, signals which are used as control commands for brain computer interface (BCI) technology. Patients with tetraplegia have used BCI technology to achieve an extraordinary degree of interaction wi ...
Neuroprosthetics, the discipline that aims at interfacing neural systems to artificially engineered devices, has witnessed in recent years important advancements towards the ultimate goal of augmenting and restoring human functions through technology and a ...
Estimation of intracranial sources, using inverse solutions methods, has been proposed as a mean to improve performance in non-invasive brain-computer interfaces. These methods estimate the activity of a large number of neural sources from a smaller number ...
This paper describes a brain-machine interface for the online control of a powered lower-limb exoskeleton based on electroencephalogram (EEG) signals recorded over the user’s sensorimotor cortical areas. We train a binary decoder that can distinguish two d ...
Future neuroprosthetics will be tightly coupled with the user in such a way that the resulting system can replace and restore impaired upper limb functions because controlled by the same neural signals than their natural counterparts. However, robust and n ...