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Brain-Machine Interface

Brain-Machine Interface

Abstract

Requiring collaboration in the fields of neurobiology, electrophysiology, engineering, computer science, and biomedicine, Brain-Machine Interfaces (BMIs) are an emerging multidisciplinary technology with countless potential benefits. The ability to record and interpret neuronal activity at a higher resolution and specificity is one of the exciting promises of BMIs. The applications of this technology provide hope for a vast number of individuals who suffer from a wide range of neurological diseases and disorders. It can also be applied to artificial prostheses, to provide limb sensation for amputees. Although BMIs hold immense potential, questions within the realm of neuroethics have raised concern. In particular, the possible exploitation that could arise through medical practices with the advancement of technology [1]. Where humans may potentially be given capabilities that surpass the norm, changing the perception of what it means to be human [1]. It is important to take into account that there are BMIs currently in place that have provided relief for various conditions. To name a few, the use of deep brain stimulation in patients with Parkinson’s, spinal cord stimulation for those with intractable pain, and the use of motor prosthesis for patients with epilepsy [1]. However, these methods oftentimes only provide temporary or mild relief and are not inerrant. The trajectory of the BMIs outlined herein aims toward finding an ideal invasive mechanism to solve these drawbacks of mild and temporary relief. There are a vast number of neurological disorders that continue to trouble humanity both emotionally and economically [1], that could substantially change through the use of BMIs.

Keywords

Brain-machine interfaces, Biocompatibility

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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