Brain Machine Interface: The Accurate Interpretation of Neurotransmitter Signals Targeting Muscles

Brain Machine Interface: The Accurate Interpretation of Neurotransmitter Signals Targeting Muscles

Rinat Galiautdinov
Copyright: © 2020 |Pages: 11
DOI: 10.4018/IJARB.2020010102
OnDemand:
(Individual Articles)
Available
$37.50
No Current Special Offers
TOTAL SAVINGS: $37.50

Abstract

The main purpose of the article is to provide the solution which allows the muscles to work in a situation when neural connection is corrupted either due to illness or injury, which usually causes paralysis. The research is on the interpretation of the brain signals based on the analysis of neurotransmitters and the transformation of this analysis into the electric signals effecting on the muscle in the situation when neural circuit between a sensor/inter neuron and a motor neuron is broken. This method would allow paralyzed people to move their limbs and potentially to walk.
Article Preview
Top

Introduction

Paralysis is a big problem. Usually it happens because of the injury or disease and the reason of paralysis is usually caused by corrupted connection between sensor/inter neurons and motor neurons. Such the problem could be resolved with a brain machine interface, however there is still no accurate and promising method to do so. One of the famous and recently suggested methods is based on randomly inserted electrodes inside of a brain which collect the APs which later on pass quite primitive interpretation. Such the method is not accurate neither revolutionary, cannot be technologically evolved with time and leads to dead end.

The method which is introduced in this research is able to accurately interpret the brain signals and effect on the muscles or motor neurons according to the proper interpretation. The method also supports technological evolution.

Complete Article List

Search this Journal:
Reset
Volume 13: 1 Issue (2024): Forthcoming, Available for Pre-Order
Volume 12: 2 Issues (2022): 1 Released, 1 Forthcoming
Volume 11: 2 Issues (2021)
Volume 10: 2 Issues (2020)
Volume 9: 2 Issues (2019)
View Complete Journal Contents Listing