Market Overview:
The global brain reading market size was significantly robust in 2021 and is expected to register a rapid revenue CAGR over the forecast period. Increasing adoption of brain reading robots for reducing human work and labor are some key factors driving brain reading robots market revenue growth over the forecast period.
A brain-reading robot is an advanced robotic technology, which is designed to read brain by analyzing changes of electric signals. The central unit of the brain reading robot is a brain–computer interface based on Electroencephalography (EEG), which is a technique used for the measurement of the electrical activity of the brain. Brain reading robots use EEG signals for distinguishing various brain signals corresponding to various body movements for action.
This brain-reading robotic technology is an important branch of robotics, as it is human-centered and used for household work, commercial assignments, and other security purposes. In addition, various advanced algorithms are deployed by mind-reading robotic technology.
The technique of deciphering electric brain signals and its conversion to spatial representation is known as brain mapping. Neurons of brain are responsible for generating electric signals, which are monitored by placing a number of electrodes on scalp. Growing applications of brain reading robots in various sectors, such as education, medicine, pharmaceutical, and manufacturing, among others for simplifying human efforts, is expected to boost revenue growth of the brain reading robots market. However, ethical concerns regarding mind reading and loss of privacy are some factors expected to restrain revenue growth of the global brain reading robots market over the forecast period.
The ability to control robots with your mind is no longer the stuff of science fiction: scientists from MIT and Boston University devised a system(Opens in a new window) that allows robots to interpret simple brain waves.
The technique is called electroencephalography (EEG), and it’s been used before, but never in a closed-loop, real-time environment. That is, the scientists were able to get a robot to react to human brain waves and change their course of action nearly instantaneously.
They programmed the robots to perform a simple sorting task. If a robot started to place an object onto one target that should have been placed in the other target, a human observer was asked to “mentally disagree” with the robot’s choice. That human response would create brain signals known as error-related potentials, which the robot could receive and interpret via its connection to an EEG cap the human was wearing.
The main goal was to alter the robot’s choice before it completed its task, a real-time error correction that hadn’t been achieved before, according to the researchers. While they achieved that goal, they weren’t able to get the robot to second-guess a signal in real-time: error-related potentials are weak signals, so sometimes the robots were confused.
