Neurotechnology: Two experiments achieve remote control of devices with the mind and without implants | Technology

Turning a device on or off, moving a robot or writing with your mind is now possible. The brain emits singular waves from specific regions for each order. This electrical activity can be converted into information represented by a binary code (the one processed by common computers) and transmitted to a device. However, the systems currently being investigated present two problems. The most popular, because it was developed by Neuralink (Elon Musk’s company), incorporates brain implants that can generate rejection by the body. Those who use external headphones (companies like Emotiv already sell several models) face the inconvenience of interference. Two experiments, one developed by the Chinese space program and the other by researchers from universities in Spain, the United Kingdom, China and Peru, have managed to overcome these two pitfalls by avoiding implants and applying artificial intelligence that corrects errors to achieve precision of up to 99%.

The basis of both experiments is non-invasive electroencephalography (EEG) (without implants). It consists of measuring the electrical activity generated by brain cells from electrodes placed on the scalp. The main obstacle is that any external interference, any noise or the presence of a mobile, generates errors in reading the brain information and prevents the correct interpretation of the order.

A team of researchers led by Wang Congqing has developed an experiment at the Beijing-based China Astronaut Research and Training Center to control equipment using their brain waves. The work, reviewed and published in the scientific journal Computer Measurement and Control and spread by South China Morning Post, has yielded results of 99% efficiency in the manipulation of a robotic arm and its application in the Chinese space station is planned Tiangong (Palace in the sky). According to the researcher in the scientific publication, “an untrained person can use it to issue commands with fairly high accuracy and speed.” To improve the device’s performance, the team used artificial intelligence to discriminate brain wave patterns.

A similar approach has been developed in research published in Applied Soft Computing for the group Intelligent Systems Based on Fuzzy Decision Analysis (SINBAD), from the University of Jaén, and the faculties of Engineering and Technology of Essex (United Kingdom), Nantong (China) and Lima (Peru), according to the Discover Foundation.

The model, based on the application of artificial intelligence and fuzzy logic (representing knowledge in mathematical language for complex decisions in problems that present uncertainty, imprecision or vagueness), has been experimented with healthy volunteers and stroke patients in a daily environment, where any noise or interference can alter the reading of brain activity. The registered effectiveness has been between 74.3% and 98.6%. Study participants were able to select a character on a virtual keyboard and activate device switches with their minds.

Javier Andreu-Pérez, lead author of the study, from Malaga, SINBAD researcher and chairman of a group at the Center for Computational Intelligence at the University of Essex, summarizes that his research demonstrates a “pretty good decoding of thought for the control of devices in a home automation”. And he specifies: “We do not correct the mind. The person thinks what he has to think if he has to focus on turning on a certain appliance. What we have improved is the decoding using deep learning in combination with fuzzy processing techniques to eliminate all that noise that is around the signal and focus on the neuronal activity that can be captured by electroencephalography”.

Difficulties

Research thus saves one of the main pitfalls of this technology. Andreu-Pérez explains that “a mobile phone, environmental noise, hair or even a few steps can corrupt the signal.” “Interferences can be reduced in a laboratory, but we have tested it in a natural environment”, he highlights.

The other great challenge they have overcome is the implantation of devices in the brain, one of the great limitations of these technologies due to their secondary effects. In this sense, the researcher simplifies to explain the process: “Each neuron generates an electrical impulse of a very small voltage. It can be captured by an electrode, which is usually gold or platinum and is implanted in the head. We use an external helmet that listens to that voltage, amplifies it and captures it to be able to process it”.

Andreu-Pérez explains the reason for the difference in results: “One person is able to concentrate on a certain thought better than another and facilitate it in a clearer way so that we can codify it.” “Overall,” he says, “the average percentages have been pretty good. There is always a margin of error, but they have worked quite well.”

Applications

Although the experiment has focused on simple home automation actions, such as turning on a light with your mind or activating an appliance, the future of this technology is gigantic. The Spanish researcher explains: “We have started with this, but we are more ambitious: we want to reach robotics, driving, neuromedicine, leisure… In the end it is to use your brain as another extremity of your body in the most naturally possible”.

In this sense, another of the development paths of the Andreu-Pérez team is the creation of ever smaller EEG reading devices. Mikhail Lebedev, a neuroscientist at the University of Skoltech (Moscow) and unaware of the study led by the Spanish researcher and the Chinese experiment, highlights the possibilities of encephalography devices, especially in the medical field: “They can help people with restricted mobility regain control of their limbs or provide advance warning of an impending seizure to patients with epilepsy.” And he adds other applications such as research on sleep, decision making, memory and attention. Also as a formula for evaluating brain damage or for monitoring patients in a coma, without excluding the manipulation of devices, from the arm of an exoskeleton to turning on a television, or leisure.

Devices

Lebedev, author of an article in Experimental Brain Research, He agrees with Andreu-Pérez that one of the keys will be the development of compact and affordable devices. As he explains, the problem with existing systems used in laboratories and hospitals is that they are either bulky and expensive or the number of electrodes is limited, resulting in moderate signal quality. Hobbyist devices tend to be more affordable, but with even poorer sensitivity.

To circumvent these limitations, researchers at South Ural State University, North Carolina State University, and Brainflow, led by electronics research engineer Ildar Rakhmatulin and Lebedev, have created a device that can be built with an investment approximately 350 euros, a third of the cost of analogs currently available, with 24 more electrodes than conventional ones, weighing 150 grams and with a signal quality consistent with the average needs of an investigation.

But the biggest drawback of the advancement of these technologies is the privacy of thought and external influence on the brain. Andreu-Pérez recognizes it. “We are advancing in the technological field, but there has to be a parallel ethical work. There can’t be one thing without the other.”

ethical implications

In this sense, researchers from Imperial College London have carried out APL Bioengineering a review of modern commercial brain-computer interface (BCI) devices to discuss major technological limitations and ethical and legal challenges.

According to the researchers, the technology allows communication in both directions, so it has advantages for patients with brain damage or could favor learning, but also, according to Rylie Green, co-author of the study, “it is clear that neurotechnologies have the potential to profoundly shape our own human experience.”

It refers not only to potential mental and physiological side effects that are still unexplored, but also to the potential for exploitation of users’ neural data by private companies developing these technologies. Apart from diagnostic value, EEG data could be used to infer emotional and cognitive states, providing unparalleled insight into user intentions, preferences, and emotions.

What would happen if the technology allowed only those who can pay for it to obtain better academic results, widening inequalities or if the owner of the brain data wanted to commercialize it or use it to induce certain behaviors? “This bleak picture poses an interesting dilemma for policymakers in the commercialization of BCI,” says Green. And she wonders: “Should regulators intervene to prevent misuse and unequal access to neurotechnology? Should society follow the path taken by previous innovations, such as the internet or the smartphone, which originally targeted niche markets but are now being traded on a global scale?

The researcher believes, like Andreu-Pérez, that action is essential in parallel to the necessary and promising technological development: “Despite the potential risks, the ability to integrate the sophistication of the mind with the capabilities of modern technology constitutes an achievement unprecedented scientist who is beginning to challenge our own preconceived ideas of what a human being is.”

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