Every year, thousands of people around the world experience various neurological diseases like stroke and spinal cord injuries. Due to these diseases, many of them have paralysis. Such people are almost completely isolated from the social life, from any communication with doctors and relatives. That is why it is sometimes even impossible to avoid the usage of expensive equipment. There are already technologies in the world for reading thoughts and turning them into text messages at up to eight words per minute, but recently, scientists from the US state of Illinois have been able to improve this indicator. Artificial intelligence helped them greatly.
ScienceMag introduced this technology. In their article they described the experiment in which a new technology returns the possibility of communication to the patient with the so-called tetraplegia. During the experiment, patient with implanted electrodes imagined how he would move a hand if he wrote letters. Certainly, during this process brain showed some activity, which ,as the result, was remembered by AI. Then computer was able to remember the place of the activity in the brain connected with particular letter of the alphabet and was able to display symbols alternately that patient mentally traced on the screen.
According to the scientists, AI is able to recognize symbols with 95% accuracy. AI make several mistakes only with similar letters like «g» and «q», for example. Regardless this, now paralyzed person can text with the speed of 66 words per minute. To compare, the speed of texting of healthy person is 120 words per minute.
By the way, thoughts can be even transformed into the speech.
According to the editors of ScienceMag, researchers from Germany and the USA used some computational models based on neural networks, they reconstructed words and sentences by reading brain signals, as it was mentioned before. So the system is the same, they just observed areas of the brain at those moments when people read aloud, speak, or simply listen to notes.
During this research, they relied on data obtained from 5 people with epilepsy. The network analyzed the behavior of the auditory cortex (which is active both during speech and during listening). Then the computer reconstructed the speech data from the pulses received from these people. As a result, the algorithm coped with an accuracy of 75%.
Another team relied on the data of 6 people, that experienced the removing of brain tumor. Microphone picked up their voices when they read out loud different words. While this process, the electrodes recorded information from the speech center of the brain. Then computer compared the data from the electrodes with audio recording. Only 40% was correct as the result.
The third team from the University of California reconstructed entire sentences based on brain activity from three patients with epilepsy who read specific sentences out loud. Some sentences were correctly identified in more than 80% of cases.
Regardless such appealing results, the system has a lot of shortcomings and is needed to be adjusted. However, it will be developed even more, so millions of people will have an opportunity to text and to speak once again.