Now Possible to Understand the Needs of Patients with Brain Injuries

A Damghan University faculty member, Dr. Hanif Heidari, has discovered a new method for analyzing the electroencephalogram (EEG) behaviors of patients suffering brain stroke and injuries and understanding the needs of these patients. As Dr. Heydari mentioned, “a significant percentage of patients with brain strokes and nerve damages are not able to speak or move any part of their body, and thus, it is impossible for others to understand these patients’ conditions and needs, making the situation very difficult for the patients themselves and the people around them.” “To open a window to the mental world of these patients and understand their feelings and needs,” Dr. Heidari added, “we, in collaboration with Professor Velichko from Russia, used a new measurement technique (introduced in 2021) to mathematically analyze the EEG behaviors of the patients and detect the needs of the patients with neurological lesions.”

Referring to the research done by other researchers in the past, Dr. Heidari mentioned, “in the previous methods, the number of the channels were very high and the accuracy of the findings was very low. However, in this method, we reduced the number of the channels (from 30 to 8) to diagnose the patient's behaviors; this significantly lowered the cost, and on the other hand, increased the accuracy of the analysis. It not only helps read the mind of the patients with brain injuries, but also significantly improves the evaluation of the treatment effectiveness.” Referring to a sample patient suffering hemorrhagic stroke, Dr. Heidari said, “in the previous algorithms, it was not possible to detect the movements of the hands and the feet, but now, not only it is possible to detect these movements with 65-70% accuracy, but Continuous EEGs can also evaluate the patient's recovery process and the effectiveness of the treatment.”

He expressed hopes that with this new method and help offered by artificial intelligence and robotics, we will soon witness smart home devices for communication with patients suffering brain injuries. The results of this research are published in the edited volume “Biomedical Signals Based Computer-Aided Diagnosis for Neurological Disorders” by Springer International Publishing.