Businessman Artur Shehu breaks his silence: I am a long-time land owner in Zvërnec, I don't know the investors at all
Albanian businessman Artur Shehu spoke on the Opinion show...
Albanian businessman Artur Shehu spoke on the Opinion show...

Brain neurotechnology is a field that involves the development of advanced devices for monitoring, treating, and modifying brain functions.
Key devices include electroencephalograms (EEG), magnetic resonance imaging (MRI), deep brain stimulation (DBS), and brain-computer interfaces (BCIs).
Electroencephalogram ( EEG) is used to measure the electrical activity of the brain and has applications in the diagnosis of epilepsy, monitoring coma states, and cognitive training.

Functional magnetic resonance imaging (MRI), such as MEG, provides more precise information on modal brain activity, giving it an advantage over EEG in localizing the source of disordered activity.
Depolarizing brain stimulation (DBS) is a technology that uses electrodes placed in specific areas of the brain to treat Parkinson's disease, dystonia, and depression.
Brain-computer interfaces (BCIs) allow direct interaction between the brain and computer systems for communication, rehabilitation, and control of external devices, which has potential for therapy for patients with motor deficits.
Artificial intelligence in medicine is bringing major advances in diagnosis, treatment, and personalization of therapy.
AI algorithms are used for analyzing raw medical images, diagnosing neurodegenerative diseases like Alzheimer's, and developing treatment protocols based on big data.
Most notably, AI intervenes in improving the analysis of biological signals and collaborates with neurotechnologies to advance the functional rehabilitation of patients.
Brain Neurotechnology Devices
1. Electroencephalogram (EEG):
-Use: Measures electrical brain activity in real time.
-Applications: Diagnosis of epilepsy, monitoring of coma states, study of cognitive processes and scientific research on the internal activity of the brain.
-Technology: Bags with electrodes placed on the skin that capture changes in the electrical potentials of nerve cells.
2. Magnetoencephalography (MEG):

-Use: Measures the electromagnetic activity of the brain with greater accuracy than EEG.
-Applications: Localization of the source of epileptic activity, study of specialized brain functions, and neuroscience research.
3. Deep Brain Stimulation (DBS):
-Use: Treatment of movement disorders such as Parkinson's, severe depression and other neuropsychiatric disorders.
-Technology: Electrodes placed in specific areas of the brain that send electrical impulses to modify disordered activity.
4. Brain-Computer Interfaces (BCIs):

Usage:
-Communication for patients with motor diseases or nervous system damage.
-Rehabilitation of motor functions.
-Control of external devices, such as robotic arms or other machinery.
-Technology: Provides direct interaction between the brain and the computer by reading neural signals and translating them into actions.

1. Diagnostics and Analysis of Medical Data:
-AI algorithms analyze medical images (MRI, CT, PET) to identify pathological changes in the brain such as tumors, injuries, or degenerative diseases.
-Data analysis is useful for early diagnosis of Alzheimer's and other neurodegenerative diseases.
2. Treatment Personalization:
-AI helps create personalized treatment programs by analyzing the patient's genetic profile and clinical data.
-This is very important especially in the treatment of chronic and neuropsychiatric diseases.
3. Rehabilitation with AI:
-AI-based systems provide intelligent therapy for patients with neurological injuries, adapting exercises and rehabilitation tools in real time.
-Using machine learning algorithms to track progress and optimize treatment.
4. Research and Cognitive Science:
-AI is used to analyze patterns of brain activity and better understand its functioning in mediating cognitive science.
-This helps in developing new theories about thinking, perception, and actions, especially in cases of anomalies.
5. Development of new technologies:
-The use of artificial neural networks, deep learning algorithms, and other automated systems to improve neuroscience and medicine, offering new opportunities for effective treatment and rapid diagnoses./ CNA
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