###### Abstract
By incorporating specific case studies and statistical data, the compelling impact of BCI technology becomes evident, highlighting its critical role in modern rehabilitation and assistive technology. This expanded introduction not only discusses the potential benefits of BCI systems for individuals with motor impairments but also includes relevant statistics and case studies to underscore the importance and impact of this technology. BCI systems hold transformative potential for individuals suffering from severe motor impairments due to conditions such as amyotrophic lateral sclerosis (ALS), spinal cord injuries, or stroke. These systems offer a means to regain some level of interaction with the environment, significantly improving their quality of life. Some case studies are explained in detail below. **1. Amyotrophic Lateral Sclerosis (ALS)**  
One of the most prominent examples of BCI application is in patients with ALS, a progressive neurodegenerative disease that leads to the loss of motor functions. A famous case is that of [PERSON], who, despite severe disability, communicated and wrote books using a computerized speech synthesis system. Modern BCIs can further enhance such capabilities, allowing for direct brain-to-computer communication without the need for physical input. According to the ALS Association, approximately 5000 people in the United States are diagnosed with ALS each year. The average life expectancy of a person with ALS is 2-5 years from the time of diagnosis, emphasizing the urgent need for assistive technologies such as BCI to maintain communication abilities as motor functions decline. **2. Spinal Cord Injuries**  
Consider a study conducted by the University of Pittsburgh, where a patient with quadriplegia (complete paralysis) was able to control a robotic arm using a BCI to perform tasks such as feeding themselves. This represents a significant breakthrough in assistive technology, as it allows individuals with no motor control to regain a level of autonomy. The World Health Organization estimates that between 250,000 and 500,000 people suffer spinal cord injuries each year, with many losing the ability to move and requiring lifelong care. BCIs could drastically reduce the burden on caregivers by enabling greater independence. **3. Stroke Rehabilitation**  
BCI systems have also been used in stroke rehabilitation. For example, the work of researchers at the University of Tubingen in Germany showed that stroke patients who used a BCI to control a virtual hand saw improvements in motor function. This approach leverages neuroplasticity, helping the brain to rewire itself and restore lost capabilities. The American Stroke Association reports that about 800,000 people in the United States have a stroke each year. Approximately 50% of stroke survivors experience some form of motor impairment, underlining the potential impact of BCIs in rehabilitation. EEG is a popular technique for acquiring neural signals because it is non-invasive and offers high temporal resolution. EEG neural signals can be categorized by frequency into delta (0.5-4 Hz), theta (4-8 Hz), alpha (8-12 Hz), beta (12-30 Hz), and gamma (30-100 Hz) bands [2; 3]. Motor imagery (MI) or motor activities primarily activate the brain's sensorimotor cortex, leading to sensory motor rhythms (SMRs). These rhythms can be classified using event-related synchronization (ERS) and event-related desynchronization (ERD), which are particularly useful for distinguishing between left- and right-hand movements [4]. Decoding EEG signals involves several steps, starting with preprocessing to remove artifacts such as muscle noise, heart signals (ECG), and ocular movements. Given the non-stationary nature of EEG signals, effective feature extraction techniques such as wavelet transformation are essential [3]. Classification of these features can be performed with or without machine learning models.