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  • Open Access

    ARTICLE

    Image Segmentation-P300 Selector: A Brain–Computer Interface System for Target Selection

    Hang Sun, Changsheng Li*, He Zhang

    CMC-Computers, Materials & Continua, Vol.79, No.2, pp. 2505-2522, 2024, DOI:10.32604/cmc.2024.049898 - 15 May 2024

    Abstract Brain–computer interface (BCI) systems, such as the P300 speller, enable patients to express intentions without necessitating extensive training. However, the complexity of operational instructions and the slow pace of character spelling pose challenges for some patients. In this paper, an image segmentation P300 selector based on YOLOv7-mask and DeepSORT is proposed. The proposed system utilizes a camera to capture real-world objects for classification and tracking. By applying predefined stimulation rules and object-specific masks, the proposed system triggers stimuli associated with the objects displayed on the screen, inducing the generation of P300 signals in the patient’s… More >

  • Open Access

    ARTICLE

    Efficient MAC Protocols for Brain Computer Interface Applications

    Shams Al Ajrawi1,*, Ramesh Rao2, Mahasweta Sarkar3

    CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 589-605, 2021, DOI:10.32604/cmc.2021.016930 - 04 June 2021

    Abstract Brain computer interface (BCI) systems permit individuals with motor disorders to utilize their thoughts as a mean to control external devices. BCI is a promising interdisciplinary field that gained the attention of many researchers. Yet, the development of BCI systems is facing several challenges, such as network lifetime. The Medium Access Control (MAC) Protocol is the bottle- neck of network reliability. There are many MAC protocols that can be utilized for dependable transmission in BCI applications by altering their control parameters. However, modifying these parameters is another source of concern due to the scarcity in… More >

  • Open Access

    ARTICLE

    Cognitive Skill Enhancement System Using Neuro-Feedback for ADHD Patients

    Muhammad Usman Ghani Khan1,2, Zubaira Naz1, Javeria Khan1, Tanzila Saba3, Ibrahim Abunadi3, Amjad Rehman3, Usman Tariq4,*

    CMC-Computers, Materials & Continua, Vol.68, No.2, pp. 2363-2376, 2021, DOI:10.32604/cmc.2021.014550 - 13 April 2021

    Abstract The National Health Interview Survey (NHIS) shows that there are 13.2% of children at the age of 11 to 17 who are suffering from Attention Deficit Hyperactivity Disorder (ADHD), globally. The treatment methods for ADHD are either psycho-stimulant medications or cognitive therapy. These traditional methods, namely therapy, need a large number of visits to hospitals and include medication. Neurogames could be used for the effective treatment of ADHD. It could be a helpful tool in improving children and ADHD patients’ cognitive skills by using Brain–Computer Interfaces (BCI). BCI enables the user to interact with the… More >

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