Supporting Independent Prayer in Alzheimer’s Patients with an EEG-Enabled BCI System

  • Huda Almuzaini Computer Science Department, College of Computer and Information Sciences, Imam Mohammed Ibn Saud Islamic University, Riyadh 11432, Saudi Arabia
  • Sara AlRahili Computer Science Department, College of Computer and Information Sciences, Imam Mohammed Ibn Saud Islamic University, Riyadh 11432, Saudi Arabia
  • Maha Al-sharikh Computer Science Department, College of Computer and Information Sciences, Imam Mohammed Ibn Saud Islamic University, Riyadh 11432, Saudi Arabia
  • Samia Al-faifi Computer Science Department, College of Computer and Information Sciences, Imam Mohammed Ibn Saud Islamic University, Riyadh 11432, Saudi Arabia
DOI: https://doi.org/10.24003/emitter.v14i1.1030
Keywords: Alzheimer's Disease (AD), Brain-Computer Interface (BCI), EEG Signal Processing, Islamic Prayer (Salat), Machine Learning, Classification

Abstract

Alzheimer's disease (AD) significantly impairs cognitive functions, making independent activities, including Muslim prayers, challenging for patients. This study introduces an innovative Brain-Computer Interface (BCI) system leveraging Electroencephalography (EEG) signals to facilitate prayer practices for individuals with AD. Utilizing a 5-channel EEG headset to monitor attention levels, our system detects alpha and beta wave patterns to assess user focus. When attention diminishes, the system provides guidance to the next prayer step, ensuring continuity and support. Additionally, motion detection technology captures physical movements associated with prayer, enabling the classifier to learn and recognize different prayer postures from a dataset of two individuals. This approach aids AD patients in maintaining religious practices independently while significantly enhancing their psychological well-being by fostering autonomy and spiritual fulfillment. Our findings suggest that integrating EEG-based BCI systems with motion detection offers a promising avenue for supporting daily activities and improving quality of life for individuals with cognitive impairments.  

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Published
2026-06-29
How to Cite
Almuzaini, H., AlRahili, S., Al-sharikh, M., & Al-faifi, S. (2026). Supporting Independent Prayer in Alzheimer’s Patients with an EEG-Enabled BCI System. EMITTER International Journal of Engineering Technology, 14(1), 60-76. https://doi.org/10.24003/emitter.v14i1.1030
Issue
Vol 14 No 1 (2026)
Section
Articles

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