All Outputs (5)

Heart patient health monitoring system using invasive and non-invasive measurement (2024)
Journal Article
Mastoi, Q., Alqahtani, A., Almakdi, S., Sulaiman, A., Rajab, A., Shaikh, A., & Alqhtani, S. M. (2024). Heart patient health monitoring system using invasive and non-invasive measurement. Scientific Reports, 14(1), Article 9614. https://doi.org/10.1038/s41598-024-60500-0

The abnormal heart conduction, known as arrhythmia, can contribute to cardiac diseases that carry the risk of fatal consequences. Healthcare professionals typically use electrocardiogram (ECG) signals and certain preliminary tests to identify abnorma... Read More about Heart patient health monitoring system using invasive and non-invasive measurement.

Survey improving usability of the smartphones for elders (2023)
Journal Article
Mastoi, Q. (2023). Survey improving usability of the smartphones for elders. Acta Biotechnologica, 6(1), Article 256. https://doi.org/10.56979/601/2023

The focal point of this study is the usability of smartphones for elderly individuals. Notably, Android dominates the current smartphone market share at 72.72%. This prevalence is influenced by various factors, including affordability, a diverse arra... Read More about Survey improving usability of the smartphones for elders.

Novel framework for efficient detection of QRS morphology for the cardiac arrhythmia classification (2023)
Journal Article
Mastoi, Q., Farman, H., & Ahmed, S. (2023). Novel framework for efficient detection of QRS morphology for the cardiac arrhythmia classification. Journal of Computing and Biomedical Informatics, 5(02), 12-20. https://doi.org/10.56979/502/2023

The abnormal conduction or disturbance in the cardiac activity is called cardiac arrhythmia except for sinus rhythm. Cardiac arrhythmias are placing a significant strain on the healthcare system as a result of the rising mortality rate in the world.... Read More about Novel framework for efficient detection of QRS morphology for the cardiac arrhythmia classification.

A fully automatic model for premature ventricular heartbeat arrhythmia classification using the Internet of Medical Things (2023)
Journal Article
Mastoi, Q. U. A., Shaikh, A., Saleh Al Reshan, M., Sulaiman, A., Elmagzoub, M. A., & AlYami, S. (2023). A fully automatic model for premature ventricular heartbeat arrhythmia classification using the Internet of Medical Things. Biomedical Signal Processing and Control, 83, Article 104697. https://doi.org/10.1016/j.bspc.2023.104697

Cardiac arrhythmias are one of the leading causes of increased mortality worldwide and place a heavy burden on the medical environment. Premature ventricular contraction is the disturbance in electrical activity which is the most dangerous arrhythmia... Read More about A fully automatic model for premature ventricular heartbeat arrhythmia classification using the Internet of Medical Things.

Deep neural network-based application partitioning and scheduling for hospitals and medical enterprises using IoT assisted mobile fog cloud (2021)
Journal Article
Lakhan, A., Mastoi, Q., Elhoseny, M., Suleman, M., Mazin, M. &., Mohammed, A., …Mohammed, M. A. (2022). Deep neural network-based application partitioning and scheduling for hospitals and medical enterprises using IoT assisted mobile fog cloud. Enterprise Information Systems, 16(7), Article 1883122. https://doi.org/10.1080/17517575.2021.1883122

These days, fog-cloud based healthcare application partitioning techniques have been growing progressively. However, existing static fog-cloud based application partitioning methods are static and cannot adopt dynamic changes in the dynamic environme... Read More about Deep neural network-based application partitioning and scheduling for hospitals and medical enterprises using IoT assisted mobile fog cloud.