Abdulrahman K. Eesee

• MSc Biomedical Engineering
• Lecturer at Northern Technical University

The rapid advancement of technology related to Industry 4.0 has brought about a paradigm shift in the way we interact with assets across various domains. This progress has led to the emergence of the concept of a Human Digital Twin (HDT), a virtual representation of an individual’s cognitive, psychological, and behavioral characteristics. The HDT h...

In recent years, Finger Outer Knuckle (FOK) has come out as a promising biometric modality. This paper considers enhancing the FOK recognition of verification by using a suggested efficient deep learning network. It is called the Deep Recurrent Neural Network (DRNN). This network has the ability to deal with both minor and major FOKs. It consists o...

Fingerprint is one of the most well-known biometrics that has been used for personal recognition. However, faked fingerprints have become the major enemy where they threat the security of this biometric. This paper proposes an efficient deep fingerprint classification network (DFCN) model to achieve accurate performances of classifying between...

Breast cancer is one of the leading reason of death among women. Nevertheless, medications for this fatal disease are still away of ambitions. Patients (thought to have breast cancer) should go through several advanced medical diagnostic procedures like mammography, biopsy analysis, ultrasound imaging, etc. Mammography is one of the medical imaging...

Heart sounds play a crucial role in the clinical assessment of patients. Stethoscopes are used for detecting heart sounds and diagnosing potential abnormal conditions. However, several parameters of the cardiac sounds cannot be extracted by traditional stethoscopes. This paper presents a proposed algorithm based on peaks detection. Besides its abil...

Disability, specifically impaired upper and/or lower limbs, has a direct impact on the patients’ quality of life. Nowadays, motorized wheelchairs supported by a mobility-aided technique have been devised to improve the quality of life of these patients by increasing their independence. This study aims to present a platform to control a motorized wh...

Galvanic Skin Response (GSR) is a physiological marker that have been used to monitor the Electro-dermal activities (EDA) due to the change in the sweat glands activities. The autonomic nervous system is the responsible about most of the sweat glands activities; as a result, the GSR has been used to study the emotions and stress. This paper is focu...

The Galvanic Skin Response (GSR) is a measure of change in the electrodermal properties resulted from the change in the sweat glands activity in response to the modulation of the autonomic nervous system. For this reason it has begun to be of interest as a signal that can be used to monitor emotional states and stress. The aim of this project was t...