Mohammed G. Ayoub
Northern Technical University

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Journal : TELKOMNIKA (Telecommunication Computing Electronics and Control)

Streaming in-patient BPM data to the cloud with a real-time monitoring system Mohammed G. Ayoub; Mazin N. Farhan; Mohamme S. Jarjees
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 6: December 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i6.13263

Abstract

Monitoring the heart activities for old people or people with medical history (Arrhythmia or CHD) is targeted by most new medical technologies. This paper demonstrated an in-patient real-time monitoring system for heart rate estimation. A ratio of beats per minute (BPM) is continuously recorded, streamed and archived to the cloud via WeMos WiFi development board. This cost effective system is simply based on two sub-systems: BPM data acquisition through pulse sensor and WeMos-based communication systems. The streamed BPM data are saved instantaneously in Google drive as spreadsheets which can only be accessed by authorized persons wherever the internet service is available. Thus, the person in charge can remotely observe the patient’s status and do analytics for the archived data. A pilot study with eight subjects was carried out to validate the developed BPM tele-monitoring system. Encouraging results have been achieved.
Qualitative assessment of image enhancement algorithms for mammograms based on minimum EDV Mazin N. Farhan; Mohammed G. Ayoub; Hassan M. Qassim; Abdulrahman K. Eesee
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 2: April 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i2.14085

Abstract

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 techniques used for detecting breast cancer. However, its resulted images may not be clear enough or helpful for physician to diagnose each case correctly. This fact has pushed researchers towards developing effective ways to enhance images throughout using various enhancement algorithms. In this paper, a comparison amongst these applied algorithms was done to evaluate the optimum enhancement technique. A morphology enhancement, which is resulted from combining top-hat operation and bottom-hat operation, was used as a proposed enhancement algorithm. The proposed enhancement algorithm was compared to three other well-known enhancement algorithms, specifically histogram equalization, logarithmic transform, and gamma correction with different gamma values. Twenty-five mammographic images were taken from the mammography image analysis society (MIAS) database samples. The minimum entropy difference value (EDV) was used as metric to evaluate the best enhancement algorithm. Results has approved that the proposed enhancement algorithm gave the best-enhanced images in comparison to the aforementioned algorithms.