Heart Disease Detection using ML and ES (Smart Wearable Health Monitoring System) | ||||
| Kafrelsheikh Journal of Information Sciences | ||||
| Article 5, Volume 2, Issue 1, August 2021, Page 1-7 PDF (314.32 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/kjis.2021.42695.1009 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Osama M. Abu Zaid  ; adham aly mohamed; Kamel Alaa El-Sehly; Mahmoud Mohamed Ossman; Mostafa Gamal Kamal; Marwan Atef Aly
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| Department of Computer Sciences, Faculty of Computers and Information, Kafrelsheikh University, Egypt | ||||
| Abstract | ||||
| This paper proposed a smart wearable system for heart disease detection using machine learning and embedded systems. A smart wearable system that able to monitor the heart beat rate condition of patient. The heart beat rate is detected using photoplethysmogram (PPG). The signal is processed using ATmega32 Microcontroller to determine heart beat rate per minute. Then, it sends the heart rate represented as BPM to Android App Via Bluetooth Communication, Android app sends SMS alert to the mobile phone of medical experts or patient's family member, or their relatives via SMS contains user's current location, Android app calculates daily steps count. Android/Desktop app allow user to check nearest hospitals, cardiac centers, nearest Health centers (GYM) and also user's current location. Android/Desktop app allow user to know if he suffers from heart disease or not by one click which run a machine/Deep learning module that analyze user ‘s data to detect heart disease. | ||||
| Keywords | ||||
| Firebase Cloud; Deep Learning; Machine Learning; Neural network; Logistic Regression | ||||
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