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Development of an Efficient Monitoring System Using Fog Computing and Machine Learning Algorithms on Healthcare 4.0

Development of an Efficient Monitoring System Using Fog Computing and Machine Learning Algorithms on Healthcare 4.0
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Author(s): Sowmya B. J. (M.S. Ramaiah Institute of Technology, India), Pradeep Kumar D. (M.S. Ramaiah Institute of Technology, India), Hanumantharaju R. (M.S. Ramaiah Institute of Technology, India), Gautam Mundada (M.S. Ramaiah Institute of Technology, India), Anita Kanavalli (M.S. Ramaiah Institute of Technology, India) and Shreenath K. N. (Siddaganga Institute of Technology, India)
Copyright: 2022
Pages: 21
Source title: Deep Learning Applications for Cyber-Physical Systems
Source Author(s)/Editor(s): Monica R. Mundada (M.S. Ramaiah Institute of Technology, India), S. Seema (M.S. Ramaiah Institute of Technology, India), Srinivasa K.G. (National Institute of Technical Teachers Training and Research, Chandigarh, India) and M. Shilpa (M.S. Ramaiah Institute of Technology, India)
DOI: 10.4018/978-1-7998-8161-2.ch005

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Abstract

Disruptive innovations in data management and analytics have led to the development of patient-centric Healthcare 4.0 from the hospital-centric Healthcare 3.0. This work presents an IoT-based monitoring systems for patients with cardiovascular abnormalities. IoT-enabled wearable ECG sensor module transmits the readings in real-time to the fog nodes/mobile app for continuous analysis. Deep learning/machine learning model automatically detect and makes prediction on the rhythmic anomalies in the data. The application alerts and notifies the physician and the patient of the rhythmic variations. Real-time detection aids in the early diagnosis of the impending heart condition in the patient and helps physicians clinically to make quick therapeutic decisions. The system is evaluated on the MIT-BIH arrhythmia dataset of ECG data and achieves an overall accuracy of 95.12% in classifying cardiac arrhythmia.

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