An end-to-end Point of Cardiovascular Body Sensor Network with Cloud Service
Radha B. Kalaskar1, Bharati Harsoor2
1Mrs. Radha B. Kalaskar, Assistant Professor, Department of Computer Science and Engineering, PDA College of Engineering, Gulbarga (Karnataka), India.
2Dr. Bharati Harsoor, Professor and Head, Department of Information Science, PDA College of Engineering, Gulbarga (Karnataka), India.
Manuscript received on 21 May 2019 | Revised Manuscript received on 11 June 2019 | Manuscript Published on 27 June 2019 | PP: 30-33 | Volume-8 Issue-1C May 2019 | Retrieval Number: A10070581C19/2019©BEIESP
Open Access | Editorial and Publishing Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: India is the world capital of cardiovascular diseases and there is an immense shortage of doctors to serve the patients. This work focuses on cardiovascular sensor data collection and processing. Unlike other wireless body sensor network where the parameters are discrete, often cardiovascular data analysis needs continuous data at a high sampling rate. Such wireless signal gathering over a continuous wireless channel hasn’t been proposed so far due to critical consequences of noise in that signal during transmission. Furthermore, existing many techniques proposes a small data collection in a local node and then dissipating them to cloud. But, continuous wireless sensor signal data transmission and simultaneous processing hasn’t been successfully performed. This work addresses the aforementioned issue and delivers an end-to-end sensor network solution to acquire continuous cardiac signal, transmission to a local processing node and mitigating the data to cloud in real time and also implemented simple heart rate monitoring algorithm of the cloud to visualize continuous heart rate of a patient with this sensor node.
Keywords: Cardiovascular Disease (CVD), Electrocardiogram (ECG), Biomedical Single Processing (BSP), Ballistocardiograpy (BCG), Artificial Neural Network (ANN), Artificial Intelligence (AI), Wireless Sensor Network (WSN).
Scope of the Article: Cloud Computing and Networking