Body Channel Communication based Patient Monitoring System
J. Lavanya1, N. Syed Suhail Ahmed2, S. Sai Prakash3, T. Divya4, A. Manikandan5
1J. Lavanya, Student, Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
2N. Syed Suhail Ahmed, Student, Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
3S. Sai Prakash, Student, Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
4T. Divya, Student, Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
5A. Manikandan, Faculty Charge, Department of Electronics and Communication Engineering, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
Manuscript received on 04 June 2019 | Revised Manuscript received on 29 June 2019 | Manuscript Published on 04 July 2019 | PP: 387-392 | Volume-8 Issue-1S4 June 2019 | Retrieval Number: A10700681S419/2019©BEIESP
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© 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: Body channel communication or human body communication is a developing field and there are various methodology through which we can pursue and implement such a system. Health monitoring and prediction is of utmost concern since the number of patients and diseases are increasing over the years. The previously existing systems are mostly wired, generate a lot of additional noise and are expensive. To curb those differences and to produce a cost-effective system with real time implementation is the main objective. We can implement this system using different algorithms using MATLAB, Arduino, python and other image processing embedded systems. This can also be realised using deep learning and AI. For practical concerns we use MATLAB in front end and Arduino in back end along with Putty or hyper terminal.
Keywords: Feature Extraction in Discrete Wavelet Transform, Signal Pre-process, Noise Analysis, Channel Estimation, MATLAB.
Scope of the Article: Wireless Communications