Impedance Cardiography Signal Improvement Through Sign Related Adaptive Removers for Remote Health Care
Soniya Nuthalapati1, Kusuma Nutalapati2, Naveen Laghuvarapu Prasad Nagipogu3, P. Yaswanth Sai Mandepudi Koteswararao4, Maddineni Venkata Jaya Prakash5
1Soniya Nuthalapati*, Department of Electronics & Communication Engineering, Jawaharlal Nehru Technological University, Kakinada. Guntur (A.P), India.
2Kusuma Nutalapati, Department of Electronics & Communication Engineering, Jawaharlal Nehru Technological University, Kakinada. Guntur (A.P), India.
3Naveen Laghuvarapu Prasad Nagipogu, Department of Electronics & Communication Engineering, Jawaharlal Nehru Technological University, Kakinada. Guntur (A.P), India.
4P. Yaswanth Sai Mandepudi Koteswararao, Department of Electronics & Communication Engineering, Jawaharlal Nehru Technological University, Kakinada. Guntur (A.P), India.
5Maddineni Venkata Jaya Prakash, Department of Electronics & Communication Engineering, Jawaharlal Nehru Technological University, Kakinada. Guntur (A.P), India.
Manuscript received on 29 March 2022. | Revised Manuscript received on 04 April 2022. | Manuscript published on 30 April 2022. | PP: 16-20 | Volume-11 Issue-5, April 2022. | Retrieval Number: 100.1/ijitee.E98470411522 | DOI: 10.35940/ijitee.E9847.0411522
Open Access | Ethics and 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: The impedance cardiography (ICG) shows the impedance caused in the heart. The ICG gives a clear and accurate results and the applied techniques reduce artifacts and also mathematical calculations. The ICG signal shows various physiological and non-physiological situations, and can calculate the heart volume. The computational complexity is also a main part for remote health care. The adaptive techniques used in this project reduces or removes the noise in the signal, Improve the signal. Mainly to take over the applied signal, convergence rate, and to reduce computations of the proposed theory, we added the sign and normalized adaptive algorithms to take out the realistic wave. In final, the results are taken out from the outcomes by additionally relating it with the adaptive filter to situate it in the proper format.
Keywords: Convergence Rate, Physiological, Non-Physiological and Adaptive Algorithms.
Scope of the Article: Healthcare Informatics