| Issue |
E3S Web Conf.
Volume 430, 2023
15th International Conference on Materials Processing and Characterization (ICMPC 2023)
|
|
|---|---|---|
| Article Number | 01189 | |
| Number of page(s) | 5 | |
| DOI | https://doi.org/10.1051/e3sconf/202343001189 | |
| Published online | 06 October 2023 | |
Smart Medical Assistance using Soft Computing
1 Assistant Professor, Department of Biomedical Engineering, Vignan’s Foundation for Science Technology and Research, India - 522213
2a,b,c UG Student, Department of Biomedical Engineering , Vignan’s Foundation for Science Technology and Research, India - 522213
3 Uttaranchal University Uttarakhand, India - 248007
4 Department of Computer Science and Engineering, GRIET, Bachupally, Hyderabad, Telangana, ramesh680@gmail.com
5 Lovely Professional University, Phagwara Punjab, 144001, India
6 KG Reddy College of Engineering & Technology, lrgupta528@gmail.com
* katikala.himabindu@gmail.com, 2amanojkumarkommuri2001@gmail.com, 2bloshalikamalapati@gmail.com, 2cgreeshmanthchowdary16@gmail.com
In recent years, in consumer electronics, the Health care system is the most important one to evaluate humans' diverse pathological activities. Collaborating with the biomedical field, electronics can find remedial designs for an artificial implant that functionalizes as a human organ to deal with different prostheses, therapy dialysis, etc., conditions and analyze the neural system responses. Using the advanced technological approach, the desired sub-blocks are to be designed to improve the Implant’s performance, especially in cost & market- production. This paper briefly explains the Bionic hearing-aid Implant recognized as a Cochlear implant and its architecture in.
Key words: Cochlear Implant (CI) / Fin Field Effect Transistor (FINFET) / Electrode Array / Back Telemetry
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.