Physical Stint Virtual Representation of Biomedical Signals with Wireless Sensors Using Swarm Intelligence Optimization Algorithm
Many people in the society are facing problems related to health care and the diseases in the body are unable to be identified even with the presence of sensing technologies. The major reason for such failure in identification process is that no virtual technologies are identified in market. Most of...
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| Vydáno v: | IEEE sensors journal Ročník 23; číslo 4; s. 1 |
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| Hlavní autoři: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
New York
IEEE
15.02.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Témata: | |
| ISSN: | 1530-437X, 1558-1748 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Many people in the society are facing problems related to health care and the diseases in the body are unable to be identified even with the presence of sensing technologies. The major reason for such failure in identification process is that no virtual technologies are identified in market. Most of the health care solicitations aim to design a particular application that provides information only about sensing values and fail to recall the virtual representation of that represented values. Therefore, this article provides an integration platform that connects the sensing devices with Virtual/ Audio Reality (VR/AR) techniques where it is applied in real time for detecting the presence of infections inside the body. In addition, one type of swarm intelligent algorithm is implemented in the recognition procedure with modified fitness function and it is termed as Fruit Fly Optimization (FFO). The process of FFO provides much low layer perception thus enhancing the output for smooth operation. To examine the real time conditions the projected AR/VR procedure is applied with biomedical sensors where three different case studies are separated. From the comparative numerical results it is pragmatic that proposed method provides better numerical results with 65 percentage full scale representations, less than 0.5 dB of distortion at 0.3 percentage of tuning force. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 1530-437X 1558-1748 |
| DOI: | 10.1109/JSEN.2022.3233407 |