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
Hlavní autoři: Shitharth, S., Yonbawi, Saud, Manoharan, Hariprasath, Alahmari, Sultan, Yafoz, Ayman, Mujlid, Hana
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York IEEE 15.02.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algorithms
Augmented reality
Biomedical sensors
Force
Intelligent sensors
Mathematical models
Medical electronics
Medical services
Optimization
Real time
Real-time systems
Representations
Sensing units
Sensor phenomena and characterization
Sensors
Swarm intelligence
Virtual reality
ISSN:1530-437X, 1558-1748
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Abstract 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.
AbstractList Many people in society are facing problems related to health care, and diseases in the body are unable to be identified even with the presence of sensing technologies. The major reason for such failures in the identification process is that no virtual technologies are identified in the market. Most healthcare solicitations aim to design a particular application that provides information only about sensing values and fails to recall the virtual representation of that represented values. Therefore, this article provides an integration platform that connects the sensing devices with virtual reality/audio reality (VR/AR) techniques, which are 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 a modified fitness function and it is termed 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 the proposed method provides better numerical results with 65% full-scale representations and less than 0.5 dB of distortion at 0.3% tuning force.
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.
Author Alahmari, Sultan
Mujlid, Hana
Shitharth, S.
Manoharan, Hariprasath
Yonbawi, Saud
Yafoz, Ayman
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SubjectTerms Algorithms
Augmented reality
Biomedical sensors
Force
Intelligent sensors
Mathematical models
Medical electronics
Medical services
Optimization
Real time
Real-time systems
Representations
Sensing units
Sensor phenomena and characterization
Sensors
Swarm intelligence
Virtual reality
Title Physical Stint Virtual Representation of Biomedical Signals with Wireless Sensors Using Swarm Intelligence Optimization Algorithm
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