Development Of Microwave Brain Stroke Imaging System Using Multiple Antipodal Vivaldi Antennas Based On Raspberry Pi Technology
This paper proposes a Microwave Imaging System (MIS) for brain stroke detection. In the MIS, the primary challenge is to improve in terms of cost, size, and stroke image quality. Thus, the main contribution of this work is the economy and the compact rotation platform integrated with an array of nin...
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my.utem.eprints.248392021-03-01T14:56:59Z http://eprints.utem.edu.my/id/eprint/24839/ Development Of Microwave Brain Stroke Imaging System Using Multiple Antipodal Vivaldi Antennas Based On Raspberry Pi Technology Salleh, Azahari Islam, Mohammad Tariqul Ching, Chiou Yang Touhidul Alam, Touhidul Alam Jit Singh, Mandeep Singh Md. Samsuzzaman, Md. Samsuzzaman This paper proposes a Microwave Imaging System (MIS) for brain stroke detection. In the MIS, the primary challenge is to improve in terms of cost, size, and stroke image quality. Thus, the main contribution of this work is the economy and the compact rotation platform integrated with an array of nine antipodal Vivaldi antenna in circular arrangement and single computer board, Raspberry Pi Module (RPM) as microcontroller developed. The design and fabrication of wideband antenna based on Computer Simulation Technology (CST) software and Rogers RO4350B substrate, which operated from 2.06 GHz to 2.61 GHz. In the RPM, the Python programming language used for regulating the angle of rotation and antenna switching process. The process of receiving reflection signals from the head phantom for each antenna supervised by Single-Pole 8-Throw (SP8T) Radio Frequency (RF) switch. The fabricated head phantom based on the primary tissues of the brain, white matter using inexpensive materials, and located in the middle of the platform. Platform rotation is a combination of wood-based platform with the size 0.36m2 and material Perspex. Then, through an interfacing process between Python script and Vector Network Analyzer (VNA), the raw data in S-Parameters transferred to the MATLAB software for analysis. The fabricated antenna able to realize high directivity, 86.92% efficiency, and 2.45 dBi gain. Overall, the proposed system offers the cost-effective, compact, and able to collect the data effectively around the head phantom that consist of a target clot and without a target clot at 50 different positions. It successfully tracked the presence of stroke clots through color differences in color plots. Penerbit UKM 2020-02 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/24839/2/06.PDF Salleh, Azahari and Islam, Mohammad Tariqul and Ching, Chiou Yang and Touhidul Alam, Touhidul Alam and Jit Singh, Mandeep Singh and Md. Samsuzzaman, Md. Samsuzzaman (2020) Development Of Microwave Brain Stroke Imaging System Using Multiple Antipodal Vivaldi Antennas Based On Raspberry Pi Technology. Jurnal Kejuruteraan, 32 (1). pp. 39-49. ISSN 0128-0198 http://journalarticle.ukm.my/14841/1/06.pdf 10.17576/jkukm-2020-32(1)-06 |
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This paper proposes a Microwave Imaging System (MIS) for brain stroke detection. In the MIS, the primary challenge is to improve in terms of cost, size, and stroke image quality. Thus, the main contribution of this work is the economy and the compact rotation platform integrated with an array of nine antipodal Vivaldi antenna in circular arrangement and single computer board, Raspberry Pi Module (RPM) as microcontroller developed. The design and fabrication of wideband antenna based on Computer Simulation Technology (CST) software and Rogers RO4350B substrate, which
operated from 2.06 GHz to 2.61 GHz. In the RPM, the Python programming language used for regulating the angle of rotation and antenna switching process. The process of receiving reflection signals from the head phantom for each antenna supervised by Single-Pole 8-Throw (SP8T) Radio Frequency (RF) switch. The fabricated head phantom based on the primary tissues of the brain, white matter using inexpensive materials, and located in the middle of the platform. Platform rotation is a combination of wood-based platform with the size 0.36m2 and material Perspex. Then, through an interfacing process between Python script and Vector Network Analyzer (VNA), the raw data in S-Parameters transferred to the MATLAB software for analysis. The fabricated antenna able to realize high directivity, 86.92% efficiency, and 2.45 dBi gain. Overall, the proposed system offers the cost-effective, compact, and able to collect the data effectively around the head phantom that consist of a target clot and without a target clot at 50 different positions. It successfully tracked the presence of stroke clots through color differences in color plots. |
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Salleh, Azahari Islam, Mohammad Tariqul Ching, Chiou Yang Touhidul Alam, Touhidul Alam Jit Singh, Mandeep Singh Md. Samsuzzaman, Md. Samsuzzaman |
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Salleh, Azahari Islam, Mohammad Tariqul Ching, Chiou Yang Touhidul Alam, Touhidul Alam Jit Singh, Mandeep Singh Md. Samsuzzaman, Md. Samsuzzaman Development Of Microwave Brain Stroke Imaging System Using Multiple Antipodal Vivaldi Antennas Based On Raspberry Pi Technology |
author_facet |
Salleh, Azahari Islam, Mohammad Tariqul Ching, Chiou Yang Touhidul Alam, Touhidul Alam Jit Singh, Mandeep Singh Md. Samsuzzaman, Md. Samsuzzaman |
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Salleh, Azahari |
title |
Development Of Microwave Brain Stroke Imaging System Using Multiple Antipodal Vivaldi Antennas Based On Raspberry Pi Technology |
title_short |
Development Of Microwave Brain Stroke Imaging System Using Multiple Antipodal Vivaldi Antennas Based On Raspberry Pi Technology |
title_full |
Development Of Microwave Brain Stroke Imaging System Using Multiple Antipodal Vivaldi Antennas Based On Raspberry Pi Technology |
title_fullStr |
Development Of Microwave Brain Stroke Imaging System Using Multiple Antipodal Vivaldi Antennas Based On Raspberry Pi Technology |
title_full_unstemmed |
Development Of Microwave Brain Stroke Imaging System Using Multiple Antipodal Vivaldi Antennas Based On Raspberry Pi Technology |
title_sort |
development of microwave brain stroke imaging system using multiple antipodal vivaldi antennas based on raspberry pi technology |
publisher |
Penerbit UKM |
publishDate |
2020 |
url |
http://eprints.utem.edu.my/id/eprint/24839/2/06.PDF http://eprints.utem.edu.my/id/eprint/24839/ http://journalarticle.ukm.my/14841/1/06.pdf |
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