University of Oulu

Särestöniemi M. et al. (2020) Detection of Brain Hemorrhage in White Matter Using Analysis of Radio Channel Characteristics. In: Alam M.M., Hämäläinen M., Mucchi L., Niazi I.K., Le Moullec Y. (eds) Body Area Networks. Smart IoT and Big Data for Intelligent Health. BODYNETS 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 330. Springer, Cham. https://doi.org/10.1007/978-3-030-64991-3_3

Detection of brain hemorrhage in white matter using analysis of radio channel characteristics

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Author: Särestöniemi, Mariella1; Pomalaza-Raez, Carlos2; Hakala, Jaakko3;
Organizations: 1Centre for Wireless Communications, University of Oulu, Finland
2Department of Electrical and Computer Engineering, Purdue University, USA
3Optoelectronics and Measurement Techniques Research Unit, Faculty of Information Technology and Electrical Engineering, University of Oulu, Finland
4Microelectronics Research Unit, Faculty of Information Technology and Electrical Engineering, University of Oulu, Finland
5Research Unit of Medical Imaging, Physics and Technology, Faculty of Medicine, University of Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 1.1 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe202102023482
Language: English
Published: Springer Nature, 2020
Publish Date: 2021-02-02
Description:

Abstract

This paper presents a simulation-based study on detection of stroke/brain hemorrhage even in the white matter using radio channel characteristics analysis. The idea is to utilize the fact that blood has different dielectric properties than brain’s white and grey matters and, thus, additional blood areas inside the brain change radio channel characteristics between the transmitter and receiver antennas located on the opposite sides of the head. The antennas should be strongly directive and designed to work attached to the body surface so that hemorrhages even in the white matter could be detected. The study is conducted using the electromagnetic simulation software CST and two different simulation models: a spherical tissue layer model and an anatomical voxel model. The antennas used in this study are bio-matched mini-horn antennas designed for implant communications at 1—4 GHz frequency range. Different sizes of the blood areas are evaluated. This initial study shows how even small sizes of hemorrhage can change radio channel even as the hemorrhage is located in the middle of the brain, in the white matter. The path loss difference is 0.5—10 dB between the hemorrhage and reference cases depending on the size and location of the hemorrhage. A practical solution of this hemorrhage detection technique could be a portable helmet type of structure having several small sized antennas around the internal part of the helmet. Such a helmet would be easy to use e.g. in ambulance, which would enable early detection of hemorrhage in its early phase and, hence, improve prospects of the cure significantly.

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Series: Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
ISSN: 1867-8211
ISSN-E: 1867-822X
ISSN-L: 1867-8211
ISBN: 978-3-030-64991-3
ISBN Print: 978-3-030-64990-6
Pages: 34 - 45
DOI: 10.1007/978-3-030-64991-3_3
OADOI: https://oadoi.org/10.1007/978-3-030-64991-3_3
Host publication: Body Area Networks. Smart IoT and Big Data for Intelligent Health 15th EAI International Conference, BODYNETS 2020, Tallinn, Estonia, October 21, 2020, Proceedings
Host publication editor: Alam, Muhammad Mahtab
Hämäläinen, Matti
Mucchi, Lorenzo
Niazi, Imran Khan
Le Moullec, Yannick
Conference: EAI Bodynets. EAI International Conference on Body Area Networks
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
Funding: This research has been financially supported by the project WBAN Communications in the Congested Environments and in part by Academy of Finland 6Genesis Flagship (grant 318927) and Academy of Finland grant 318347. This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 872752.
Academy of Finland Grant Number: 318927
318347
Detailed Information: 318927 (Academy of Finland Funding decision)
318347 (Academy of Finland Funding decision)
Copyright information: © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2020. This is a post-peer-review, pre-copyedit version of an article published in Body Area Networks. Smart IoT and Big Data for Intelligent Health 15th EAI International Conference, BODYNETS 2020, Tallinn, Estonia, October 21, 2020, Proceedings. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-64991-3_3.