University of Oulu

Särestöniemi M., Pomalaza-Raez C., Sayrafian K., Myllylä T., Iinatti J. (2022) A Preliminary Study of RF Propagation for High Data Rate Brain Telemetry. In: Ur Rehman M., Zoha A. (eds) Body Area Networks. Smart IoT and Big Data for Intelligent Health Management. BODYNETS 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 420. Springer, Cham. https://doi.org/10.1007/978-3-030-95593-9_11

A preliminary study of RF propagation for high data rate brain telemetry

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Author: Särestöniemi, Mariella1,2; Pomalaza-Raez, Carlos3; Sayrafian, Kamran4;
Organizations: 1Centre for Wireless Communications, University of Oulu, Finland
2Research Unit of Medical Imaging, Physics and Technology, Faculty of Medicine, University of Oulu, Finland
3Purdue University of Technology, USA
4National Institute of Standards and Technology, Maryland, USA
55Optoelectronics and Measurement Techniques Research Unit, Faculty of Information Technology and Electrical Engineering, University of Oulu, Finland
Format: article
Version: accepted version
Access: embargoed
Persistent link: http://urn.fi/urn:nbn:fi-fe2022021118627
Language: English
Published: Springer Nature, 2022
Publish Date: 2023-02-11
Description:

Abstract

This paper presents the preliminary results of a study on the radio frequency (RF) propagation inside the human skull at several Industrial, Scientific and Medical (ISM) and ultrawideband UWB frequencies. These frequency bands are considered as possible candidates for high data rate wireless brain telemetry. The study is conducted using a high-resolution 3D computational model of the human head. Power flow analysis is conducted to visualize propagation inside the brain for two different on-body antenna locations. Furthermore, channel attenuation between an on-body directional mini-horn antenna and an implant antenna at different depths inside the brain is evaluated. It is observed that radio frequency propagation at 914 MHz sufficiently covers the whole volume of the brain. The coverage reduces at higher frequencies, specially above 3.1 GHz. The objective of this comparative analysis is to provide some insight on the applicability of these frequencies for high data rate brain telemetry or various monitoring, and diagnostic tools.

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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: 978-3-030-95593-9
ISBN Print: 978-3-030-95592-2
Volume: 420
Pages: 126 - 138
DOI: 10.1007/978-3-030-95593-9_11
OADOI: https://oadoi.org/10.1007/978-3-030-95593-9_11
Host publication: Body Area Networks. Smart IoT and Big Data for Intelligent Health Management: 16th EAI International Conference, BODYNETS 2021, Virtual Event, October 25-26, 2021, Proceedings
Host publication editor: Rehman, Masood Ur
Zoha, Ahmed
Conference: EAI International Conference on Body Area Networks
Type of Publication: A4 Article in conference proceedings
Field of Science: 217 Medical engineering
Subjects:
Funding: This work is supported by Academy of Finland 6Genesis Flagship (grant 318927) and the European Union’s Horizon 2020 programme under the Marie Sklodowska-Curie grant agreement No. 872752.
EU Grant Number: (872752) ROVER - RELIABLE TECHNOLOGIES AND MODELS FOR VERIFIED WIRELESS BODY-CENTRIC TRANSMISSION AND LOCALIZATION
Academy of Finland Grant Number: 318927
Detailed Information: 318927 (Academy of Finland Funding decision)
Copyright information: © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2022. “This is a post-peer-review, pre-copyedit version of an article published in Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. The final authenticated version is available online at https://doi.org/10.1007/978-3-030-95593-9_11.