학술논문

UWB Microwave Functional Brain Activity Extraction for Parkinson’s Disease Monitoring
Document Type
Periodical
Source
IEEE Sensors Journal IEEE Sensors J. Sensors Journal, IEEE. PP(99):1-1
Subject
Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Robotics and Control Systems
Diseases
Photodiodes
Imaging
Monitoring
Probes
Radio frequency
Microwave theory and techniques
UWB Functional Imaging
Action Potential
UWB Pulse Amplitude Modulation
Functional Diseases
Parkinson’s Disease
Language
ISSN
1530-437X
1558-1748
2379-9153
Abstract
Microwaves have proven their imaging capabilities to visualize the body composition for medical applications thanks to their penetration inside biological structures. In this context, this paper presents a novel methodology that aims to extract not just the internal morphology but also the brain’s functional activity using the UWB Pulse Amplitude Modulation (PAM) technique to have simultaneously functional monitoring and imaging capability and apply it to monitor the Parkinson’s disease. The radiofrequency system is composed of two orthogonal sets of double UWB probes operating in the frequency range of 0.5 GHz - 1.5 GHz. An experimental set-up has been devised that avoids complex in-vivo testing, albeit allows a system proof-of-concept validation. A bio-tag consisting of an optically modulated photodiode is used to emulate local medium changes associated to cell activity. The proposed system is used to first extract the modeled brain Action Potential (AP) to validate the performance of the bio-tag, and then to monitor the Parkinson’s disease (PD) based on the beta frequency band character within basal ganglia–thalamocortical (BGTC) which is a key marker for the PD. The results show a good capability of locating and differentiating the signals generated within the phantom by the bio-tag, alternatively emulating the healthy and PD’s state, based on the frequency. The obtained results of the functional monitoring technique on distinguishing the healthy from non-healthy brain model activity, as well as in the phantom mimicking the average proprieties of a human head, will serve as a basis for detecting functional diseases in the future.