A4 Refereed article in a conference publication
A Miniaturized MEMS Motion Processing System for Nuclear Medicine Imaging Applications
Authors: Mojtaba Jafari Tadi, Eero Lehtonen, Jarmp Teuho, Antti Saraste, Mikko Pänkäälä, Mika Teräs, Tero Koivisto
Editors: Alan Murray
Conference name: Computing in Cardiology
Publication year: 2016
Journal: Computing in Cardiology
Book title : Computing in Cardiology 2016
Series title: Computing in Cardiology
Volume: 43
First page : 133
Last page: 136
Number of pages: 4
eISBN: 978-1-5090-0895-7
ISSN: 2325-887X
DOI: https://doi.org/10.22489/CinC.2016.042-452
Self-archived copy’s web address: http://www.cinc.org/archives/2016/pdf/042-452.pdf
Cardiac, respiratory, and patient body motion artifacts
degrade the image quality and quantitative accuracy of
the nuclear medicine imaging which may lead to incorrect
diagnosis, unnecessary treatment and insufficient therapy.
We present a new miniaturized system including joint micro electromechanical (MEMS) accelerometer and gyroscope sensors for simultaneous extraction of cardiac and
respiratory signals. We employ two tri-axial joint MEMS
sensors for selecting an optimal trigger point in a cardiac
and respiratory cycle. The 6-axis motion sensing helps
to detect candidate features for cardiac and respiratory
gating in Positron emission tomography (PET) imaging.
The aim of this study was to validate MEMS-derived signals against traditional Real-time Position Management
(RPM) and electrocardiography (ECG) measurement systems in 4 healthy volunteers. High agreement and correlation were found between cardiac and respiratory cycle
intervals. These promising first results warrant for further
investigations.
Downloadable publication This is an electronic reprint of the original article. |  |
