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Analysis of energy relations between noise and vibration signals in the scanning area of an open-air MRI device
Jiri Pribil * 1 , Anna Pribilova 2 , Ivan Frollo 3
1  Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovak Republic.
2  Slovak University of Technology in Bratislava, Faculty of Electrical Engineering and Information Technology, Bratislava, Slovak Republic.
3  Institute of Measurement Science, Slovak Academy of Sciences, Bratislava, Slovak Republic

Published: 14 November 2018 by MDPI AG in 5th International Electronic Conference on Sensors and Applications session Applications
10.3390/ecsa-5-05730
Abstract:

An open-air magnetic resonance imaging (MRI) tomograph is a huge intelligent sensor used for non-invasive scanning of various parts of a human body without being a burden to it as in the case of X-ray equipment. MRI is successfully used for health monitoring of therapy progress after vocal fold cancer surgery or monitoring of cartilage recovery in legs or arms after their implantation, etc. For selection of 3-D coordinates of a tested object, the MRI device contains a gradient system producing a significant mechanical vibration causing image blurring and an acoustic noise significantly degrading the simultaneously recorded speech signal during MR scanning of the human vocal tract. There is also a negative effect on a person’s psychical state depending on the intensity and time duration of the exposition. Vibration and noise energy relationships in the MRI scanning area must be mapped to minimize these factors. The paper analyzes how different setting of MR scan sequence parameters (echo time, repetition time, orientation of scan slices, sequence type, tested object mass) affects the energy of the produced noise and vibration. Measured sound pressure levels together with recorded noise and vibration signals were stored in a database and then processed using similar methods as in speech signal analysis because the main frequencies of the acoustic noise and vibration lie in the standard audio frequency range. In the signal processing phase, four types of parameters describing the signal energy were determined, statistically analyzed, and the obtained results were visually and numerically compared.

Keywords: Keywords: magnetic resonance imaging; acoustic noise; mechanical vibration
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