TY - JOUR
T1 - The fractional Fourier transform as a biomedical signal and image processing tool
T2 - A review
AU - Gómez-Echavarría, Alejandro
AU - Ugarte, Juan P.
AU - Tobón, Catalina
N1 - Funding Information:
The Author A. Gómez-Echavarría was supported by the Grant 2019-2 of Fondo Sapiencia Posgrados Nacionales - Agencia de Educación Superior de Medellín - Sapiencia from Colombia.
Publisher Copyright:
© 2020 Nalecz Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/7/1
Y1 - 2020/7/1
N2 - This work presents a literature review of the fractional Fourier transform (FrFT) investigations and applications in the biomedical field. The FrFT is a time-frequency analysis tool that has been used for signal and image processing due to its capability in capturing the non-stationary characteristics of real signals. Most biomedical signals are an example of such non-stationarity. Thus, the FrFT-based solutions can be formulated, aiming to enhance the health technology. As the literature review indicates, common applications of the FrFT involves signal detection, filtering and features extraction. Establishing adequate solutions for these tasks requires a proper fractional order estimation and implementing the suitable numeric approach for the discrete FrFT calculation. Since most of the reports barely describe the methodology on this regard, it is important that future works include detailed information about the implementation criteria of the FrFT. Although the applications in biomedical sciences are not yet among the most frequent FrFT fields of action, the growing interest of the scientific community in the FrFT, supports its practical usefulness for developing new biomedical tools.
AB - This work presents a literature review of the fractional Fourier transform (FrFT) investigations and applications in the biomedical field. The FrFT is a time-frequency analysis tool that has been used for signal and image processing due to its capability in capturing the non-stationary characteristics of real signals. Most biomedical signals are an example of such non-stationarity. Thus, the FrFT-based solutions can be formulated, aiming to enhance the health technology. As the literature review indicates, common applications of the FrFT involves signal detection, filtering and features extraction. Establishing adequate solutions for these tasks requires a proper fractional order estimation and implementing the suitable numeric approach for the discrete FrFT calculation. Since most of the reports barely describe the methodology on this regard, it is important that future works include detailed information about the implementation criteria of the FrFT. Although the applications in biomedical sciences are not yet among the most frequent FrFT fields of action, the growing interest of the scientific community in the FrFT, supports its practical usefulness for developing new biomedical tools.
KW - Biomedical signal processing
KW - Fractional Fourier transform
KW - Non-stationary signals
KW - Time-frequency analysis
UR - http://www.scopus.com/inward/record.url?scp=85086895645&partnerID=8YFLogxK
U2 - 10.1016/j.bbe.2020.05.004
DO - 10.1016/j.bbe.2020.05.004
M3 - Artículo de revisión
AN - SCOPUS:85086895645
SN - 0208-5216
VL - 40
SP - 1081
EP - 1093
JO - Biocybernetics and Biomedical Engineering
JF - Biocybernetics and Biomedical Engineering
IS - 3
ER -