Version 1
: Received: 24 October 2023 / Approved: 25 October 2023 / Online: 25 October 2023 (08:00:28 CEST)
How to cite:
Zhao, M. Recent Progresses in Signal Processing for Alzheimer's Disease Detection. Preprints2023, 2023101600. https://doi.org/10.20944/preprints202310.1600.v1
Zhao, M. Recent Progresses in Signal Processing for Alzheimer's Disease Detection. Preprints 2023, 2023101600. https://doi.org/10.20944/preprints202310.1600.v1
Zhao, M. Recent Progresses in Signal Processing for Alzheimer's Disease Detection. Preprints2023, 2023101600. https://doi.org/10.20944/preprints202310.1600.v1
APA Style
Zhao, M. (2023). Recent Progresses in Signal Processing for Alzheimer's Disease Detection. Preprints. https://doi.org/10.20944/preprints202310.1600.v1
Chicago/Turabian Style
Zhao, M. 2023 "Recent Progresses in Signal Processing for Alzheimer's Disease Detection" Preprints. https://doi.org/10.20944/preprints202310.1600.v1
Abstract
Alzheimer's Disease (AD) is a neurodegenerative disease that is common in the elderly. This paper introduces the overview of Alzheimer's disease and the application of relevant signal processing methods in its detection. Signal processing is a technique that converts raw data into meaningful information and is widely used in the medical field. This paper lists common signal processing techniques, including Fourier transform, time-frequency analysis and statistical signal processing, and discusses their applications in the detection of Alzheimer's disease. Fourier transform can convert time domain signals into frequency domain representations, providing an effective tool for the study of EEG in Alzheimer's disease. Time-frequency analysis can perform a combined time and frequency analysis of the signal to help detect the signal characteristics of Alzheimer's disease. Statistical signal processing methods can be used to identify the features of Alzheimer's disease by building mathematical models. Finally, the challenges of Alzheimer's disease detection are discussed, including signal noise, diversity, and insufficient data volume. Through in-depth research and development of signal processing methods, it is expected to improve the accuracy and efficiency of early detection of Alzheimer's disease.
Keywords
Alzheimer's disease; signal processing methods; Fourier transform; time-frequency analysis; statistical signal processing; EEG; signal characteristics; signal noise
Subject
Public Health and Healthcare, Primary Health Care
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
