Singular Spectrum Analysis of Biomedical Signals (Hardcover)

Recent advancements in signal processing and computerised methods are expected to underpin the future progress of biomedical research and technology, particularly in measuring and assessing signals and images from the human body. This book focuses on singular spectrum analysis (SSA), an effective approach for single channel signal analysis, and its bivariate, multivariate, tensor based, complex-valued, quaternion-valued and robust variants.

SSA currently has numerous applications in detecting abnormalities in quasi-periodic biosignals, such as electrocardiograms, (ECGs or EKGs), oxygen levels, arterial pressure, and electroencephalograms (EEGs). Singular Spectrum Analysis of Biomedical Signals presents relatively newly applied concepts for biomedical applications of SSA, including:

• Signal source separation, extraction, decomposition, and factorization
• Physiological, biological, and biochemical signal processing
• A new SSA grouping algorithm for filtering and noise reduction of genetics data
• Prediction of various clinical events

The book introduces a new mathematical and signal processing technique for the decomposition of widely available single channel biomedical data. It also provides illustrations of new signal processing results in the form of signals, graphs, images, and tables to reinforce understanding of the related concepts.

Singular Spectrum Analysis of Biomedical Signals enhances current clinical knowledge and aids physicians in improving diagnosis, treatment and monitoring some clinical abnormalities. It also lays groundwork for progress in SSA by making suggestions for future research.

近年來，信號處理和計算方法的最新進展被認為將支撐生物醫學研究和技術的未來發展，特別是在測量和評估人體信號和圖像方面。本書專注於奇異譜分析（SSA），這是一種有效的單通道信號分析方法，以及其雙變量、多變量、張量、複數、四元數和魯棒變體。

SSA目前在檢測類周期生物信號（如心電圖、氧氣水平、動脈壓力和腦電圖）方面具有眾多應用。《生物醫學信號的奇異譜分析》介紹了SSA在生物醫學應用中相對較新的概念，包括：

- 信號來源分離、提取、分解和因子分解
- 生理、生物和生化信號處理
- 一種新的SSA分組算法，用於過濾和降噪基因數據
- 預測各種臨床事件

本書介紹了一種用於分解廣泛可用的單通道生物醫學數據的新數學和信號處理技術。它還通過信號、圖形、圖像和表格的形式提供了新的信號處理結果的示例，以加強對相關概念的理解。

《生物醫學信號的奇異譜分析》增強了當前的臨床知識，幫助醫生改善診斷、治療和監測某些臨床異常。它還為SSA的進一步研究提出了未來研究的建議。