資料來源: Google Book

Biomedical signal analysis for connected healthcare[electronic resource]

  • 作者: Krishnan, Sridhar,
  • 出版: London : Academic Press 2021.
  • 稽核項: 1 online resource.
  • 標題: Medical informatics. , Electronic books. , Signal processing. , Medical Informatics , Biomedical engineering.
  • ISBN: 0128130865 , 9780128130865
  • 試查全文@TNUA:
  • 附註: Includes index. Front Cover -- Biomedical Signal Analysis for Connected Healthcare -- Biomedical Signal Analysis for Connected Healthcare -- Copyright -- Dedication -- Contents -- About the author -- Preface -- 1 -- Opportunities for connected healthcare -- 1. Introduction -- 2. Internet of things -- 2.1 Hardware -- 2.2 Software -- 3. Internet of medical things -- 3.1 Remote health monitoring -- 3.2 Smartphone application -- 4. Wearables for health monitoring -- 5. Biomedical signals -- 5.1 ECG signal -- 5.2 EEG signal -- 5.3 EMG signal -- 5.4 PPG signal -- 5.5 Speech signal 6. Objectives and organization of the book -- References -- 2 -- Wearables design -- 1. Introduction -- 2. Wearables survey -- 2.1 EEG-based wearable devices -- 2.1.1 About EEG signals: properties and acquisition -- 2.1.2 Existing technology, drawbacks, and opportunities -- 2.1.3 Comparison with clinical EEG data -- 2.2 EMG-based wearable devices -- 2.2.1 About EMG signals: properties and acquisition -- 2.2.2 Existing technology, drawbacks, and opportunities -- 2.2.3 Comparison with clinical EMG data -- 2.3 ECG-based wearable devices -- 2.3.1 About ECG signals: properties and acquisition 2.3.2 Existing technology, drawbacks, and opportunities -- 2.3.3 Comparison with clinical ECG data -- 2.4 Other electronic wearables -- 2.4.1 Photoplethysmogram -- 2.4.2 Auscultation of body sounds -- 2.4.3 Motion and gait analysis -- 3. Wearables design considerations -- 3.1 Signal factors -- 3.2 Human factors -- 3.3 Environmental factors -- 3.4 Medical factors -- 3.5 Economic factors -- 3.6 Other critical factors -- 4. Open hardware design considerations -- 4.1 Allocation of hardware design -- 4.2 Hardware requirements and methods -- 4.2.1 PPG sensor description and bioinstrumentation 4.2.2 EMG sensor requirements and description -- 4.2.3 ECG sensor requirements and description -- 4.2.4 Microphone requirements and description -- 4.2.5 Motion analysis IMU requirements and description -- 4.2.6 Perspectives on wearables hardware design -- 5. Textile wearables -- 6. Contactless monitoring -- 7. Discussions -- References -- 3 -- Biomedical signals and systems -- 1. Introduction -- 2. Analog to digital conversion -- 2.1 Sampling -- 2.2 Quantization -- 2.2.1 Noise power -- 2.2.2 Signal power: Vp2 -- 3. Linear systems theory -- 3.1 Stability and causality -- 3.2 Frequency response 4. Digital filters design -- 4.1 Design of FIR filters -- 4.2 Design of IIR filters -- 4.2.1 Method 1: Pole-zero placement method of IIR filter design -- 4.2.2 Method 2: Impulse-invariant method of IIR filter design -- 4.2.3 Method 3: Bilinear z-transform method of IIR filter design -- 4.2.3.1 BZT method for LPF design -- 4.2.3.2 BZT method for HPF design -- 4.3 Phase response considerations -- 4.4 Homomorphic filtering -- 5. Digital filter realization -- 5.1 FIR filter realization -- 5.2 IIR filter realization -- 6. Applications -- 6.1 Application 1: Noise filtering techniques
  • 電子資源: https://dbs.tnua.edu.tw/login?url=https://www.sciencedirect.com/science/book/9780128130865
  • 系統號: 005324248
  • 資料類型: 電子書
  • 讀者標籤: 需登入
  • 引用網址: 複製連結
Biomedical Signal Analysis for Connected Healthcare provides rigorous coverage on several generations of techniques, including time domain approaches for event detection, spectral analysis for interpretation of clinical events of interest, time-varying signal processing for understanding dynamical aspects of complex biomedical systems, the application of machine learning principles in enhanced clinical decision-making, the application of sparse techniques and compressive sensing in providing low-power applications that are essential for wearable designs, the emerging paradigms of the Internet of Things, and connected healthcare. Provides comprehensive coverage of biomedical engineering, technologies, and healthcare applications of various physiological signals Covers vital signals, including ECG, EEG, EMG and body sounds Includes case studies and MATLAB code for selected applications
來源: Google Book
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