Biomedical Signal Analysis for Connected Healthcare 1st Edition by Sridhar Krishnan ISBN 9780128130865 0128130865

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Product details:
ISBN 10: 0128130865
ISBN 13: 9780128130865
Author: Sridhar Krishnan

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

Biomedical Signal Analysis for Connected Healthcare 1st Edition Table of contents:

1. Opportunities for connected healthcare

1. Introduction

2. Internet of things

3. Internet of medical things

4. Wearables for health monitoring

5. Biomedical signals

6. Objectives and organization of the book

2. Wearables design

1. Introduction

2. Wearables survey

3. Wearables design considerations

4. Open hardware design considerations

5. Textile wearables

6. Contactless monitoring

7. Discussions

3. Biomedical signals and systems

1. Introduction

2. Analog to digital conversion

3. Linear systems theory

4. Digital filters design

5. Digital filter realization

6. Applications

7. Discussion

4. Adaptive analysis of biomedical signals

1. Introduction

2. Adaptive filter design

3. Adaptive filter algorithms

4. Linear prediction

5. Time series modeling

6. Applications

7. Discussion

5. Advanced analysis of biomedical signals

1. Introduction

2. Time-domain analysis

3. Frequency-domain analysis

4. Joint time-frequency analysis

5. Signal decomposition analysis

6. Advanced feature extraction and analysis

7. Sparse analysis and compressive sensing

8. Discussion

6. Machine learning for biomedical signal analysis

1. Introduction

2. Machine learning fundamentals

3. Types of machine learning models

4. Challenges with machine learning models

5. Feature analysis

6. Common machine learning techniques

7. Machine learning performance metrics

8. Fairness and ethics in ML

9. Summary

7. Data connectivity and application scenarios

1. Introduction

2. Pulse code modulation

3. Delta modulation

4. Lossless data compression

5. Line coding of waveforms

6. Digital modulation

7. Telecommunication networks

8. Wireless technologies

9. Mobile health

10. Electronic medical records

11. Personal health record

12. Interoperability

13. Health information security and privacy

14. Human factors and user experiences

15. Application scenarios

16. Summary

Index

 

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Tags: Sridhar Krishnan, Biomedical Signal Analysis, Connected Healthcare