Real-Time Data Acquisition in Human Physiology
Real-Time Acquisition, Processing, and Interpretation—A MATLAB-Based Approach
- 1st Edition - June 15, 2021
- Imprint: Academic Press
- Author: Dipali Bansal
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 2 2 1 1 8 - 1
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 2 1 5 6 - 3
Real-Time Data Acquisition in Human Physiology: Real-Time Acquisition, Processing, and Interpretation—A MATLAB-Based Approach focuses on the design and development of a computer-ba… Read more
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Request a sales quoteReal-Time Data Acquisition in Human Physiology: Real-Time Acquisition, Processing, and Interpretation—A MATLAB-Based Approach focuses on the design and development of a computer-based system to detect and digitally process human ECG, EMG, and carotid pulse waveforms in real time. The indigenous system developed and described in this book allows for an easy-to-interface, simple hardware arrangement for bio-signal detection. The computational functionality of MATLAB is verified for viewing, digital filtration, and feature extraction of acquired bio-signals.
This book demonstrates a method of providing a relatively cost-effective solution to human physiology real-time monitoring, processing, and interpretation that is more realizable and would directly benefit a larger population of patients.
- Presents an application-driven, interdisciplinary, and experimental approach to bio-signal processing with a focus on acquiring, processing, and understanding human ECG, EMG, carotid pulse data and HRV.
- Covers instrumentation and digital signal processing techniques useful for detecting and interpreting human physiology in real time, including experimental layout and methodology in an easy-to-understand manner.
- Discusses development of a computer-based system that is capable of direct interface through the sound port of a PC and does not require proprietary DAQ units and ADC units.
- Covers a MATLAB-based algorithm for online noise reduction, features extraction techniques, and infers diagnostic features in real time.
- Provides proof of concept of a PC-based twin channel acquisition system for the recognition of multiple physiological parameters.
- Establishes the use of Digital Signal Controller to enhance features of acquired human physiology.
- Presents the use of carotid pulse waveforms for HRV analysis in critical situations using a very simple hardware/software arrangement.
Graduates, PhD students, and lecturers in computer science, biomedical engineering, and electrical engineering, as well as scientific researchers in biomedical fields and clinicians
- Cover image
- Title page
- Table of Contents
- Copyright
- Preface
- Acknowledgment
- 1. Introduction
- Abstract
- 1.1 Rationale
- 1.2 Technical overview
- 1.3 Objectives
- References
- 2. PC-based data acquisition
- Abstract
- 2.1 Introduction
- 2.2 Sensors and transducers
- 2.3 Market research and latest developments in sensor technologies
- 2.4 Data acquisition system hardware
- 2.5 Data acquisition system software
- 2.6 Data acquisition systems market
- References
- 3. Detection and processing of real-time carotid pulse waves
- Abstract
- 3.1 Introduction
- 3.2 Experimental arrangement for detection of carotid pulse in real time
- 3.3 Digital filter designs
- 3.4 Simulated model for real-time carotid pulse detection and processing
- 3.5 Algorithm for real-time carotid pulse analysis
- 3.6 Conclusion
- References
- 4. Real-time detection and processing of electromyography signal
- Abstract
- 4.1 Introduction
- 4.2 Signal processing the electromyography data
- 4.3 Real-time detection and processing of electromyography signal in single channel mode
- 4.4 Real-time detection and processing of electromyography signal in dual channel mode
- 4.5 Standalone MATLAB code for physiological data detection and processing
- 4.6 Conclusion
- References
- 5. Real-time detection and processing of electrocardiogram signal
- Abstract
- 5.1 Introduction
- 5.2 Recent trends in cardiology
- 5.3 Notch filter designs for reducing power line interference in electrocardiogram signals
- 5.4 Real-time detection and processing of electrocardiogram signal
- 5.5 Digital signal controller-based electrocardiogram acquisition system
- 5.6 Conclusion
- References
- 6. Measurement and analysis of heart rate variability
- Abstract
- 6.1 Introduction
- 6.2 Heart rate variability metrics and norms
- 6.3 QRS detection methods
- 6.4 Real-time detection and analysis of heart rate variability
- 6.5 Conclusion
- References
- 7. Conclusion
- Abstract
- 7.1 Major contributions
- 7.2 Conclusion
- 7.3 Future directions
- References
- Index
- Edition: 1
- Published: June 15, 2021
- No. of pages (Paperback): 208
- No. of pages (eBook): 208
- Imprint: Academic Press
- Language: English
- Paperback ISBN: 9780128221181
- eBook ISBN: 9780128221563
DB
Dipali Bansal
Dr. Dipali Bansal is the Dean of Engineering at Graphic Era (Deemed to be University), Dehradun, India. She is part of a curiosity-driven research group working in the field of bio-signal processing that brings together experimental and theoretical techniques and approaches in acquiring and analyzing human physiological parameters, namely ECG, EMG, EEG signals, using professional tools like MATLAB and LabVIEW. She got her Bachelor’s degree from BIT Sindri and obtained a PhD in Bio-signal Processing from Jamia Millia Islamia Central University, New Delhi, India. In more than two decades of her professional career, she has honed her skills as an academician, a researcher, and also as an administrator.
Affiliations and expertise
Dean of Engineering, Graphic Era (Deemed to be University), Dehradun, IndiaRead Real-Time Data Acquisition in Human Physiology on ScienceDirect