Real-Time Data Acquisition in Human Physiology (eBook)

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-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.

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.

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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-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.