Dipali Bansal - Real-Time Data Acquisition in Human Physiology: Real-Time Acquisition, Processing, and Interpretation—A MATLAB-Based Approach

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Dipali Bansal

Dean of Engineering, Graphic Era (Deemed to be University), Dehradun, India

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Understanding human physiology is vital to define and design a fool-proof analytical method that encapsulates all the minor and significant signals which would lead to the correct diagnosis of a disease. Bio-signal data acquisition and their processing are a precursor for diagnostic system development. An underlying condition or disease not only needs to be diagnosed but also should be monitored and a suitable therapy needs to be provided for recovery and rehabilitation. Real-time acquisition and processing of human physiology has become indispensable as an interdisciplinary tool, which along with advancements in computational algorithms, medical science, signal processing techniques, communication engineering, and big data practices could bridge the gap and promote the universal health goals.

Existing data acquisition systems (DAQ) enable detection, processing, monitoring and analysis of human physiology, and cater to a wide range of clinical and nonclinical circumstances. Their cost-effectiveness, quality, compactness, ease of use, reduced power requirements, availability, and so on are the prime factors based on which they can be assessed objectively. A lot has been achieved in this domain; however there is still scope for improvement in terms of noise immunity, universal connectivity, real-time processing, and analysis, and also because these systems are still unaffordable and beyond the reach of common man. Modern tools and techniques that have enabled the deployment of portable computer-based DAQ can facilitate continuous monitoring of human physiology in a much simpler and affordable manner.

The book Real-Time Data Acquisition in Human Physiology emphasizes the strategy and deployment of a PC-based arrangement for real-time acquisition, processing, and analysis of human electrocardiogram (ECG), electromyogram (EMG), and carotid pulse waveforms. The indigenous system designed and described in this book allows 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 and realizable explanation to real-time monitoring, assessment, and evaluation of human physiology that can directly benefit the mass.

Key features of the book include 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 heart rate variability (HRV). It 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. Detailed discussion is presented on the development of a computer-based system that offers direct connectivity with a computer via its sound card and eliminates the requirement of proprietary DAQ and ADC subsystems. It also covers MATLAB-based algorithm for online noise reduction and feature extraction and can infer diagnostic features in real time. Proof of concept is provided for a PC-based twin channel acquisition system for recognition of multiple physiological parameters. The use of digital signal controller to enhance features of acquired human physiology has also been explained. It also presents the concept that carotid pulsation can be utilized for HRV analysis in critical circumstances using a very simple hardware/software arrangement.