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2023 | Buch

Introduction Kapitel lesen Erstes Kapitel lesen

High Performance and Power Efficient Electrocardiogram Detectors

verfasst von: Ashish Kumar, Manjeet Kumar, Rama S. Komaragiri

Verlag: Springer Nature Singapore

Buchreihe : Energy Systems in Electrical Engineering

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik"

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Über dieses Buch

This book details the characteristics of an ECG signal through the functionality and electrical activity of the human heart. This book provides a basic introduction and needs for developing implantable cardiac pacemaker systems. This book provides comprehensive details on ECG signal processing techniques that are useful for fast and accurate diagnosis of cardiovascular diseases. The book discusses the characteristics and parameters of a typical ECG signal and various noises that can corrupt an ECG signal. It also covers various challenges involved in different stages of signal acquisition, preprocessing, and detection of an ECG signal. The book also presents a detailed survey of various ECG signal detection and data compression techniques. The book contains detailed information on ECG signals and various noises that corrupt an ECG signal. It also includes de-noising techniques, ECG peak detection techniques, and ECG data compression techniques. It also includes step-by-step details to design various filters in MATLAB. This book, through detailed explanations, provides the reader with necessary information on ECG signal, ECG signal acquisition process, noise removal techniques, and the detection of ECG peaks.

Inhaltsverzeichnis

Frontmatter
Chapter 1. Introduction
Abstract
A cardiac pacemaker is a device that treats cardiac dysrhythmia by rapidly tracking the heart rate and rhythm of a subject. Cardiac pacemakers deliver rhythmic electric stimulus in a controlled manner to the heart to maintain the heartbeat. The ability to deliver a periodic and administrated electric stimulus made the implantable and wearable cardiac pacemakers a reality in today’s globally emerging world of healthcare devices. Different researchers have not only made the heavy pacemakers undergo a physical change in terms of reduction in size and weight but also economical and within reach to many, thus being a lifesaver. A discussion on the functionality of the human heart through its electrical activity is presented in this chapter. Also, the characteristics and parameters of a typical ECG signal and various noises that corrupt an ECG signal are discussed.
Ashish Kumar, Manjeet Kumar, Rama S. Komaragiri
Chapter 2. Existing Methods to Evaluate Pacemaker Device Performance
Abstract
With the alarming rise in deaths due to cardiovascular diseases (CVD), the present medical research scenario emphasizes techniques and methods to detect CVDs. As the world health organization adduced, technological proceeds in cardiac function assessment have become the nucleus and heart of all leading research studies on CVDs. Electrocardiogram (ECG) analysis is the most functional and convenient tool used to test the range of heart-related irregularities. Most of the approaches present in the literature on ECG signal analysis consider noise removal, rhythm-based analysis, and heartbeat detection to improve the performance of a cardiac pacemaker. Advancements in ECG segment detection and beat classification have a limited evaluation and still require clinical approvals. This chapter discusses approaches and techniques to implement an on-chip ECG detector for a cardiac pacemaker system. Moreover, different challenges regarding the ECG signal morphology analysis deriving from the medical literature are extensively reviewed.
Ashish Kumar, Manjeet Kumar, Rama S. Komaragiri
Chapter 3. ECG Signal Denoising Techniques for Cardiac Pacemaker Systems
Abstract
Electrocardiogram (ECG) signals are used to diagnose cardiovascular diseases. Various noises like power line interference, baseline wandering, motion artifacts, and electromyogram noise corrupt the ECG signal during ECG signal acquisition. As ECG signal is non-stationary, removing these noises from the recorded ECG signal is tricky. This chapter studies various ECG signal denoising techniques to denoise an ECG signal corrupted with noise.
Ashish Kumar, Manjeet Kumar, Rama S. Komaragiri
Chapter 4. ECG Signal Detection and Lossless Data Compression Techniques for Implantable Cardiac Pacemaker Systems
Abstract
The current trends and medical scenarios have given birth to several QRS-complex detection algorithms. The striking feature of all these detection algorithms is reduced power consumption which is an enabler of wearable devices. The research in wearable devices has integrated both unified lossy and lossless data compression techniques together. The research advancements in cardiac health monitoring have made it quantifiable to note the reduction in the sensor power by 2–5 times. It is comprehended that implementation and combination of two distinct hardware setups for QRS-complex detection and compression lead to increased system computations and power. Therefore, it is of utmost importance to have a joint QRS-complex detection and lossless data compression algorithm. In this chapter, an improved wavelet transform-based joint ECG detection, and data compression algorithm applicable for the implantable cardiac pacemaker system is presented.
Ashish Kumar, Manjeet Kumar, Rama S. Komaragiri
Chapter 5. FPGA Implementation of Combined ECG Signal Denoising, Peak Detection Technique for Cardiac Pacemaker Systems
Abstract
Cardiovascular diseases (CVD) are becoming significant for the ever-increasing mortality rates. Portable ECG devices are gaining importance and acceptance by medical practitioners as real-time human heart health monitoring devices. Holter devices cannot deliver real-time diagnosis requirements to identify arrhythmia, thus limiting their usage in critical conditions. Hence, there is a need to develop energy-efficient ECG detection algorithms for implantable and portable cardiac devices to monitor arrhythmia. A high-performance and energy-efficient electrocardiogram (ECG) detector to develop modern implantable cardiac pacemaker systems is presented in this chapter.
Ashish Kumar, Manjeet Kumar, Rama S. Komaragiri
Chapter 6. Digital ECG Signal Watermarking and Compression
Abstract
Data privacy on the Internet seems to be becoming a thing of the past. It is going to be a struggle for individuals to manage personal medical information on the Internet. ECG data is considered as the most vulnerable dataset. To safeguard and protect the personal ECG data, the use of security schemes like watermarking of ECG data is the focus of the present Chapter.
Ashish Kumar, Manjeet Kumar, Rama S. Komaragiri
Chapter 7. Basic Formation on Wavelet Transforms
Abstract
Use wavelets developed in the recent past have paved the way for applying a wavelet transform to biomedical signal analysis. Existing literature showcases thirteen wavelet families well archived and cataloged. The study so far in the literature put forward a clear perspective for selecting the best−suited base wavelet for functional signal processing. The fundamental properties support only the qualitative acceptance and fitment for a specific application, thus making a study of quantitative measures in the selection of base wavelet a much−required approach. A detailed study about the wavelet families, coefficients, and their shapes is presented in this chapter. Also, detailed information about wavelet signal denoising app is presented.
Ashish Kumar, Manjeet Kumar, Rama S. Komaragiri
Chapter 8. Conclusion and Future Work
Abstract
This work studies wave detection and lossless data compression of an ECG signal using adaptive slope prediction thresholding and a biorthogonal 3.1 wavelet transform-based filter bank realized using linear phase array structure and achieved an SNR of −53.92 dB. It is found that the combination of ECG signal detection and lossless ECG data compression reduces the false wave detection and increases the ECG data compression ratio, thus facilitating a speedy transmission and efficient bandwidth utilization. The proposed ECG detector realized using an FPGA showed significant improvements in power consumption, area, delay, and switching energy. The proposed methodology can be further extended to analyze various biomedical signals.
Ashish Kumar, Manjeet Kumar, Rama S. Komaragiri
Backmatter
Metadaten
Titel
High Performance and Power Efficient Electrocardiogram Detectors
verfasst von
Ashish Kumar
Manjeet Kumar
Rama S. Komaragiri
Copyright-Jahr
2023
Verlag
Springer Nature Singapore
Electronic ISBN
978-981-19-5303-3
Print ISBN
978-981-19-5302-6
DOI
https://doi.org/10.1007/978-981-19-5303-3

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