| Description |
1 online resource (234 p.) |
| Contents |
Intro -- New Frontiers of Cardiovascular Screening using Unobtrusive Sensors, AI, and IoT -- Copyright -- Dedication -- Contents -- Foreword -- Preface -- About the authors -- Section 1: Sensors, AI and IoT in cardiovascular diseases -- Chapter 1: Cardiovascular conditions: The silent killer -- 1. Introduction -- 2. Industrial revolution and Healthcare 4.0 -- 2.1. PhysioNet challenge -- 3. Chronic diseases and cardiovascular issues -- 4. Cardiovascular diseases: A silent killer -- 4.1. Factors enhancing cardiac risks -- 4.2. Heart rate, arrhythmia, and atrial fibrillation |
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4.3. Coronary artery disease and ischemic heart diseases -- 4.4. Cardiac fatigue and hypertension -- 4.4.1. Cardiac fatigue -- 4.4.2. Hypertension -- 4.4.3. Regulation of blood pressure -- 5. Sleep apnea and pulmonary conditions -- 6. Need for early screening and diagnosis -- 7. How sensing and AI can help -- 8. Devices: Surgical implants for cardiovascular monitoring and management -- 9. Analytics for screening and diagnosis -- 10. Putting it all together -- 11. Example of a real-world cardiovascular screening system -- References -- Further reading |
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Chapter 2: Proliferation of a new generation of sensors: Smartphones and wearables -- 1. Introduction -- 2. Unobtrusive digital sensing -- 3. Electric or electromagnetic sensing -- 3.1. Acoustic and mechanical sensing -- 3.2. Biochemical sensing -- 4. Sensing the heart: An engineers perspective -- 4.1. Mechanical system -- 4.2. Circulatory system -- 4.3. Electrical system -- 4.4. Control system -- 4.5. Systems coming together -- 5. Photoplethysmogram: pulse oximetry -- 6. Phonocardiograms: digital stethoscope -- 6.1. History of heart sounds -- 6.2. Heart sounds -- 6.3. Conventional stethoscope |
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6.4. Digital stethoscope -- 6.5. Future of the stethoscope -- 7. ECG: Electrocardiograph -- 7.1. Origination and pathways of electrical charges in the heart -- 7.2. 12 leads and Einthovens triangle -- 7.3. Basic building blocks of an ECG machine -- 8. Conclusion -- References -- Further reading -- Chapter 3: Sensor signal analytics -- 1. Introduction -- 2. Preprocessing -- 2.1. Signal conditioning -- 2.1.1. Hardware filtering -- 2.1.2. Amplification -- 2.1.3. Attenuation -- 2.2. Noise handling -- 2.2.1. Noise sources -- 2.2.2. Noise removal -- 2.2.3. Signal reconstruction |
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3. Decision making using AI -- 3.1. Supervised machine learning -- 3.2. Unsupervised machine learning -- 3.3. Splitting of training and test data -- 3.4. Feature engineering -- 3.4.1. Dimensionality reduction using principal component analysis -- 3.4.2. Independent component analysis -- 3.5. Popular machine learning algorithms -- 3.5.1. Logistic regression -- 3.5.2. Support vector machine -- 3.5.3. Decision tree -- 3.6. Deep learning in biomedical engineering -- 3.6.1. Neural network activation -- Binary step activation function -- Linear activation function -- Sigmoid activation function |
| Notes |
Description based upon print version of record |
|
Hyperbolic tangent activation function (tanh) |
| Form |
Electronic book
|
| Author |
Banerjee, Rohan
|
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Kimbahune, Sanjay
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Pal, Arpan
|
| ISBN |
9780128245002 |
|
012824500X |
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