Biomedical Signal Processing for Healthcare Applications

图书简介

This book examines the use of biomedical signal processing—EEG, EMG, and ECG—in analyzing and diagnosing various medical conditions, particularly diseases related to the heart and brain. In combination with machine learning tools and other optimization methods, the analysis of biomedical signals greatly benefits the healthcare sector by improving patient outcomes through early, reliable detection. The discussion of these modalities promotes better understanding, analysis, and application of biomedical signal processing for specific diseases.The major highlights of Biomedical Signal Processing for Healthcare Applications include biomedical signals, acquisition of signals, pre-processing and analysis, post-processing and classification of the signals, and application of analysis and classification for the diagnosis of brain- and heart-related diseases. Emphasis is given to brain and heart signals because incomplete interpretations are made by physicians of these aspects in several situations, and these partial interpretations lead to major complications.FEATURESExamines modeling and acquisition of biomedical signals of different disordersDiscusses CAD-based analysis of diagnosis useful for healthcareIncludes all important modalities of biomedical signals, such as EEG, EMG, MEG, ECG, and PCGIncludes case studies and research directions, including novel approaches used in advanced healthcare systemsThis book can be used by a wide range of users, including students, research scholars, faculty, and practitioners in the field of biomedical engineering and medical image analysis and diagnosis.

1. Automatic Sleep EEG Classification with Ensemble Learning Using Graph Modularity Kamakhya Narain Singh, Sudhansu Shekhar Patra, Swati Samantaray, Sudarson Jena, Jibendu Kumar Mantri, and Chinmaya Misra 2. Recognition of Distress Phase Situation in Human Emotion EEG Physiological Signals Abdultaofeek Abayomi, Oludayo O. Olugbara, and Delene Heukelman 3. Analysis and Classification of Heart Abnormalities Ayesha Heena 4. Diagnosis of Parkinson’s Disease Using Deep Learning Approaches: A Review Priyanka Khanna, Mridu Sahu, and Bikesh Kumar Singh 5. Classifying Phonological Categories and Imagined Words from EEG Signal Ashwin Kamble, Pradnya H Ghare, and Vinay Kumar 6. Blood Pressure Monitoring Using Photoplethysmogram and Electrocardiogram Signals Jamal Esmaelpoor and Zahra Momayez Sanat 7. Investigation of the Efficacy of Acupuncture Using Electromyographic Signals Kim Ho Yeap, Wey Long Ng, Humaira Nisar, and Veerendra Dakulagi 8. Appliance Control System for Physically Challenged and Elderly Persons through Hand Gesture-Based Sign Language G. Boopathi Raja 9. Computer-Aided Drug Designing - Modality of Diagnostic System Shalini Ramesh, Sugumari Vallinayagam, Karthikeyan Rajendran, Sasireka Rajendran, Vinoth Rathinam, and Sneka Ramesh 10. Diagnosing Chest-Related Abnormalities Using Medical Image Processing through Convolutional Neural Network Vignessh B., Reena Raj, and Balakrishnakumar 11. Recent Trends in Healthcare System for Diagnosis of Three Diseases Using Health Informatics Shawni Dutta and Samir Kumar Bandyopadhyay 12. Nursing Care System Based on Internet of Medical Things (IoMT) through Integrating Non-Invasive Blood Sugar (BS) and Blood Pressure (BP) Combined Monitoring Patrali Pradhan, Subham Ghosh, and Biswarup Neogi 13. Eye Disease Detection from Retinal Fundus Image Using CNN Padma Selvaraj and Pugazendi Rajagopal

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Biomedical Signal Processing for Healthcare Applications（Emerging Trends in Biomedical Technologies and Health informatics） 用于医疗保健应用的生物医学信号处理 生物医学工程学

Biomedical Signal Processing for Healthcare Applications（Emerging Trends in Biomedical Technologies and Health informatics）

用于医疗保健应用的生物医学信号处理
生物医学工程学