This book provides an insightful review and methodological contribution about future healthcare system. It also provides a space for creating and designing techniques for effective sensing, processing, and analysis of patient health situations based on bio-signal processing. Additionally, it discusses novel methods and algorithms which are needed to overcome limitations in current rhythmic bio-signals models. It also discusses solutions and systems needed to efficiently evaluate and process real-time data. The book is useful for wide range of users, including students, research scientists, teachers, and practitioners working in the field of heath informatics, neuroscience, biomedical engineering, and medical image processing and diagnosis.
Author(s): M. Shamim Kaiser, Mufti Mahmud, Shamim Al Mamun
Series: Studies in Rhythm Engineering
Publisher: Springer
Year: 2022
Language: English
Pages: 173
City: Singapore
Preface
Contents
Editors and Contributors
1 Is Biological Rhythm Associated with the Mortality of COVID-19?
1 Introduction
2 Methods
2.1 Biological Rhythm
2.2 Data Analysis
3 Results
4 Discussion
References
2 Deep Learning in Biomedical Devices: Perspectives, Applications, and Challenges
1 Introduction
2 Internet of Healthcare Things (IoHT)
3 IoHT and Biomedical Devices
4 Overview of Deep Learning
4.1 Basic Framework
4.2 Convolutional Neural Network (CNN)
4.3 Recurrent Neural Network (RNN)
4.4 Autoencoders (AE)
4.5 Deep Boltzmann Machine (DBM)
4.6 Deep Belief Network (DBN)
5 Deep Learning in Biomedical Devices
6 Open Issues and Future Perspectives
7 Conclusion
References
3 Effect of 3D-Multiple Object Tracking Training on Manual Dexterity in Elderly Adults with Dementia and Mild Cognitive Impairment
1 Introduction
2 Materials and Methods
2.1 Participants
3 Measures
3.1 Montreal Cognitive Assessment (MoCA Version 7.1)
3.2 Grooved Pegboard Test (GPT)
3.3 Minnesota Manual Dexterity Test (MMDT)
4 Training Procedure
4.1 3D-Multiple Object Tracking (3D-MOT)
5 Statistical Analysis
6 Results
7 Discussion
References
4 Rhythmic Pattern of EEG for Identifying Schizophrenia
1 Introduction
2 Methods
2.1 Measures of Directed Connectivity
3 Experimental Results
3.1 Dataset
3.2 Comparison of Different Models for Biomedical Application
4 Discussions
5 Conclusion
6 Future Work
References
5 Prior Prediction and Management of Autism in Child Through Behavioral Analysis Using Machine Learning Approach
1 Introduction
2 Prior Prognostic of Autism
2.1 Behavioral Analysis
2.2 Screening and Diagnosis of Autism Spectrum Disorder
3 Research Methodology
3.1 Data Collection and Description
3.2 Machine Learning Classifiers and Evaluation Metrics
3.3 Implementation
4 Experimental Result and Discussion
5 Conclusions
References
6 DNN and LiDAR Sensor Based Crowd Avoidance Method for Nurse-Following Robot in Healthcare
1 Introduction
2 Related Work
3 The Crowd Avoidance Algorithm
3.1 Person Tracking
3.2 Locate the Target Nurse and Pedestrian Person in the Space
3.3 Line Following Method
3.4 Circle Following Method
4 Experiments of the Crowd Avoidance
4.1 Hardware
4.2 Experimental Conditions
4.3 Experimental Results
5 Conclusions and Future Work
References
7 Investigation on Heart Attack Prediction Based on the Different Machine Learning Approaches
1 Introduction
2 Machine Learning Algorithms
2.1 Support Vector Machine
2.2 Logistic Regression
2.3 K-Nearest Neighbor Algorithm
2.4 Random Forest Algorithm
2.5 Naive Bayes Classifier
2.6 Decision Tree Classifier
3 Dataset
4 Methodology
5 Result and Discussion
6 Conclusion
References
8 Wearable Devices for Monitoring Vital Rhythm and Earlier Disease Diagnosis of Treatment
1 Introduction
2 Methods and Materials
2.1 Review Methodology
2.2 Wearable Devices
2.3 Vital Rhythm
2.4 Disease Diagnosis from Vital Rhythm
3 Discussions
4 Limitations and Challenges
5 Conclusion
References
9 Post-quantum Signature Scheme to Secure Medical Data
1 Introduction
2 Background and Motivation
3 Literature Review
4 Preliminaries
4.1 Keccak
4.2 Skein
4.3 Merkle Tree
5 Proposed Signature Scheme
5.1 Proposed MMT Signature Scheme for Multiple Transactions
5.2 Proposed MMT Signature Scheme for Single Transaction
5.3 Proposed Secure Blockchain for Medical Data Using MMT Signature Scheme
6 Security and Performance Analysis
6.1 Performance Analysis
6.2 Security Analysis
6.3 Trade-Off Between Performance and Security
7 Conclusion
8 Future Work
References
10 Medical Image Analysis Using Machine Learning and Deep Learning: A Comprehensive Review
1 Introduction
2 Medical Imaging Types
3 Overview of Machine Learning and Deep Learning
4 Classifier
5 Performance Metrics
6 ML and DL Approaches in Tuberculosis Detection
7 ML and DL Approaches in Lung Cancer Detection
8 ML and DL Approaches in COVID-19 Detection
9 ML and DL Approaches in Pneumonia Detection
10 Discussion
11 Conclusion
References
