Signal Processing in Medicine and Biology: Innovations in Big Data Processing

✍ Scribed by Iyad Obeid, Joseph Picone, Ivan Selesnick

• Publisher: Springer
• Year: 2023
• Tongue: English
• Leaves: 152
• Category: Library

✦ Synopsis

​Signal Processing in Medicine and Biology: Innovations in Big Data Processing provides an interdisciplinary look at state-of-the-art innovations in biomedical signal processing, especially as it applies to large data sets and machine learning. Chapters are presented with detailed mathematics and complete implementation specifics so that readers can completely master these techniques. The book presents tutorials and examples of successful applications and will appeal to a wide range of professionals, researchers, and students interested in applications of signal processing, medicine, and biology at the intersection between healthcare, engineering, and computer science.

✦ Table of Contents

Preface
Contents
Hyper-Enhanced Feature Learning System for Emotion Recognition
1 Introduction
1.1 Emotion Work and Its Relation to Affective States
1.2 Qualitative Approach to Emotion Recognition
2 Related Background
2.1 Literature Review and Applications of Machine/Deep Learning to Emotion Recognition
3 Databases and Emotion State Modeling
3.1 Valence-Arousal Emotional State Modeling
4 Hyper-Enhanced Learning System Methodology
5 Experimentation
5.1 Data Preprocessing and Feature Learning
6 Results and Discussion
6.1 Multimodal Classification
6.2 Results of the Hybrid Neuro-single and Neuro-multimodal Network Classification
7 Conclusions
References
Monitoring of Auditory Discrimination Therapy for Tinnitus Treatment Based on Event-Related (De-) Synchronization Maps
1 Introduction
1.1 What Is Tinnitus?
1.2 Sort of Tinnitus
1.3 Tinnitus Affectation
1.4 How Can Be Over-Synchronization of Neurons Due to Tinnitus Detected?
1.5 Event-Related (De-) Synchronization (ERD/ERS)
1.6 How Can Be Tinnitus Treated?
1.7 Auditory Discrimination Therapy (ADT)
1.8 How Can Be Auditory Discrimination Therapy for Tinnitus Treatment Monitored?
1.9 Methods to Evaluate Auditory Discrimination Therapy
2 Methodology
2.1 EEG Database
2.2 EEG Signal Pre-processing
2.3 ERD/ERS Maps
2.4 Statistical Evaluation
3 Results
3.1 ERD/ERS Maps Grouped by the THI Outcome
3.2 Individual Analysis of the ERD/ERS Maps in Tinnitus Subjects
3.3 Quantification of ERD/ERS Responses
3.4 Cross-Sectional Analysis (Tinnitus Versus Control Group)
4 Discussion
4.1 ERD/ERS Maps Grouped by the THI Outcome
4.2 Individual Analysis of the ERD/ERS Maps
4.3 Quantification of ERD/ERS Responses
4.4 Cross-Sectional Analysis (Tinnitus Versus Control Group)
4.5 Comparison Analysis
5 Conclusions
References
Investigation of the Performance of fNIRS-based BCIs for Assistive Systems in the Presence of Acute Pain
1 Introduction
1.1 fNIRS
1.2 BCI
1.3 Input Data for BCI in Assistive Systems
1.4 Pain and BCI
1.5 Objective
2 Experiment
3 Data Preprocessing
4 Classification
4.1 SVM
4.2 Convolutional Neural Network
5 Results and Discussions
6 Conclusions
References
Spatial Distribution of Seismocardiographic Signal Clustering
1 Introduction
2 Methods
2.1 Experimental Data
2.2 Preprocessing
2.2.1 Filtering
2.2.2 Lung Volume Signal
2.2.3 Segmentation
2.3 SCG Clustering
2.3.1 Distance Measure
Dynamic Time Warping (DTW)
Euclidian and Cross-correlation-based Distance (Ecorr)
2.3.2 Initial Conditions
2.3.3 K-medoid Clustering Algorithm
2.4 Decision Boundary Between Clusters in the Standardized Flow Rate-Lung Volume Feature Space
2.4.1 Consistency of Clustering Spatial Distribution
2.5 Heart Rates in the Clusters
2.6 Intra-cluster Variability Reduction After Clustering
3 Results and Discussion
3.1 Clustering Accuracy
3.2 Decision Boundary Angle
3.2.1 Intra-subject and Inter-subject Angle Variability
3.3 Clusters Locations in Relation to the Respiratory Phase
3.4 Heart Rates in the Clusters
3.5 Intra-cluster Variability Reduction After Clustering
3.6 Computational Cost of the Different Distance Measures
4 Conclusions
Appendix A Heart Rate Distribution in the FL-LV Feature Space
References
Non-invasive ICP Monitoring by Auditory System Measurements
1 Introduction
2 Auditory System-Based Measurements
3 Evoked Tympanic Membrane Displacement
4 Spontaneous Tympanic Membrane Pulsation (TMp)
5 Tympanometry
6 Otoacoustic Emissions
7 Discussion
8 Conclusion
References
Index