Proceeding of the 3rd International Conference on Electronics, Biomedical Engineering, and Health Informatics: ICEBEHI 2022, 5–6 October, Surabaya, Indonesia

Description

This book presents high-quality peer-reviewed papers from the International Conference on Electronics, Biomedical Engineering, and Health Informatics (ICEBEHI) 2022 held at Surabaya, Indonesia, virtually. The contents are broadly divided into three parts: (a) Electronics, (b) Biomedical Engineering, and (c) Health Informatics. The major focus is on emerging technologies and their applications in the domain of biomedical engineering. It includes papers based on original theoretical, practical, and experimental simulations, development, applications, measurements, and testing. Featuring the latest advances in the field of biomedical engineering applications, this book serves as a definitive reference resource for researchers, professors, and practitioners interested in exploring advanced techniques in the fields of electronics, biomedical engineering, and health informatics. The applications and solutions discussed here provide excellent reference material for future product development. Organization Preface Contents About the Editors A Preliminary Study of Vehicle License Plate Detection and Identification 1 Introduction 2 Related Works 3 Proposed Method 4 Results 5 Discussion 6 Conclusion References Feature Selection Using Extra Trees Classifier for Research Productivity Framework in Indonesia 1 Introduction 2 Related Works 3 Materials and Methods 4 Result and Discussion 5 Conclusion References A Survey on Big Data Analytics for Load Prediction in Smart Grids 1 Introduction 2 Foundation 2.1 Big Data 2.2 Smart Grid 2.3 Big Data and Smart Grid 2.4 Sources of Data for Smart Grids 3 Power Analytics 3.1 Data Gathering, Sharing, and Filtering 3.2 Data Analytics 4 Forecasting Methods 4.1 Forecasting Loads Utilizing Time Series Models 4.2 Predicting Loads Using Multivariate Models 5 Issues and Alternative Solutions 6 Discussion 7 Comparative Load Prediction Techniques Currently in Use 8 Conclusion References Analysis of Three-Phase Induction Motor Speed Performance with Load Torque Changes Using Inverter Space Vector Pulse Width Modulation (SVPWM) Control 1 Introduction 2 Space Vector Concept 2.1 Eight Vector Switching Inverter Combinations in Space Vector Pulse Modulation (SVPWM) 2.2 Time Calculation and Gate Trigger Pattern 3 Method 4 Results and Discussion 5 Conclusion References Assessing the Effect on Cognitive Workload Index, EEG Band Ratios, and Band Frequencies Using Band Power and Implementing Machine Learning Classification 1 Introduction 2 Materials and Methods 2.1 Recording and Selection of the EEG Signals 2.2 Attribute of Subject Participation in the Protocol 2.3 Wavelet Decomposition 3 Results and Analysis 3.1 Individual Band Frequencies 3.2 Cognitive Load Indices (EEG Band Ratios) 3.3 Prefrontal Electrode Analysis 3.4 Binary Classification 4 Discussion 5 Conclusion References Fetal ECG Signal Processing Using One-Dimensional Convolutional Neural Network (1D CNN) for Fetal Arrhythmias Detection 1 Introduction 2 Material and Method 2.1 Dataset 2.2 Convolutional Neural Network (CNN) 2.3 Proposed CNN 2.4 System Performance 3 Result and Discussion 3.1 Result 3.2 Discussion 4 Conclusion References Diabetic Retinopathy Classification Based on Fundus Image Using Convolutional Neural Network (CNN) with MobilenetV2 1 Introduction 2 Material and System Design 2.1 Dataset 2.2 Convolutional Neural Network 2.3 Proposed CNN 2.4 MobileNetV2 3 Results 4 Discussion 5 Conclusion References Image Improvement and Dose Reduction on Computed Tomography Mastoid Using Interactive Reconstruction 1 Introduction 2 Data and Method 3 Results 3.1 Image Information Quality Profile (Anatomy Assessment, Noise, and Pixel Value) 3.2 Dosage Profile on CT Mastoid 4 Discussion 5 Conclusion References Classification of Pneumonia Based on X-Ray Images with ResNet-50 Architecture 1 Introduction 2 Basic Theory 2.1 The Lungs 2.2 Pneumonia 2.3 Digital Image Processing 2.4 Convolutional Neural Network 2.5 Residual Network (ResNet) 2.6 Confusion Matrix 3 System Design 4 Result and Discussion 5 Conclusion References A Model Convolutional Neural Network for Early Detection of Chili Plant Diseases in Small Datasets 1 Introduction 2 Materials and Method 2.1 Data Acquisition 2.2 Pre-Processing Data 2.3 Convolutional Neural Network 2.4 DenseNet201 2.5 System Evaluation 3 Result and Discussion 3.1 Dataset Configuration 3.2 Training Result 3.3 Confusion Matrix Result 3.4 Testing Result 3.5 Analysis and Discussion 4 Conclusion References Early Risk Pregnancy Prediction Based on Machine Learning Built on Intelligent Application Using Primary Health Care Cohort Data 1 Introduction 2 Methodology 2.1 Data 2.2 Study Design 2.3 Feature Variables 2.4 Machine Learning Algorithm 3 Results 3.1 Data Pre-processing 3.2 Model Prediction 4 Discussion 5 Conclusion References Uretery Stone Detection with CT Scan Image Contrast Analysis 1 Introduction 2 Materials and Methods 3 Results and Discussion 4 Conclusion References Accuration of Classification of Covid with Convolutional Neural Network-Based Image Chest X-ray with Variations in Image Size and Batch Size 1 Introduction 2 Data and Method 2.1 Identification of Covid with Chest X-ray Image 2.2 Collecting Data 2.3 CNN Architecture 3 Results and Discussion 4 Conclusion References Automatic Water Monitoring and Draining System Manufacturing for Aquascape Based on Water Quality Using Fuzzy Logic Method 1 Introduction 2 Literature Review 2.1 Aquascape Industry 2.2 Temperature 2.3 Humidity 2.4 Turbidity 2.5 Power of Hydrogen 2.6 Blynk 2.7 Fuzzy Logic 3 System Designing 3.1 System Design 3.2 Hardware Design 3.3 System Work Flowchart 4 Results 4.1 Sensor Accuracy Test 4.2 System Drainage Test 4.3 Notification Testing System 5 Conclusion References Comparison of Principal Component Analysis and Recursive Feature Elimination with Cross-Validation Feature Selection Algorithms for Customer Churn Prediction 1 Introduction 2 Methods 2.1 Research Framework 2.2 Principal Component Analysis (PCA) 2.3 Recursive Feature Elimination with Cross-Validation (RFECV) 2.4 eXtreme Gradient Boosting (XGBoost) 2.5 Evaluation Metrics 3 Results and Discussion 3.1 Results 3.2 Discussion 4 Conclusion References Implementation and Evaluation of Prototype Photoplethysmography for Healthy Person-Based Internet of Things 1 Introduction 2 Method 3 Results 4 Discussion 5 Conclusion References Enhancing Temperature Control in a Miniature Green House for Corn Plantation System Using Model Predictive Controller 1 Introduction 1.1 Background 2 Materials and Methods 2.1 Hardware Configuration 2.2 Model Predictive Controller 2.3 Software System Design 3 Result 3.1 Hardware Device Implementation 3.2 Software Implementation 4 Analysis and Discussion 5 Conclusion References DenseNet201 Model for Robust Detection on Incorrect Use of Mask 1 Introduction 2 Materials and Methods 2.1 Data Acquisition 2.2 Preprocessing Data 2.3 Transfer Learning 2.4 System Evaluation 3 Result and Discussion 3.1 Hardware and Method Configuration 3.2 Training Result 3.3 Testing Result 4 Conclusion References Comparison of Nutritional Status Prediction Models of Children Under 5 Years of Age Using Supervised Machine Learning 1 Introduction 2 Methodology 2.1 Data Collection 2.2 Data Preprocessing 2.3 Nutritional Status Prediction Modeling 2.4 Evaluation 3 Results and Discussions 4 Conclusion References Stock Investment Modeling and Prediction Using Vector Autoregression (VAR) and Cross Industry Standard Process for Data Mining (CRISP-DM) 1 Introduction 2 Research Methods 2.1 Business Understanding 2.2 Data Understanding 2.3 Data Preparation 2.4 Modeling 2.5 Evaluation 3 Result and Discussion 4 Conclusion References Development Human Activity Recognition for the Elderly Using Inertial Sensor and Statistical Feature 1 Introduction 2 Method and Material 2.1 Datasets 2.2 Preprocessing 2.3 Extraction Features 2.4 Feature Selection 2.5 Classifier 3 Results and Analysis 3.1 Preprocessing 3.2 Machine Learning 4 Discussion 5 Conclusion References Heart Abnormality Classification with Power Spectrum Feature and Machine Learning 1 Introduction 2 Method and Material 2.1 Proposed Method 2.2 Dataset 2.3 Feature Extraction 2.4 Classifier 3 Result 4 Discussion 5 Conclusion References Classification of Epileptic EEG Signal Using MSLD Entropy 1 Introduction 2 Material and Method 2.1 EEG Signal Dataset 2.2 MSLD Entropy 2.3 Classification 3 Results 4 Discussion 5 Conclusion References Comparison Performance of Deep Learning Models for Brain Tumor Segmentation Based on 2D Convolutional Neural Network 1 Introduction 2 Materials and Method 2.1 Data 2.2 Deep Learning Models 2.3 Research Methods 3 Result 4 Discussion 5 Conclusion References Hand Gesture Recognition Using FMCW Radar and Deep Learning for Understanding Deaf Sign Language 1 Introduction 2 Materials and Method 2.1 Material 2.2 Experimental Procedures 2.3 Proposed CNN Design 2.4 Proposed CNN Design 3 Results 4 Discussion 5 Conclusion References The Performance of Various Concise Convolutional Neural Network Configurations in Classifying Tomato Diseases Based on Leaf Images 1 Introduction 2 Material and Methods 2.1 Related Works 2.2 Dataset 2.3 The Proposed Architecture and Its Configurations 2.4 Comparison Architectures 2.5 Training and Evaluation 3 Results and Discussion 3.1 Investigation of the Proposed Architectural Configuration 3.2 Performance Comparison of the Proposed Architecture and the Comparison Architectures 4 Conclusion and Future Work References An Advanced Data Augmentation Scheme on Limited EEG Signals for Human Emotion Recognition 1 Introduction 2 Materials and Method 2.1 Dataset 2.2 Signal to Image Transformation 2.3 Pix2pix 2.4 Cohen’s Kappa Coefficient 2.5 Research Design 3 Result 3.1 Performance on Different Number of Appended Training Data 3.2 The Best Data Augmentation Scheme 4 Discussion 4.1 Accuracy Improvement 4.2 Kappa Coefficient 4.3 Accuracy Benchmarking with Other Results 4.4 Limitation and Implication 5 Conclusion References Comparison of KNN and SVM Methods for the Accuracy of Individual Race Classification Prediction Based on SNP Genetic Data 1 Introduction 2 Research Methods 2.1 Research Data 2.2 Research Stages 3 Results and Discussion 3.1 Results Analysis 3.2 Discussion 4 Conclusion References FMCW Radar Signal Processing for Human Activity Recognition with Convolutional Neural Network 1 Introduction 2 Materials and Method 2.1 Material 2.2 Experimental Procedures 2.3 Flowchart 3 Result 3.1 CNN Architecture 3.2 Training Results 3.3 Testing Results 4 Discussion 5 Conclusion References Classification of Alphabets and Numbers Indonesian Sign System Using uRAD Radar Based on FMCW Radar and Deep Learning Techniques 1 Introduction 2 Materials and Method 2.1 Materials 2.2 Experimental Procedures 3 Result 4 Discussion 5 Conclusion References Heart Rate Variability of Photoplethysmography for Hypertension Detection Using Support Vector Machine 1 Introduction 2 Method 2.1 PPG Database 2.2 Heart Rate Variability 2.3 Support Vector Machines 3 Results 4 Discussion 5 Conclusion References Enhancing the Diagnosis of Skin Neglected Tropical Diseases by Artificial Neural Networks Using Evolutionary Algorithms: Implementation on Raspberry Pi 1 Introduction 2 Materials and Method 2.1 Theoretical Background (Math Modeling) 2.2 Hybrid Whale Shark Algorithm. 2.3 Dataset 2.4 Experimental Procedure 2.5 Data Processing 3 Results 3.1 Image Pre-processing and Processing 3.2 Data Analysis 3.3 Deployment Result 4 Discussion 5 Conclusion References Small Displacement Detection System of Landslide Using FMCW Radar with Phase-Detection and Change Point Detection Method 1 Introduction 2 Materials and Method 2.1 Material 2.2 Experimental Procedures 2.3 Pre-Processing 2.4 Flowchart 3 Result 4 Discussion 5 Conclusion References Machine Learning Performance Analysis for Classification of Medical Specialties 1 Introduction 2 Methods 2.1 Dataset 2.2 Multi-layer Perceptron 2.3 Logistic Regression 2.4 Random Forest 2.5 K-nearest Neighbor 2.6 Support Vector Machine 2.7 Confusion Matrix 3 Result and Discussion 3.1 Pre-processing 3.2 Text Representation 3.3 Classification 3.4 Evaluation 3.5 Discussion 4 Conclusion References Controlling the Temperature of PID System-Based Baby Incubator to Reduction Overshoot 1 Introduction 2 Research Method 2.1 Data Acquisition 2.2 Data Collection 2.3 Data Processing 2.4 Statistical Analysis 3 Results Discussion 3.1 Test Results of Temperature Control Based on PID Control System 3.2 Testing the PID System by Giving an Interruption 4 Discussion 5 Conclusion References Improving the Myoelectric Feature Linearity to Enhance the Elbow Motion Estimation Using Kalman Filter 1 Introduction 2 Materials and Methods 2.1 Participants 2.2 Equipment 3 Results and Discussion 4 Conclusion References State of the Art Methods of Machine Learning for Prosthetic Hand Development: A Review 1 Introduction 2 Materials and Method 2.1 Article Publication Trend 2.2 Keyword Network Visualization 3 Result 4 Discussion 5 Conclusion References Recognizing Face Using the Combination of Singular Value Decomposition and Hidden Markov Model Algorithms 1 Introduction 2 Research Method 2.1 Singular Value Decomposition 2.2 Hidden Markov Model 2.3 Data Set 2.4 Experimental Procedure 2.5 Data Processing 2.6 Training Process 2.7 Testing and Recognition Process 3 Results 3.1 Preprocessing Process 3.2 Results of the Recognition Process 3.3 Results Using the a Transition Probability Matrix 3.4 Results Using the A1 Transition Probability Matrix 3.5 Influence of Changing the SVD Coefficients 3.6 Influence of Changing the Quantization Level 4 Discussion 5 Conclusion References Analysis of Receive Signal Strength Indicator (RSSI) on Pulse Oximetry Data Delivery via Bluetooth Low Energy (BLE) 1 Introduction 2 Materials and Methods 2.1 Theoretical Background 2.2 Experimental Procedure 2.3 Data Processing 2.4 Data Analysis 3 Results 3.1 SpO2 and BPM Measurement 3.2 Results of RSSI Data Measurement on the Android Application 3.3 Results and Analysis of Lost Data Testing on Oximetry Data Retrieval and on the Android Application 3.4 Results and Analysis of Data Delay Testing on Oximetry Data Retrieval and on the Android Application 4 Discussion 5 Conclusion References Web-Based Incubator Analyzer Effectiveness and Efficiency Analysis Using ISO:IEC 25022 1 Introduction 2 General Information 2.1 Data Transfer Method 3 Material and Methods 3.1 Data Collection 3.2 Data Analysis 4 Result 4.1 The Web-Based Incu Analyzer 4.2 Compliance with Standards 4.3 Effectiveness and Efficiency 5 Discussion 6 Conclusion References Effectiveness Analysis of Infinite Impulse Response Digital Filter on Electrocardiogram Signal to Extract Respiration Rate Signal 1 Introduction 2 Material and Methods 2.1 Theoretical Background 2.2 Data Set 2.3 Experimental Procedure 2.4 Data Processing 2.5 Data Analysis 3 Results 3.1 Module Test Result 3.2 Research Results 3.3 Correlation Analysis 4 Discussion 5 Conclusion References Analysis of Finite Impulse Response (FIR) Filter to Reduce Motion Artifacts of Heart Rate Signal Based on Photoplethysmography 1 Introduction 2 Material and Methods 2.1 Theoretical Background 2.2 Dataset 2.3 Experimental Procedure 2.4 Data Processing 2.5 Data Analysis 3 Results 3.1 System Evaluation 3.2 Motion Artifact Test Results 3.3 Filter Test Result 4 Discussion 5 Conclusion References Analysis of Electrocardiogram and Photoplethysmogram Signals to Detect Car Driver Drowsiness Using the Threshold Method 1 Introduction 2 Materials and Methods 2.1 Theoretical Background 2.2 Dataset 2.3 Experimental Procedure 2.4 Data Processing 2.5 Data Analysis 3 Results 3.1 Device Evaluation 3.2 Results of Parameters Test 3.3 Results of Drowsiness Test 4 Discussion 5 Conclusion References Comparing Machine Learning and Deep Learning Approaches to Diagnose Epilepsy Disease 1 Introduction 2 Materials and Method 2.1 Dataset 2.2 De-noising EEG Signal 2.3 Short-Time Fourier Transform (STFT) 2.4 Spectrogram Images 2.5 Machine Learning 2.6 Deep Learning 3 Results 4 Discussion 5 Conclusion References