Biomedical engineering systems and technologies : 14th International Joint Conference, BIOSTEC 2021, Virtual event, February 11-13, 2021, revised selected papers / / Claudine Gehin [and seven others] (editors)

• Record Nr.: UNISA996503562803316
• Pubbl/distr/stampa: Cham, Switzerland : , : Springer, , [2022]; ©2022
• ISBN: 3-031-20664-9
• Descrizione fisica: 1 online resource (277 pages)
• Collana: Communications in Computer and Information Science Series ; ; Volume 1710
• Disciplina: 572.80285
• Soggetti: Bioinformatics; Biomedical engineering
• Lingua di pubblicazione: Inglese
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Intro -- Preface -- Organization -- Contents -- Systematic Design Procedure of CMOS Microelectrode-Arrays Based on Analog Signal Processing Noise Figure -- 1 Introduction -- 2 CMOS MEAs -- 3 Noise Figure and Noise Contributions in CMOS MEAs -- 3.1 Noise Power at the Electrolyte-Electrode Interface -- 3.2 TDM Noise -- 4 Noise Figure Based Design Procedure of CMOS MEAs -- 5 Conclusions -- References -- LigityScore: A CNN-Based Method for Binding Affinity Predictions -- 1 Introduction -- 2 LigityScore Overview -- 3 Dataset -- 4 LigityScore Implementation -- 4.1 Feature Generation -- 4.2 Feature Representation of Molecular Complex -- 4.3 CNN Architecture -- 5 Results and Evaluation -- 6 Conclusion and Discussion -- References -- Chaotic Changes in Fingertip Pulse Waves and Psychological Effects of Reminiscence Therapy Intervention -- 1 Introduction -- 1.1 Reminiscence Therapy -- 1.2 The Chaos of Fingertip Pulse Waves -- 1.3 Purpose -- 2 Methods -- 2.1 Materials -- 2.2 Equipment -- 2.3 Procedures -- 2.4 Ethical Considerations -- 3 Results -- 3.1 Mean LLE Changes in the Two Groups -- 3.2 Changes in the Psychological Indices of the Two Groups -- 3.3 Discriminant Analysis -- 3.4 LLE Changes Depending on the Easiness of Recalling Childhood Memories -- 3.5 Changes in the Attractor -- 4 Discussion -- 4.1 Childhood Memories ; and the Effects of Memory Retrieval -- 4.2 Future Perspectives -- References -- Determination of Charge Transfer Resistance from Randles Circuit Spectra Using Elliptical Fitting -- 1 Introduction -- 2 Materials and Methods -- 2.1 Simulation of Electrochemical Impedance Spectroscopy Data -- 2.2 Evaluation with Real Data of a Cortisol-Sensitive IMFET -- 2.3 Complex Nonlinear Least-Squares Regression -- 2.4 Elliptical Fitting -- 3 Results -- 3.1 Simulated Data -- 3.2 Measured Real Data -- 4 Discussion and Outlook -- References.; Towards Segmentation and Labelling of Motion Data in Manufacturing Scenarios -- 1 Introduction -- 1.1 Work Related Disorders and Risk Evaluation -- 1.2 Motivation -- 1.3 Towards Occupational Data Segmentation -- 2 Related Work -- 3 Dataset Description -- 3.1 Population -- 3.2 Instruments and Setup -- 4 Methods -- 4.1 SSM Construction -- 4.2 Similarity Function -- 4.3 Novelty Function -- 4.4 Sub-sequences Searched-by-example -- 4.5 Illustrative Example -- 5 Results and Discussion -- 5.1 Active Working Periods Segmentation -- 5.2 Working Cycles Segmentation -- 5.3 Towards Multi Time-Scale Segmentation -- 5.4 Labeling with Query-by-example -- 6 Conclusions -- References -- Evaluating the Performance of Diadochokinetic Tests in Characterizing Parkinson's Disease Hypokinetic Dysarthria -- 1 Introduction -- 2 Materials and Methods -- 3 Results -- 4 Discussion -- 5 Conclusions -- References -- Technology-Based Education and Training System for Nursing Professionals -- 1 Introduction -- 1.1 Demographic Background -- 1.2 Sensor System Conceptualization -- 1.3 Related Work -- 2 Methods -- 2.1 The Sensor System -- 2.2 Experimental Design -- 3 Results -- 3.1 Duration of Feedback Rounds -- 3.2 Keywords in Feedback Rounds -- 3.3 Amount of Criticized Aspects -- 3.4 Comparison of Information Content -- 3.5 Feedback by Additional Sensors Systems -- 4 Discussion -- References -- Evaluation of Algorithms to Measure a Psychophysical Threshold Using Digital Applications*-6pt -- 1 Introduction -- 2 Algorithms -- 2.1 STRICTN -- 2.2 BESTN -- 2.3 PEST -- 2.4 PESTN -- 3 Simulation Protocol -- 4 Analysis of the Results -- 5 Discussion -- 6 Related Work -- 7 Conclusion -- References -- Improving Teledermatology Referral with Edge-AI: Mobile App to Foster Skin Lesion Imaging Standardization -- 1 Introduction -- 2 Related Work -- 3 Macroscopic Image Acquisition Pipeline.; 3.1 Datasets -- 3.2 Preview and Acquired Image Focus Assessment -- 3.3 Lesion Segmentation -- 4 Mobile Application -- 5 Results and Discussion -- 5.1 Macroscopic Image Acquisition Pipeline Results -- 5.2 Trial Results -- 6 Conclusion and Future Work -- References -- Towards Interpretable Machine Learning Models to Aid the Academic Performance of Children and Adolescents with Attention-Deficit/Hyperactivity Disorder -- 1 Introduction -- 2 Background -- 2.1 Attention-Deficit/Hyperactivity Disorder -- 2.2 Features Selection with Genetic Algorithm -- 2.3 Interpretability -- 3 Related Works -- 4 Materials and Methods -- 4.1 Description of the Database -- 4.2 Pre-processing -- 4.3 Dimensionality Reduction with Genetic Algorithm, Random Forest, and Specialist -- 4.4 Description of Methods -- 4.5 Model Quality Assessment Metrics -- 5 Results and Discussions -- 5.1 VTJ48 Rules and Interpretability Using SHAP -- 6 Final Considerations -- References -- Requirements for Implementing Digital Health Terminology Standards in Uganda's Electronic Medical Records-Based Health Information Systems -- 1 Introduction -- 2 Methodology -- 2.1 Study Design -- 2.2 Study Respondents -- 2.3 Data Collection and Analysis -- 2.4 Ethical Clearance -- 3 Findings -- 3.1 Functional Requirements for Implementing Digital Health Terminology Services -- 3.2 Non-functional Requirements for Implementing Digital Health ; Terminology Services -- 4 Discussion -- 4.1 Mapping Healthcare Business Processes -- 4.2 Developing Terminology Services -- 4.3 Governance Structures -- 4.4 Capacity Building -- 5 Conclusion -- References -- Multi-class Detection of Arrhythmia Conditions Through the Combination of Compressed Sensing and Machine Learning -- 1 Introduction -- 2 Background and Related Work -- 2.1 The Arrhythmia Conditions -- 2.2 Automatic Detection of Arrhythmia Conditions.; 2.3 Detection in the Compressed Domain -- 2.4 The Compressed Sensing Algorithm -- 3 Automatically Detecting Arrhythmia Conditions -- 3.1 ECG Digital Processing -- 3.2 Heartbeat Features -- 3.3 Beat Classification -- 4 The Study -- 4.1 Study Design -- 4.2 Study Results -- 5 Conclusion and Future Work -- References -- DL-Assisted ROP Screening Technique -- 1 Introduction -- 2 Literature Review and Related Work -- 3 Methodology -- 3.1 Neonatal Retinal Scanning -- 3.2 Data Preparation -- 3.3 Noise Reduction and Image Pre-processing -- 3.4 OD Detection -- 3.5 Vessels Extraction -- 3.6 ROP Classification -- 4 Experimental Setup and Results -- 4.1 Evaluation Metrics -- 4.2 Pre-processing of Fundus Image -- 4.3 OD Segmentation -- 4.4 Vessels Segmentation -- 4.5 ROP Zoning -- 5 Conclusions -- References -- Author Index.