CLASSIFICATION OF SEVERITY OF COVID-19 PATIENTS BASED ON THE HEART RATE VARIABILITY
Document
Metadata
Title
CLASSIFICATION OF SEVERITY OF COVID-19 PATIENTS BASED ON THE HEART RATE VARIABILITY
作者
PORDEUS, DANIEL | RIBEIRO, PEDRO | ZACARIAS, LAÍLA | PAULO MADEIRO, JOÃO | MARQUES, JOÃO ALEXANDRE LOBO | MIGUEL RODRIGUES, PEDRO | LEITE, CAMILA | ALVES NETO, MANOEL | AIRES PEIXOTO JR, ARNALDO | DE OLIVEIRA, ADRIEL
PUBLISH YEAR
2023
FACULTY / RESEARCH UNIT
摘要
THE CONTINUOUS DEVELOPMENT OF ROBUST MACHINE LEARNING ALGORITHMS IN RECENT YEARS HAS HELPED TO IMPROVE THE SOLUTIONS OF MANY STUDIES IN MANY FIELDS OF MEDICINE, RAPID DIAGNOSIS AND DETECTION OF HIGH-RISK PATIENTS WITH POOR PROGNOSIS AS THE CORONAVIRUS DISEASE 2019 (COVID-19) SPREADS GLOBALLY, AND ALSO EARLY PREVENTION OF PATIENTS AND OPTIMIZATION OF MEDICAL RESOURCES. HERE, WE PROPOSE A FULLY AUTOMATED MACHINE LEARNING SYSTEM TO CLASSIFY THE SEVERITY OF COVID-19 FROM ELECTROCARDIOGRAM (ECG) SIGNALS. WE RETROSPECTIVELY COLLECTED 100 5-MINUTE ECGS FROM 50 PATIENTS IN TWO DIFFERENT POSITIONS, UPRIGHT AND SUPINE. WE PROCESSED THE SURFACE ECG TO OBTAIN QRS COMPLEXES AND HRV INDICES FOR RR SERIES, INCLUDING A TOTAL OF 43 FEATURES. WE COMPARED 19 MACHINE LEARNING CLASSIFICATION ALGORITHMS THAT YIELDED DIFFERENT APPROACHES EXPLAINED IN A METHODOLOGY SESSION.
SUBJECTS
COVID-19,ELECTROCARDIOGRAM (ECG) SIGNAL,HEART RATE VARIABILITY (HRV) INDICES,SEVERITY,SIGNAL PROCESSING
DOCUMENT TYPE
SDG Category
Part of
COMPUTERIZED SYSTEMS FOR DIAGNOSIS AND TREATMENT OF COVID-19
DOI
10.1007/978-3-031-30788-1_10
ISBN
978-3-031-30788-1