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  4. A Review of Methods and Applications for a Heart Rate Variability Analysis
 
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A Review of Methods and Applications for a Heart Rate Variability Analysis

Type
Journal article
Language
English
Date issued
2023
Author
Nayak, Suraj Kumar
Pradhan, Bikash
Mohanty, Biswaranjan
Sivaraman, Jayaraman
Ray, Sirsendu Sekhar
Wawrzyniak, Jolanta 
Jarzębski, Maciej 
Pal, Kunal
Faculty
Wydział Nauk o Żywności i Żywieniu
Journal
Algorithms
ISSN
1999-4893
DOI
10.3390/a16090433
Web address
http://www.mdpi.com/1999-4893/16/9/433
Volume
16
Number
9
Pages from-to
art. 433
Abstract (EN)
Heart rate variability (HRV) has emerged as an essential non-invasive tool for understanding cardiac autonomic function over the last few decades. This can be attributed to the direct connection between the heart’s rhythm and the activity of the sympathetic and parasympathetic nervous systems. The cost-effectiveness and ease with which one may obtain HRV data also make it an exciting and potential clinical tool for evaluating and identifying various health impairments. This article comprehensively describes a range of signal decomposition techniques and time-series modeling methods recently used in HRV analyses apart from the conventional HRV generation and feature extraction methods. Various weight-based feature selection approaches and dimensionality reduction techniques are summarized to assess the relevance of each HRV feature vector. The popular machine learning-based HRV feature classification techniques are also described. Some notable clinical applications of HRV analyses, like the detection of diabetes, sleep apnea, myocardial infarction, cardiac arrhythmia, hypertension, renal failure, psychiatric disorders, ANS Activity of Patients Undergoing Weaning from Mechanical Ventilation, and monitoring of fetal distress and neonatal critical care, are discussed. The latest research on the effect of external stimuli (like consuming alcohol) on autonomic nervous system (ANS) activity using HRV analyses is also summarized. The HRV analysis approaches summarized in our article can help future researchers to dive deep into their potential diagnostic applications.
Keywords (EN)
  • cannabis

  • heart rate variability

  • signal analysis

  • feature selection

  • artificial intelligence

License
cc-bycc-by CC-BY - Attribution
Open access date
September 9, 2023
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