Open AccessHeart-Rate-Based Machine-Learning Algorithms for Screening Orthostatic Hypotension
Author(s) -
Ho Jin Kim,
Hayom Kim,
JungJoon Sung,
Seol-Hee Baek,
Byung Jo Kim
Publication year - 2020
Publication title -
journal of clinical neurology/the journal of clinical neurology
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.208
H-Index - 45
eISSN - 2005-5013
pISSN - 1738-6586
DOI - 10.3988/jcn.2020.16.3.448
Subject(s) - orthostatic intolerance , orthostatic vital signs , valsalva maneuver , expiration , univariate , algorithm , medicine , univariate analysis , multivariate statistics , heart rate , multivariate analysis , blood pressure , cardiology , machine learning , mathematics , computer science , respiratory system
Many elderly patients are unable to actively stand up by themselves and have contraindications to performing the head-up tilt test (HUTT). We aimed to develop screening algorithms for diagnosing orthostatic hypotension (OH) before performing the HUTT.