A two-step pre-processing tool to remove Gaussian and ectopic noise for heart rate variability analysis

Journal article

Heart rate variability (HRV) is a naturally occurring cardiovascular phenomenon referring to the changing timing between consecutive heartbeats. The connection between HRV and overall cardiovascular health and autonomic nervous system function has been well established through prior research and well documented in existing literature. The existing studies, however, included shorter HRV subject recording session, using traditional HRV monitoring methods that do not typically combine electrocardiogram (ECG), seismocardiogram (SCG) and galvanic skin response (GSR) respiration monitoring. The inclusion of longer HRV subject recording may allow for further insight on the possible effects of given observable biological phenomenon on HRV. The current technology for the collection and storage of analog voltage HRV signals exists as separate ECG, SCG and GSR data collection units; all of which are required to make meaningful conclusions about HRV. These individual units work independently from one another, are not portable, must be connected to a power grid at all times, require attachments to the subject at specific body surface locations to ensure data accuracy and require technical expertise to operate efficiently and interpret the obtained data. The study proposes a long-term simultaneous recording device capable of tracking these signals which will allow more detailed inter-signal analysis that can provide more insight into cardiac activity in the presence of changing observable biological phenomena over time

Authors: Saleem, S; Khandoker, AH; Alkhodari, M; Hadjileontiadis, LJ; Jelinek, HF

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Nature Research
• Journal: Scientific Reports
• Volume: 12
• Issue: 1
• Pages: 18396-18396
• Article number: 18396
• Publication date: 2022-11-01
• DOI: 10.1038/s41598-022-21776-2
• EISSN: 2045-2322
• ISSN: 2045-2322
• Language: English
• Keywords: Signal processing; Preprocessor; Medicine; Heart rate variability; Computer science; Hilbert–Huang transform; Pattern recognition (psychology); Algorithm; Speech recognition; Computer vision; Statistics; Gaussian noise; Adaptive filter; Artificial intelligence; Noise (video); Filter (signal processing); Digital signal processing; Heart rate; Mathematics