Automated analysis of breathing waveforms using BreathMetrics: a respiratory signal processing toolbox.

Abstract:

:Nasal inhalation is the basis of olfactory perception and drives neural activity in olfactory and limbic brain regions. Therefore, our ability to investigate the neural underpinnings of olfaction and respiration can only be as good as our ability to characterize features of respiratory behavior. However, recordings of natural breathing are inherently nonstationary, nonsinusoidal, and idiosyncratic making feature extraction difficult to automate. The absence of a freely available computational tool for characterizing respiratory behavior is a hindrance to many facets of olfactory and respiratory neuroscience. To solve this problem, we developed BreathMetrics, an open-source tool that automatically extracts the full set of features embedded in human nasal airflow recordings. Here, we rigorously validate BreathMetrics' feature estimation accuracy on multiple nasal airflow datasets, intracranial electrophysiological recordings of human olfactory cortex, and computational simulations of breathing signals. We hope this tool will allow researchers to ask new questions about how respiration relates to body, brain, and behavior.

journal_name

Chem Senses

journal_title

Chemical senses

authors

Noto T,Zhou G,Schuele S,Templer J,Zelano C

doi

10.1093/chemse/bjy045

subject

Has Abstract

pub_date

2018-09-22 00:00:00

pages

583-597

issue

8

eissn

0379-864X

issn

1464-3553

pii

5050471

journal_volume

43

pub_type

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