Cardiorespiratory Temporal Causal Links and the Differences by Sport or Lack Thereof

Frontiers in Physiology
Marcel Młyńczak, Hubert Krysztofiak

Abstract

Fitness level, fatigue and adaptation are important factors for determining the optimal training schedule and predicting future performance. We think that adding analysis of the mutual relationships between cardiac and respiratory activity enables better athlete profiling and feedback for improving training. Therefore, the main objectives were (1) to apply several methods for temporal causality analysis to cardiorespiratory data; (2) to establish causal links between the signals; and (3) to determine how parameterized connections differed across various subgroups. One hundred elite athletes (31 female) and a control group of 20 healthy students (6 female) took part in the study. All were asked to follow a protocol comprising two 5-min sessions of free breathing - once supine, once standing. The data were collected using Pneumonitor 2. Respiratory-related curves were obtained through impedance pneumography, along with a single-lead ECG. Several signals (e.g., tidal volume, instantaneous respiratory rate, and instantaneous heart rate) were derived and stored as: (1) raw data down-sampled to 25Hz; (2) further down-sampled to 2.5Hz; and (3) beat-by-beat sequences. Granger causality frameworks (pairwise-conditional, spectral or exte...Continue Reading

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Citations

Sep 12, 2019·Frontiers in Psychology·Sylvain LabordeFabrice Dosseville
Jul 28, 2020·Frontiers in Physiology·Dmitriy Yu UryumtsevSergey G Krivoschekov

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Methods Mentioned

BETA
RSA

Software Mentioned

TransferEntropy R
R
Pneumonitor
MATLAB
tseries
TiMINo

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