Kasprowisko 2017 Presentation - Abstract by Marcel Młyńczak, Hubert Krysztofiak, Marek Żyliński and Gerard Cybulski

1. Analysis of cardiorespiratory coupling
in athletes in rest using causal approach
Marcel Młyńczak, MSc, Hubert Krysztofiak, PhD,
Marek Żyliński, MSc, Gerard Cybulski, PhD
Zakopane, March 4th, 2017

2. Introduction
ECG-based analyses in sport medicine
• Well established in the community
• Relatively simple
• Usually measure single „modality”
• Do not consider the mutual cardiorespiratory activity
Left figure adapted from medicalexpo.com
2

3. Introduction
Traditional respiratory monitoring
• The most reliable methods
• Direct measurements of airflows
• The need for using a face mask or mouthpiece with nose clip
• Uncomfortable during exercises, natural functioning or sleep
Figures adapted from chat.stackexchange.com and legio24.pl
Mesh grid of
known pneumatic
resistance
3

4. Introduction
Impedance pneumography
Basic idea
Changes of transthoracic bioimpedance are
connected with changes of the amount of air in the lungs
Method of
measurements
The nature of the
IP signals
Carried out using tetrapolar method
Volume-related
Calibration
Simple linear model provides the best accuracy of volume
parameters estimation for specific electrode configuration
4

5. Objectives
• Conducting pilot studies using Pneumonitor 2 in athletes in rest.
• Preliminary analysis of cardiorespiratory coupling using
Granger causality test and by calculating best shift between:
➡ RR intervals (tachograms),
➡ Tidal Volume (TV) curves.
5

6. Methodology
Participants
Min Avg Max
Weight [kg] 49.1 78.6 151.0
Height [cm] 158.0 183.4 208.0
BMI 17.4 23.2 42.7
Age 16.0 24.6 40.0
6
Polish elite athletes (studied before Rio 2016): 32 females and 73 males

7. Methodology
Pneumonitor 2
• ECG signal to estimate heart rate
and tachogram
• Impedance signal relating to
main breathing activity
• Portable
• Recording on SD card
• Rechargeable battery
• Motion signal from 3-axis
accelerometer to indicate
subject’s activity and body position
7

8. Methodology
8
IP electrodes
Electrode configuration
ECG electrodes

9. Methodology
Study protocol
9
5 minute free breathing supine body position

10. Methodology
• RR intervals were established using:
➡ R peaks detection,
➡ intervals between consecutive R peaks determination,
➡ interpolation.
• Tidal Volume
➡ No calibrations procedures were performed.
➡ Assuming, that changes of impedance relates linearly
with changes of the amount of air in the lungs.
Signals
10

11. Methodology
• Granger causality test
➡ Statistical test for determining whether one time series is ”useful”
in modeling/predicting another one.
➡ Assessment whether breathing or cardiac activity could be consider
as a cause for the second signal changes.
➡ Which approach gives higher test statistics?
• Best shift
➡ What is the shift between signals?
➡ What is the determination coefficient of linear model between
tachogram and tidal volume after applying the adjustment?
• ANOVA
➡ Significance estimation of each demographic parameter
on Granger causality test statistics and best shift parameters.
Analysis
11

12. Results
Example signals
12

13. Results
• Higher test statistics of Granger causality test obtained while assuming
tachogram as the cause.
13
Granger causality test

14. Results
• Concerning physiological intuition we changed the convention
➡ the beginning of inspiration was marked as a maximum of TV signal
• The best adjustment was a positive tachogram's shift by 296 ± 264 ms
➡ taking into account the results only for arbitrarily set R2 > 0.2
14
Best shift

15. Results
• No considered demographic parameter had significant effect on the
differences between Granger causality test statistics and the best shift
between RR intervals and TV signals.
15
ANOVA

16. Summary
Depending on the interpretation, the causal analysis allows to assess
synchronization between cardiac and respiratory function.
Pneumonitor 2 provides the opportunity to assess cardiorespiratory
coupling, minimally affecting the natural functioning of the subject.
Further analyses will include approaches in spectral and information domain.
16

17. Marcel Młyńczak, MSc
mlynczak@mchtr.pw.edu.pl
Analysis of cardiorespiratory coupling
in athletes in rest using causal approach
Zakopane, March 4th, 2017

18. Discussion
Ambulatory respiratory monitoring
Sleep Physiology Sport medicine
• Hypo-, normo-, and
hyperventilation monitoring
in the obese and those with
neuromuscular diseases
• Cardiorespiratory coupling
analysis
• In-house diagnostics
• Training control
• Determining the level of
exercice
Figures adapted from ”Pulmonary Function Testing” Rolf M. Schlegelmilch, Rüdiger Kramme, Springer, 2011
• Monitoring of breathing
disorders
• Analysis of the effects of
pharmacological treatment
18

19. Discussion
Quantitative respiratory parameters
Figures adapted from Clevend Clinic Medical & Wikicommons materials
19
Breathing frequency [ l/min ]
Flow-volume parametersTidal volume [ l ]
Minute ventilation [ l/min ]