Optimizing phase variability threshold for automated synchrogram analysis of cardiorespiratory interactions in amateur cyclists

We propose a procedure suitable for automated synchrogram analysis for setting the threshold below which phase variability between two marker event series is of such a negligible amount that the null hypothesis of phase desynchronization can be rejected. The procedure exploits the principle of maximizing the likelihood of detecting phase synchronization epochs and it is grounded on a surrogate data approach testing the null hypothesis of phase uncoupling. The approach was applied to assess cardiorespiratory phase interactions between heartbeat and inspiratory onset in amateur cyclists before and after 11-week inspiratory muscle training (IMT) at different intensities and compared to a more traditional approach to set phase variability threshold. The proposed procedure was able to detect the decrease in cardiorespiratory phase locking strength during vagal withdrawal induced by the modification of posture from supine to standing. IMT had very limited effects on cardiorespiratory phase synchronization strength and this result held regardless of the training intensity. In amateur athletes training, the inspiratory muscles did not limit the decrease in cardiorespiratory phase synchronization observed in the upright position as a likely consequence of the modest impact of this respiratory exercise, regardless of its intensity, on cardiac vagal control. This article is part of the theme issue 'Advanced computation in cardiovascular physiology: new challenges and opportunities'.

Modeling and Analyzing Neural Signals with Phase Variability using the Fisher-Rao Registration

The Dynamic Time Warping (DTW) has recently been introduced to analyze neural signals such as EEG and fMRI where phase variability plays an important role in the data. In this study, we propose to adopt a more powerful method, referred to as the Fisher-Rao Registration (FRR), to study the phase variability. We systematically compare the FRR with the DTW in three aspects: 1) basic framework, 2) mathematical properties, and 3) computational efficiency. We show that the FRR has superior performance in all these aspects and the advantages are well illustrated with simulation examples. We then apply the FRR method to two real experimental recordings – one fMRI and one EEG data set. It is found the FRR method properly removes the phase variability in each set. Finally, we use the FRR framework to examine brain networks in these two data sets and the result demonstrates the effectiveness of the new method.

Comparison of Lumbopelvic Coordination between Trunk Flexion and Extension

Lumbopelvic coordination describes the relative contributions of lumbar and pelvis to the total trunk flexion/extension motion, which has been identified as a major influential factor to spinal loading. The current study investigated the differences in lumbopelvic coordination between trunk flexion and extension. Thirteen subjects performed pace-controlled trunk flexion/extension motions in the sagittal plane while lumbopelvic continuous relative phase and phase variability were quantified. The results demonstrated that compared with trunk extension, lumbopelvic continuous relative phase and phase variability were 28% and 117% greater in trunk flexion motion, respectively, which indicated a more anti-phase and unstable coordination pattern. Quantifying these coordination patterns helps identifying abnormal patterns and serves as normative benchmarks during low back pain rehabilitation.