Complexity and Entropy in Physiological Signals (CEPS): Resonance Breathing Rate Assessed Using Measures of Fractal Dimension, Heart Rate Asymmetry and Permutation Entropy.

BACKGROUND: As technology becomes more sophisticated, more accessible methods of interpretating Big Data become essential. We have continued to develop Complexity and Entropy in Physiological Signals (CEPS) as an open access MATLAB® GUI (graphical user interface) providing multiple methods for the modification and analysis of physiological data. METHODS: To demonstrate the functionality of the software, data were collected from 44 healthy adults for a study investigating the effects on vagal tone of breathing paced at five different rates, as well as self-paced and un-paced. Five-minute 15-s recordings were used. Results were also compared with those from shorter segments of the data. Electrocardiogram (ECG), electrodermal activity (EDA) and Respiration (RSP) data were recorded. Particular attention was paid to COVID risk mitigation, and to parameter tuning for the CEPS measures. For comparison, data were processed using Kubios HRV, RR-APET and DynamicalSystems.jl software. We also compared findings for ECG RR interval (RRi) data resampled at 4 Hz (4R) or 10 Hz (10R), and non-resampled (noR). In total, we used around 190-220 measures from CEPS at various scales, depending on the analysis undertaken, with our investigation focused on three families of measures: 22 fractal dimension (FD) measures, 40 heart rate asymmetries or measures derived from Poincaré plots (HRA), and 8 measures based on permutation entropy (PE). RESULTS: FDs for the RRi data differentiated strongly between breathing rates, whether data were resampled or not, increasing between 5 and 7 breaths per minute (BrPM). Largest effect sizes for RRi (4R and noR) differentiation between breathing rates were found for the PE-based measures. Measures that both differentiated well between breathing rates and were consistent across different RRi data lengths (1-5 min) included five PE-based (noR) and three FDs (4R). Of the top 12 measures with short-data values consistently within ± 5% of their values for the 5-min data, five were FDs, one was PE-based, and none were HRAs. Effect sizes were usually greater for CEPS measures than for those implemented in DynamicalSystems.jl. CONCLUSION: The updated CEPS software enables visualisation and analysis of multichannel physiological data using a variety of established and recently introduced complexity entropy measures. Although equal resampling is theoretically important for FD estimation, it appears that FD measures may also be usefully applied to non-resampled data.

CEPS: An Open Access MATLAB Graphical User Interface (GUI) for the Analysis of Complexity and Entropy in Physiological Signals.

BACKGROUND: We developed CEPS as an open access MATLAB® GUI (graphical user interface) for the analysis of Complexity and Entropy in Physiological Signals (CEPS), and demonstrate its use with an example data set that shows the effects of paced breathing (PB) on variability of heart, pulse and respiration rates. CEPS is also sufficiently adaptable to be used for other time series physiological data such as EEG (electroencephalography), postural sway or temperature measurements. METHODS: Data were collected from a convenience sample of nine healthy adults in a pilot for a larger study investigating the effects on vagal tone of breathing paced at various different rates, part of a development programme for a home training stress reduction system. RESULTS: The current version of CEPS focuses on those complexity and entropy measures that appear most frequently in the literature, together with some recently introduced entropy measures which may have advantages over those that are more established. Ten methods of estimating data complexity are currently included, and some 28 entropy measures. The GUI also includes a section for data pre-processing and standard ancillary methods to enable parameter estimation of embedding dimension m and time delay τ ('tau') where required. The software is freely available under version 3 of the GNU Lesser General Public License (LGPLv3) for non-commercial users. CEPS can be downloaded from Bitbucket. In our illustration on PB, most complexity and entropy measures decreased significantly in response to breathing at 7 breaths per minute, differentiating more clearly than conventional linear, time- and frequency-domain measures between breathing states. In contrast, Higuchi fractal dimension increased during paced breathing. CONCLUSIONS: We have developed CEPS software as a physiological data visualiser able to integrate state of the art techniques. The interface is designed for clinical research and has a structure designed for integrating new tools. The aim is to strengthen collaboration between clinicians and the biomedical community, as demonstrated here by using CEPS to analyse various physiological responses to paced breathing.

EEG applications for sport and performance.

One approach to understanding processes that underlie skilled performing has been to study electrical brain activity using electroencephalography (EEG). A notorious problem with EEG is that genuine cerebral data is often contaminated by artifacts of non-cerebral origin. Unfortunately, such artifacts tend to be exacerbated when the subject is in motion, meaning that obtaining reliable data during exercise is inherently problematic. These problems may explain the limited number of studies using EEG as a methodological tool in the sports sciences. This paper discusses how empirical studies have generally tackled the problem of movement artifact by adopting alternative paradigms which avoid recording during actual physical exertion. Moreover, the specific challenges that motion presents to obtaining reliable EEG data are discussed along with practical and computational techniques to confront these challenges. Finally, as EEG recording in sports is often underpinned by a desire to optimise performance, a brief review of EEG-biofeedback and peak performance studies is also presented. A knowledge of practical aspects of EEG recording along with the advent of new technology and increasingly sophisticated processing models offer a promising approach to minimising, if perhaps not entirely circumventing, the problem of obtaining reliable EEG data during motion.

A randomized controlled trial of the effects of hypnosis with 3-D virtual reality animation on tiredness, mood, and salivary cortisol.

Case studies suggest hypnosis with a virtual reality (VR) component may be an effective intervention; although few follow-up randomized, controlled trials have been performed comparing such interventions with standard hypnotic treatments. Thirty-five healthy participants were randomized to self-hypnosis with VR imagery, standard self-hypnosis, or relaxation interventions. Changes in sleep, cortisol levels, and mood were examined. Self-hypnosis involved 10- to 20-min. sessions visualizing a healthy immune scenario. Trait absorption was also recorded as a possible moderator. Moderated regression indicated that both hypnosis interventions produced significantly lower tiredness ratings than relaxation when trait absorption was high. When trait absorption was low, VR resulted in significantly higher engagement ratings, although this did not translate to demonstrable improvement in outcome. Results suggest that VR imagery may increase engagement relative to traditional methods, but further investigation into its potential to enhance therapeutic efficacy is required.

Acting performance and flow state enhanced with sensory-motor rhythm neurofeedback comparing ecologically valid immersive VR and training screen scenarios.

Actors were trained in sensory-motor rhythm (SMR) neurofeedback interfaced with a computer rendition of a theatre auditorium. Enhancement of SMR led to changes in the lighting while inhibition of theta and high beta led to a reduction in intrusive audience noise. Participants were randomised to a virtual reality (VR) representation in a ReaCTor, with surrounding image projection seen through glasses, or to a 2D computer screen, which is the conventional neurofeedback medium. In addition there was a no-training comparison group. Acting performance was evaluated by three experts from both filmed, studio monologues and Hamlet excerpts on the stage of Shakespeare's Globe Theatre. Neurofeedback learning reached an asymptote earlier as did identification of the required mental state following training in the ReaCTor training compared with the computer screen, though groups reached the same asymptote. These advantages were paralleled by higher ratings of acting performance overall, well-rounded performance, and especially the creativity subscale including imaginative expression, conviction and characterisation. On the Flow State scales both neurofeedback groups scored higher than the no-training controls on self-ratings of sense of control, confidence and feeling at-one. This is the first demonstration of enhancement of artistic performance with eyes-open neurofeedback training, previously demonstrated only with eyes-closed slow-wave training. Efficacy is attributed to psychological engagement through the ecologically relevant learning context of the acting-space, putatively allowing transfer to the real world otherwise achieved with slow-wave training through imaginative visualisation. The immersive VR technology was more successful than a 2D rendition.