Time Series Analysis using Embedding Dimension on Heart Rate Variability

Heart Rate Variability (HRV) is the measurement sequence with one or more visible variables of an underlying dynamic system, whose state changes with time. In practice, it is difficult to know what variables determine the actual dynamic system. In this research, Embedding Dimension (ED) is used to find out the nature of the underlying dynamical system. False Nearest Neighbour (FNN) method of estimating ED has been adapted for analysing and predicting variables responsible for HRV time series. It shows that the ED can provide the evidence of dynamic variables which contribute to the HRV time series. Also, the embedding of the HRV time series into a four-dimensional space produced the smallest number of FNN. This result strongly suggests that the Autonomic Nervous System that drives the heart is a two features dynamic system: sympathetic and parasympathetic nervous system.Peer reviewedFinal Published versio

The Relationship Between Heart Rate Variability and Electroencephalography Functional Connectivity Variability Is Associated With Cognitive Flexibility

[EN] The neurovisceral integration model proposes a neuronal network that is related to heart rate activity and cognitive performance. The aim of this study was to determine whether heart rate variability (HRV) and variability in electroencephalographic (EEG) functional connectivity in the resting state are related to cognitive flexibility. Thirty-eight right-handed students completed the CAMBIOS test, and their heart and EEG activity was recorded during 6 min in the resting state with their eyes open. We calculated correlations, partial correlations and multiple linear regressions among HRV indices, functional brain connectivity variability and CAMBIOS scores. Furthermore, the sample was divided into groups according to CAMBIOS performance, and one-way ANOVA was applied to evaluate group differences. Our results show direct and inverse correlations among cognitive flexibility, connectivity (positive and negative task networks) and heartbeat variability. Partial correlations and multiple linear regressions suggest that the relation between HRV and CAMBIOS performance is mediated by neuronal oscillations. ANOVA confirms that HRV and variability in functional brain connectivity is related to cognitive performance. In conclusion, the levels of brain signal variability might predict cognitive flexibility in a cognitive task, while HRV might predict cognitive flexibility only when it is mediated by neuronal oscillations.This work was supported by the Spanish Ministry of Economy and Competitiveness (PSI2014-57231-R). Research was funded by Grant Nos. PSI2014-57231-R and PSI2017-88388-C4-3-R from Spanish Ministry of Science. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors have declared that no competing interests exist.Alba, G.; Vila, J.; Rey, B.; Montoya, P.; Muñoz, MÁ. (2019). 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Exploring Cognitive States: Methods for Detecting Physiological Temporal Fingerprints

Cognitive state detection and its relationship to observable physiologically telemetry has been utilized for many human-machine and human-cybernetic applications. This paper aims at understanding and addressing if there are unique psychophysiological patterns over time, a physiological temporal fingerprint, that is associated with specific cognitive states. This preliminary work involves commercial airline pilots completing experimental benchmark task inductions of three cognitive states: 1) Channelized Attention (CA); 2) High Workload (HW); and 3) Low Workload (LW). We approach this objective by modeling these "fingerprints" through the use of Hidden Markov Models and Entropy analysis to evaluate if the transitions over time are complex or rhythmic/predictable by nature. Our results indicate that cognitive states do have unique complexity of physiological sequences that are statistically different from other cognitive states. More specifically, CA has a significantly higher temporal psychophysiological complexity than HW and LW in EEG and ECG telemetry signals. With regards to respiration telemetry, CA has a lower temporal psychophysiological complexity than HW and LW. Through our preliminary work, addressing this unique underpinning can inform whether these underlying dynamics can be utilized to understand how humans transition between cognitive states and for improved detection of cognitive states

Respiratory and cardiac monitoring at night using a wrist wearable optical system

Sleep monitoring provides valuable insights into the general health of an individual and helps in the diagnostic of sleep-derived illnesses. Polysomnography, is considered the gold standard for such task. However, it is very unwieldy and therefore not suitable for long-term analysis. Here, we present a non-intrusive wearable system that, by using photoplethysmography, it can estimate beat-to-beat intervals, pulse rate, and breathing rate reliably during the night. The performance of the proposed approach was evaluated empirically in the Department of Psychology at the University of Fribourg. Each participant was wearing two smart-bracelets from Ava as well as a complete polysomnographic setup as reference. The resulting mean absolute errors are 17.4 ms (MAPE 1.8%) for the beat-to-beat intervals, 0.13 beats-per-minute (MAPE 0.20%) for the pulse rate, and 0.9 breaths-per-minute (MAPE 6.7%) for the breath rate.Comment: Submitted to the 40th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC

The Appreciative Heart: The Psychophysiology of Positive Emotions and Optimal Functioning

This monograph is an overview of Institute of HeartMath's research on the physiological correlates of positive emotions and the science underlying two core HeartMath techniques which supports Heart-Based Living. The heart's connection with love and other positive emotions has survived throughout millennia and across many diverse cultures. New empirical research is providing scientific validation for this age-old association. This 21-page monograph offers a comprehensive understanding of the Institute of HeartMath's cutting-edge research exploring the heart's central role in emotional experience. Described in detail is physiological coherence, a distinct mode of physiological functioning, which is generated during sustained positive emotions and linked with beneficial health and performance-related outcomes. The monograph also provides steps and applications of two HeartMath techniques, Freeze-Frame(R) and Heart Lock-In(R), which engage the heart to help transform stress and produce sustained states of coherence. Data from outcome studies are presented, which suggest that these techniques facilitate a beneficial repatterning process at the mental, emotional and physiological levels

Influence of Task Combination on EEG Spectrum Modulation for Driver Workload Estimation

Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG geförderten) Allianz- bzw. Nationallizenz frei zugänglich.This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.Objective: This study investigates the feasibility of using a method based on electroencephalography (EEG) for deriving a driver’s mental workload index. Background: The psychophysiological signals provide sensitive information for human functional states assessment in both laboratory and real-world settings and for building a new communication channel between driver and vehicle that allows for driver workload monitoring. Methods: An experiment combining a lane-change task and n-back task was conducted. The task load levels were manipulated in two dimensions, driving task load and working memory load, with each containing three task load conditions. Results: The frontal theta activity showed significant increases in the working memory load dimension, but differences were not found with the driving task load dimension. However, significant decreases in parietal alpha activity were found when the task load was increased in both dimensions. Task-related differences were also found. The driving task load contributed more to the changes in alpha power, whereas the working memory load contributed more to the changes in theta power. Additionally, these two task load dimensions caused significant interactive effects on both theta and alpha power. Conclusion: These results indicate that EEG technology can provide sensitive information for driver workload detection even if the sensitivities of different EEG parameters tend to be task dependent. Application: One potential future application of this study is to establish a general driver workload estimator that uses EEG signals

Aerospace Medicine and Biology: A continuing bibliography with indexes (supplement 314)

This bibliography lists 139 reports, articles, and other documents introduced into the NASA scientific and technical information system in August, 1988

Timesharing performance as an indicator of pilot mental workload

Attentional deficits (workloads) were evaluated in a timesharing task. The results from this and other experiments were incorporated into an expert system designed to provide workload metric selection advice to non-experts in the field interested in operator workload

Effect of parasympathetic stimulation on brain activity during appraisal of fearful expressions

Autonomic nervous system activity is an important component of human emotion. Mental processes influence bodily physiology, which in turn feeds back to influence thoughts and feelings. Afferent cardiovascular signals from arterial baroreceptors in the carotid sinuses are processed within the brain and contribute to this two-way communication with the body. These carotid baroreceptors can be stimulated non-invasively by externally applying focal negative pressure bilaterally to the neck. In an experiment combining functional neuroimaging (fMRI) with carotid stimulation in healthy participants, we tested the hypothesis that manipulating afferent cardiovascular signals alters the central processing of emotional information (fearful and neutral facial expressions). Carotid stimulation, compared with sham stimulation, broadly attenuated activity across cortical and brainstem regions. Modulation of emotional processing was apparent as a significant expression-by-stimulation interaction within left amygdala, where responses during appraisal of fearful faces were selectively reduced by carotid stimulation. Moreover, activity reductions within insula, amygdala, and hippocampus correlated with the degree of stimulation-evoked change in the explicit emotional ratings of fearful faces. Across participants, individual differences in autonomic state (heart rate variability, a proxy measure of autonomic balance toward parasympathetic activity) predicted the extent to which carotid stimulation influenced neural (amygdala) responses during appraisal and subjective rating of fearful faces. Together our results provide mechanistic insight into the visceral component of emotion by identifying the neural substrates mediating cardiovascular influences on the processing of fear signals, potentially implicating central baroreflex mechanisms for anxiolytic treatment targets