Estimating core body temperature using electrocardiogram signals

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.

Objective stress values during radiation emergency medicine for future human resources: Findings from a survey of nurses

Introduction

Shortages of human resources in radiation emergency medicine (REM) caused by the anxiety and stress of due to working in REM, are a major concern. The present study aimed to quantify stress and identify which tasks involved in REM response are most stressful to help educate (human resource development) and effectively reduce stress in workers. Furthermore, the final goal was to reduce the anxiety and stress of medical personnel in the future, which will lead to sufficient human resources in the field of REM.

Methods

In total, 74 nurses who attended an REM seminar were asked to answer a questionnaire (subjective) survey and wear a shirt-type electrocardiogram (objective survey). Then, informed consent was obtained from 39 patients included in the analysis. In the objective survey, average stress values of participants for each activity during the seminar were calculated based on heart rate variability (HRV). The average stress value was output as stress on a relative scale of 0–100, based on the model which is the percentile of the low-frequency/high-frequency ratio derived from HRV at any point in time obtained over time.

Results

A total of 35 (89.7%) participants answered that they had little or no knowledge of nuclear disaster and 33 (84.6%) had more than moderate anxiety. Stress values observed during the decontamination process were significantly higher than those observed when wearing and removing protective gear and during the general medical treatment process (P = 0.001, 0.004, and 0.023, respectively). Stress values did not increase during general medical treatment performed in protective clothing, but increased during the decontamination process, which is the task characteristic of REM.

Discussion

Stress felt by medical personnel throughout the entire REM response may be effectively reduced by providing careful education/training to reduce stress during the decontamination process. Reducing stress during REM response effectively could contribute to resolving the shortage of human resources in this field.