Geometric indexes of heart rate variability in healthy individuals exposed to long-term air pollution

Environmental Exposome and Atrial Fibrillation: Emerging Evidence and Future Directions

There has been increased awareness of the linkage between environmental exposures and cardiovascular health and disease. Atrial fibrillation is the most common sustained cardiac arrhythmia, affecting millions of people worldwide and contributing to substantial morbidity and mortality. Although numerous studies have explored the role of genetic and lifestyle factors in the development and progression of atrial fibrillation, the potential impact of environmental determinants on this prevalent condition has received comparatively less attention. This review aims to provide a comprehensive overview of the current evidence on environmental determinants of atrial fibrillation, encompassing factors such as air pollution, temperature, humidity, and other meteorologic conditions, noise pollution, greenspace, and the social environment. We discuss the existing evidence from epidemiological and mechanistic studies, critically evaluating the strengths and limitations of these investigations and the potential underlying biological mechanisms through which environmental exposures may affect atrial fibrillation risk. Furthermore, we address the potential implications of these findings for public health and clinical practice and identify knowledge gaps and future research directions in this emerging field.

Cardiac autonomic modulation in response to postural transition during a virtual reality task in individuals with spinal cord injury: A cross-sectional study

PURPOSE

The postural transition from sitting to standing is a moment of dysautonomic occurrence in individuals with Spinal Cord Injury (SCI). Different tools can be used to minimize this event, such as virtual reality. Thus, we aimed to analyze cardiac autonomic modulation in individuals with SCI during postural transition from the sitting to orthostatism position using a cognitive virtual reality (VR) task.

METHODS

Individuals with and without SCI were positioned on the Easy Stand® device, sitting at rest, at 0° considering the angle between the seat and the floor, elevation at 45°, and orthostatism at 90°, for 5 minutes in each position. Heart rate variability (HRV) measures of sympathovagal balance were collected (heart rate receiver: Polar V800). The groups were subdivided into two groups, one that performed VR as an intervention during the postural angle changes and another group that did not perform VR.

RESULTS

We evaluated 76 individuals, 40 with a medical diagnosis of SCI and 36 who composed the able-bodied control group without SCI, matched by age and sex. The HRV results showed that the SCI group who performed the task in VR demonstrated no significant difference in parasympathetic activation and global variability between the sitting versus 90° positions. There was better sympathovagal balance in SCI and able-bodied control groups who performed the VR task between the sitting versus 90° positions.

CONCLUSION

The use of a VR task seems to contribute to better sympathovagal balance, with the potential to reduce dysautonomia during postural changes.

Effects of a Combined Intradialytic Exercise Training Program and Music on Cardiac Autonomic Nervous System Activity in Hemodialysis Patients

This study aimed to examine the effect of an intradialytic exercise program in combination with music on heart rate variability (HRV) indices and functional capacity in patients on maintenance hemodialysis (HD). Methods: Forty HD patients were randomized to four training groups for six months: the combined music and exercise group (Group A), the exercise group (Group B), the music group (Group C), and the control group (Group D). At baseline and after 6 months, all participants underwent both short- (for 30 min) and long- (for 24 h) term measurements of HRV and functional capacity assessment with a 6 min walking test (6MWT). Patients of groups A and C listened to preferred music. Results: Long-term HRV analysis showed that standard deviation of all normal-to-normal RR intervals (SDNN) and the square root of the mean squared differences of successive RR intervals (rMSSD) were significantly higher at the end of the study in groups A (by 13.2% and 47.3%), B (by 15.1% and 50%), and C (by 9.0% and 30.1%), compared to group D (p < 0.05). Values of rMSSD and percentage of RR intervals differing by more than 50 ms from the preceding RR interval (pNN50) were elevated in groups A (by 35.6% and 142.9%), B (by 36.1% and 75%), and C (by 15.2% and 28.6%), compared to baseline measurements (p < 0.05). Also, pNN50 was increased in group A compared to groups B (by 21.4%), C (by 88.9%), and D (by 142.9%) (p < 0.05). Similar results were noted by short-term HRV analysis. Functional capacity was improved at the end of the 6-month study in groups A (by 20.3% and 25.7%) and B (by 15.8% and 21.1%) compared to groups C and D (p < 0.05). Conclusions: Intradialytic exercise combined with music-listening can improve the functional capacity and cardiac autonomic nervous system activity in hemodialysis patients.

Assimilative capacity approach for air pollution control in automotive engines through magnetic field-assisted combustion of hydrocarbons

Deterioration of air quality through the combustion of hydrocarbon fuels has been one of the global transboundary problems put before the research community since last five decades. According to the updated statistics, 79% of energy needs in India are met by fossil fuel combustion which results in the emission of toxic pollutants like carbon monoxide, oxides of nitrogen, and unburned hydrocarbons. Air quality has seriously been affected in many parts of India, and statistically, 13 out of 15 most polluted cities in the world lie in India. Magnetic field-assisted combustion has been proven as a reliable technology in internal combustion engines for enhancing the combustion of fuels and reduction of harmful emissions that are the byproducts of incomplete combustion of fuels. In the present work, the magnetic field-assisted combustion of a liquid-phase and a gas-phase fuel (gasoline and LPG) has been studied in a multicylinder automobile engine replicating on road driving conditions in a laboratory focusing on the levels of emissions in comparison with normal combustion of both the fuels. The experimental study concludes that the applied magnetic field positively influences combustion, resulting in reduced level of emission of toxic components irrespective of the phase of hydrocarbon fuels. It is also observed that the percentage reduction in emissions increases with increase in intensity of magnetization. The maximum reduction obtained for CO and UBHC emissions through this technique is 20.58% and 14.47%, respectively. The effectiveness of MFAC in countering air pollution from vehicular exhaust is also studied with respect to fuel phase and mode of operation. The effectiveness of MFAC is observed to be more in high-speed operation of the engine and decreases in the order CO > UBHC > NO. The obtained emission results have a cumulative significance as 45% of total air pollution in India is caused by combustion of hydrocarbons in automotive engines.

A Proposal for a Data-Driven Approach to the Influence of Music on Heart Dynamics

Electrocardiographic signals (ECG) and heart rate viability measurements (HRV) provide information in a range of specialist fields, extending to musical perception. The ECG signal records heart electrical activity, while HRV reflects the state or condition of the autonomic nervous system. HRV has been studied as a marker of diverse psychological and physical diseases including coronary heart disease, myocardial infarction, and stroke. HRV has also been used to observe the effects of medicines, the impact of exercise and the analysis of emotional responses and evaluation of effects of various quantifiable elements of sound and music on the human body. Variations in blood pressure, levels of stress or anxiety, subjective sensations and even changes in emotions constitute multiple aspects that may well-react or respond to musical stimuli. Although both ECG and HRV continue to feature extensively in research in health and perception, methodologies vary substantially. This makes it difficult to compare studies, with researchers making recommendations to improve experiment planning and the analysis and reporting of data. The present work provides a methodological framework to examine the effect of sound on ECG and HRV with the aim of associating musical structures and noise to the signals by means of artificial intelligence (AI); it first presents a way to select experimental study subjects in light of the research aims and then offers possibilities for selecting and producing suitable sound stimuli; once sounds have been selected, a guide is proposed for optimal experimental design. Finally, a framework is introduced for analysis of data and signals, based on both conventional as well as data-driven AI tools. AI is able to study big data at a single stroke, can be applied to different types of data, and is capable of generalisation and so is considered the main tool in the analysis.

Fine particulate matter constituents and heart rate variability: A panel study in Shanghai, China

BACKGROUND

Short-term exposure to fine particulate matter (PM_2.5) has been associated with reduced heart rate variability (HRV), an established indicator of cardiac autonomic function, but it remains uncertain which specific constituents of PM_2.5 had key impacts.

OBJECTIVE

To examine the short-term associations between various PM_2.5 constituents and HRV measures.

METHODS

We conducted a retrospective panel study among 78 participants who received repeated 24-h electrocardiogram testing in Shanghai, China from 2015 to 2019. We obtained daily concentrations of 14 main chemical constituents of PM_2.5 from a fixed-site monitor. During 3 or 4 rounds of follow-ups, we measured 6 HRV parameters, including 3 frequency-domain parameters (power in very low frequency, low frequency and high frequency) and 3 time-domain parameters (standard deviation of normal-to-normal intervals, root mean square successive difference and percent of adjacent normal R-R intervals with a difference ≥50 msec). We used linear mixed-effects models to analyze the data after controlling for time trends, environmental and individual risk factors.

RESULTS

The average daily PM_2.5 exposure was 45.8 μg/m³ during the study period. The present-day exposure to PM_2.5 had the strongest negative influences on various HRV indicators. These associations attenuated greatly on lag 1 d or lag 2 d. Elemental carbon, organic carbon, nitrate, sulfate, arsenic, cadmium, chromium and nickel were consistently associated with reduced HRV parameters in both single-constituent models and constituent-PM_2.5 models.

CONCLUSION

Our study highlighted the key roles of traffic-related components of PM_2.5 in inhibiting cardiac autonomic function.