Associations of Personal Hourly Exposures to Air Temperature and Pollution with Resting Heart Rate in Chronic Obstructive Pulmonary Disease.

Previous studies linked higher daily ambient air temperature and pollution with increased cardiorespiratory morbidity, but immediate effects of personal, hourly exposures on resting heart rate remained unclear. We followed 30 older former smokers with chronic obstructive pulmonary disease (COPD) in Massachusetts for four nonconsecutive 30-day periods over 12 months, collecting 54,487 hourly observations of personal air temperature, fine particulate matter (PM2.5), nitrogen dioxide (NO2), ozone (O3), and resting heart rate. We explored the single lag effects (0-71 h) and cumulative effects (0-5 h, the significant lag windows) of air temperature and pollution on resting heart rate using generalized additive mixed models with distributed lag nonlinear models. Single lag effects of higher air temperature and pollutants on higher resting heart rate were most pronounced at lag 0 to 5 h. Cumulative effects of higher air temperature, PM2.5, O3, and NO2 (each interquartile range increment) on higher resting heart rate at lag 0-5 h, show differences of (beats per minute [bpm], 95% CI) 1.46 (1.31-1.62), 0.35 (0.32-0.39), 2.32 (2.19-2.45), and 1.79 (1.66-1.92), respectively. In conclusion, higher personal hourly air temperature, PM2.5, O3, and NO2 exposures at lag 0-5 h are associated with higher resting heart rate in COPD patients.

Short- and medium-term cumulative effects of traffic-related air pollution on resting heart rate in the elderly: A wearable device study.

BACKGROUND: Epidemiological evidence regarding the association between air pollution and resting heart rate (RHR), a predictor of cardiovascular disease and mortality, is limited and inconsistent. OBJECTIVES: We used wearable devices and time-series analysis to assess the exposure-response relationship over an extended lag period. METHODS: Ninety-seven elderly individuals (>65 years) from the Taipei Basin participated from May to November 2020 and wore Garmin® smartwatches continuously until the end of 2021 for heart rate monitoring. RHR was defined as the daily average of the lowest 30-min heart rate. Air pollution exposure data, covering lag periods from 0 to 60 days, were obtained from nearby monitoring stations. We used distributed lag non-linear models and linear mixed-effect models to assess cumulative effects of air pollution. Principal component analysis was utilized to explore underlying patterns in air pollution exposure, and subgroup analyses with interaction terms were conducted to explore the modification effects of individual factors. RESULTS: After adjusting for co-pollutants in the models, an interquartile range increase of 0.18 ppm in carbon monoxide (CO) was consistently associated with increased RHR across lag periods of 0-1 day (0.31, 95 % confidence interval [CI]: 0.24-0.38), 0-7 days (0.68, 95 % CI: 0.57-0.79), and 0-50 days (1.02, 95 % CI: 0.82-1.21). Principal component analysis identified two factors, one primarily influenced by CO and nitrogen dioxide (NO2), indicative of traffic sources. Increases in the varimax-rotated traffic-related score were correlated with higher RHR over 0-1 day (0.36, 95 % CI: 0.25-0.47), 0-7 days (0.62, 95 % CI: 0.46-0.77), and 0-50 days (1.27, 95 % CI: 0.87-1.67) lag periods. Over a 0-7 day lag, RHR responses to traffic pollution were intensified by higher temperatures (ß = 0.80 vs. 0.29; interaction p-value [P_int] = 0.011). Males (ß = 0.66 vs. 0.60; P_int < 0.0001), hypertensive individuals (ß = 0.85 vs. 0.45; P_int = 0.028), diabetics (ß = 0.96 vs. 0.52; P_int = 0.042), and those with lower physical activity (ß = 0.70 vs. 0.54; P_int < 0.0001) also exhibited stronger responses. Over a 0-50 day lag, males (ß = 0.99 vs. 0.96; P_int < 0.0001), diabetics (ß = 1.66 vs. 0.69; P_int < 0.0001), individuals with lower physical activity (ß = 1.49 vs. 0.47; P_int = 0.0006), and those with fewer steps on lag day 1 (ß = 1.17 vs. 0.71; P_int = 0.029) showed amplified responses. CONCLUSIONS: Prolonged exposure to traffic-related air pollution results in cumulative cardiovascular risks, persisting for up to 50 days. These effects are more pronounced on warmer days and in individuals with chronic conditions or inactive lifestyles.

Corrigendum: Cardiac function and autonomic cardiac function during a multi-stage cycling event: a brief report.

[This corrects the article DOI: 10.3389/fspor.2024.1356577.].

Feasibility of Monitoring Heart and Respiratory Rates Using Nonwearable Devices and Consistency of the Measured Parameters: Pilot Feasibility Study.

Background: As Japan is the world's fastest-aging society with a declining population, it is challenging to secure human resources for care providers. Therefore, the Japanese government is promoting digital transformation and the use of nursing care equipment, including nonwearable devices that monitor heart and respiratory rates. However, the feasibility of monitoring heart and respiratory rates with nonwearable devices and the consistency of the rates measured have not been reported. Objective: In this study, we focused on a sheet-type nonwearable device (Safety Sheep Sensor) introduced in many nursing homes. We evaluated the feasibility of monitoring heart rate (HR) and respiratory rate (RR) continuously using nonwearable devices and the consistency of the HR and RR measured. Methods: A sheet-type nonwearable device that measured HR and RR every minute through body vibrations was placed under the mattress of each participant. The participants in study 1 were healthy individuals aged 20-60 years (n=21), while those in study 2 were older adults living in multidwelling houses and required nursing care (n=20). The HR was measured using standard methods by the nurse and using the wearable device (Silmee Bar-type Lite sensor), and RR was measured by the nurse. The primary outcome was the mean difference in HR and RR between nonwearable devices and standard methods. Results: The mean difference in HR was -0.32 (SD 3.12) in study 1 and 0.04 (SD: 3.98) in study 2; both the differences were within the predefined accepted discrepancies (<5 beats/min). The mean difference in RR was -0.98 (SD 3.01) in study 1 and -0.49 (SD 2.40) in study 2; both the differences were within the predefined accepted discrepancies (3 breaths/min). Conclusions: HR and RR measurements obtained using the nonwearable devices and the standard method were similar. Continuous monitoring of vital signs using nonwearable devices can aid in the early detection of abnormal conditions in older people.

International expert consensus statement on physiological interpretation of cardiotocograph (CTG): First revision (2024).

The first international consensus guideline on physiological interpretation of cardiotocograph (CTG) produced by 44 CTG experts from 14 countries was published in 2018. This guideline ensured a paradigm shift from classifying CTG by arbitrarily grouping certain features of the fetal heart rate into different "categories", and then, randomly combining them to arrive at an overall classification of CTG traces into "Normal, Suspicious and Pathological" (or Category I, II and III) to a classification which is based on the understanding of fetal pathophysiology. The guideline recommended the recognition of different types of fetal hypoxia, and the determination of features of fetal compensatory responses as well as decompensation to ongoing hypoxic stress on the CTG trace. Since its first publication in 2018, there have been several scientific publications relating physiological interpretation of CTG, especially relating to features indicative of autonomic instability due to hypoxic stress (i.e., the ZigZag pattern), and of fetal inflammation. Moreover, emerging evidence has suggested improvement in maternal and perinatal outcomes in maternity units which had implemented physiological interpretation of CTG. Therefore, the guideline on Physiological Interpretation of CTG has been revised to incorporate new scientific evidence, and the interpretation table has been expanded to include features of chorioamnionitis and relative utero-placental insufficiency of labour (RUPI-L).

Relationship Between High Frequency Component of Heart Rate Variability and Delta EEG Power During Sleep in Women With Irritable Bowel Syndrome Compared to Healthy Women.

OBJECTIVE: To explore the relationship between the high frequency (HF) heart rate variability (HRV) and electroencephalogram (EEG) delta band power in women with irritable bowel syndrome (IBS) versus healthy control women. MATERIALS AND METHODS: Twenty women with IBS and twenty healthy controls were studied over three consecutive nights using polysomnography in a sleep laboratory. To avoid the first night effect, only second-night data were analyzed. Power spectral analysis was applied to HRV and EEG recordings. The linear system coherence/phase analysis assessed the relationship between normalized HF power of HRV and normalized delta band power of EEG during the first four NREM-REM sleep cycles. RESULTS: Women with IBS exhibited a significantly higher percentage of NREM sleep, higher normalized HF, lower normalized low frequency (LF) and decreased LF/HF ratio of HRV in the first four NREM-REM sleep cycles compared to controls. Additionally, their normalized delta band power was significantly lower in these sleep cycles and over the whole night. The phase shift between HF and delta band power was significantly longer in the IBS group. While the coherence between normalized HF and normalized delta band power was lower in the IBS group, the difference was not statistically significant. CONCLUSIONS: The coherence/phase analysis showed a dysregulated interaction between autonomic and central nervous systems in women with IBS, manifested by increased lag time between cardiac and EEG delta band power compared to healthy controls. Whether this dysregulation contributes to the pathophysiology of IBS remains to be determined.

Assessing the psychobiological demands of high-fidelity training in pre-hospital emergency medicine.

BACKGROUND: Individuals who provide critical emergency care mount rapid psychobiological responses when faced with an incident. These responses are adaptive and ensure resources at time of demand; however, frequent activation with minimal opportunity for recovery can have negative consequences for health and wellbeing. Monitoring individuals in real emergency situations would provide an understanding of their stress responses during the provision of critical care; however, this presents logistical challenges. An alternative is to assess individuals during high-fidelity training scenarios. This is the first comprehensive assessment of psychobiological responding during continuous high-fidelity training in pre-hospital emergency medicine. METHODS: A sample of doctors and paramedics (N = 27) participated during 10 days of training and a weekend of no activities. Training involved the acquisition of human factors, non-technical and surgical skills, and their application in complex high-fidelity scenarios including road-traffic accidents, firearms incidents, and swift water rescue operations. On each day participants reported levels of state, cognitive, and somatic anxiety, and self-confidence following waking and before sleep, and their anticipated (at wake) and experienced (before sleep) demands of the day. Saliva samples were obtained each day for assessment of diurnal cortisol indices and the Cortisol Awakening Response (CAR). Garmin smartwatches were worn throughout for the collection of heart rate and HRV-derived stress. RESULTS: There were significant (p < 0.001) differences across days for state, cognitive, and somatic anxiety; self-confidence; anticipated and experienced demands; aggregated measures of heart rate and HRV-derived stress; levels of cortisol at waking (p = 0.002) and for the CAR (p < 0.001). Measures of psychobiological responding during training were distinct from the weekend and the highest levels of psychobiological responding occurred on days characterised by greater anticipated and experienced demands. DISCUSSION: This high-fidelity training is typical of the day-to-day requirements of emergency services and these observations are representative of functioning during real-life critical care emergencies. Increased responding during times of demand is adaptive; however, frequent and sustained responding increases allostatic load and is a contributor to burnout. As burnout is a significant concern in emergency medicine, this study identifies patterns of responding and recovery that may impact upon longer-term health and wellbeing.

Impact of early detection and steroid treatment on fetal ventricular heart rate and pacemaker implantation in anti-Ro/SSA positive congenital heart block.

INTRODUCTION: We investigated the effects of timing of detection and transplacental fluorinated steroid treatment on ventricular heart rate (HR) and age at pacemaker implantation in fetal third-degree atrioventricular block (AVB). MATERIAL AND METHODS: Twenty-five of 31 fetuses diagnosed with Ro/SSA autoantibody-positive AVB II-III at our tertiary fetal cardiology center (2000-2020) and AVB III as final feto-neonatal outcome were reviewed. RESULTS: AVB was detected approximately 5 weeks earlier in pregnancy if followed in a surveillance program compared to cases referred from primary care for bradycardia (20.6 [2.3] [mean (SD)] vs. 25.4 [3.2] weeks, p = 0.001). AVB detected before 24 weeks had higher HR than those detected later in gestation (63.3 [6.9] vs. 57.2 [6.9] bpm, p = 0.042), with a larger proportion having HR >60 bpm (80% vs. 33%, p = 0.041). The 17/25 cases that received treatment with fluorinated steroid were diagnosed earlier in gestation, with higher HR at diagnosis (61.7 [7.1] vs. 54.7 [6.3] bpm, p = 0.026), 1-2 weeks after diagnosis/treatment start, and before birth (65.4 [12.4] vs. 54.9 [5.7] bpm, p = 0.030) than untreated cases. Overall, 11 cases were commenced on betamimetics: three at diagnosis and eight at or after the examination made 1-2 weeks after diagnosis/treatment start, without any HR improvement. Two of 24 surviving babies were born preterm, and 4/24 received a neonatal pacemaker. Age at pacemaker implantation correlated significantly with HR before birth (Spearman R 0.57, p = 0.004), and fetuses with HR >60 bpm had a higher rate of pacemaker-free survival at three (90% vs. 40%, p = 0.018) and 12 months of age (80% vs. 13%, p = 0.002). The same trend was observed in pacemaker-free survival at 3 months of age in fluorinated steroid-treated compared to untreated cases (71% vs. 38%, ns). CONCLUSIONS: Our data confirm that AVB III detected earlier in gestation have a higher HR, and suggest that this higher HR can be successfully maintained to the end of gestation in cases treated with fluorinated steroids. Fetuses with HR >60 bpm before birth had a lower rate of pacemaker implantation at 3 and 12 months of age.

Pathways to maternal health inequities: Structural racism, sleep, and physiological stress.

Racial inequities in health are vast and well-documented, particularly regarding maternal and infant health. Sleep health, including but not limited to duration and quality, is central to overall health and well-being. However, research has not adequately addressed how racism embedded in structures and systems, in addition to individual experiences, may affect maternal health by impacting sleep. In this critical review, we aim to 1) synthesize findings, emphasizing collaborative studies within our group, 2) highlight gaps in knowledge, and 3) propose a theoretical framework and methodological approach for moving the field forward. Specifically, we focus on findings and future directions linking perinatal sleep, cardiovascular and immune function, and racial disparities in maternal health. Because too few studies look beyond individual-level determinants of sleep deficiencies among Black Americans, we assert a critical need for research that bridges multiple levels of analysis (e.g., individual, community, society) and provides recommendations for specific health parameters that researchers in this area can target. Although the need to understand and address perinatal health disparities is clear, the goal of identifying multilevel mechanisms underlying how racism in one's environment and daily life may interact to affect health extends far beyond pregnancy research.

Racial biases, facial trustworthiness, and resting heart rate variability: unravelling complexities in pain recognition.

The study explores whether racial identity and appearance-based trustworthiness judgments can affect recognition of pain in medical students differing in levels of resting heart rate variability (HRV), a measure of parasympathetic control of the heart. After undergoing HRV assessment, 68 medical students (37 females) participated in a dynamic pain recognition task, viewing video clips of White and Black faces, which differed in perceived trustworthiness based on facial appearance, transitioning from neutral to intense pain expressions. Response time, pain intensity attribution and treatment recommendations were analyzed. Pain was recognized slower and estimated as less intense in Black compared to White faces, leading to a lower likelihood of recommending therapy. Pain recognition was faster for untrustworthy-looking White faces compared to trustworthy ones, while perceived trustworthiness had a minimal impact on the speed of pain recognition in Black faces. However, untrustworthy-looking faces were estimated to express more pain, particularly for Black faces. Notably, these biases were more pronounced in individuals with low, rather than high, resting HRV. Considering that therapeutic decisions mirrored pain intensity attribution, it would be important to increase awareness of these biases during medical training in order to promote equity in future pain assessment and treatment.

Agreement Between Heart Rate Variability - Derived vs. Ventilatory and Lactate Thresholds: A Systematic Review with Meta-Analyses.

BACKGROUND: Determining thresholds by measuring blood lactate levels (lactate thresholds) or gas exchange (ventilatory thresholds) that delineate the different exercise intensity domains is crucial for training prescription. This systematic review with meta-analyses aims to assess the overall validity of the first and second heart rate variability - derived threshold (HRVT1 and HRVT2, respectively) by computing global effect sizes for agreement and correlation between HRVTs and reference - lactate and ventilatory (LT-VTs) - thresholds. Furthermore, this review aims to assess the impact of subjects' characteristics, HRV methods, and study protocols on the agreement and correlation between LT-VTs and HRVTs. METHODS: Systematic computerised searches for studies determining HRVTs during incremental exercise in humans were conducted. The agreements and correlations meta-analyses were conducted using a random-effect model. Causes of heterogeneity were explored by subgroup analysis and meta-regression with subjects' characteristics, incremental exercise protocols, and HRV methods variables. The methodological quality was assessed using QUADAS-2 and STARDHRV tools. The risk of bias was assessed by funnel plots, fail-safe N test, Egger's test of the intercept, and the Begg and Mazumdar rank correlation test. RESULTS: Fifty included studies (1160 subjects) assessed 314 agreements (95 for HRVT1, 219 for HRVT2) and 246 correlations (82 for HRVT1, 164 for HRVT2) between LT-VTs and HRVTs. The standardized mean differences were trivial between HRVT1 and LT1-VT1 (SMD = 0.08, 95% CI -0.04-0.19, n = 22) and between HRVT2 and LT2-VT2 (SMD = -0.06, 95% CI -0.15-0.03, n = 42). The correlations were very strong between HRVT1 and LT1-VT1 (r = 0.85, 95% CI 0.75-0.91, n = 22), and between HRVT2 and LT2-VT2 (r = 0.85, 95% CI 0.80-0.89, n = 41). Moreover, subjects' characteristics, type of ergometer, or initial and incremental workload had no impact on HRVTs determination. CONCLUSION: HRVTs showed trivial differences and very strong correlations with LT-VTs and might thus serve as surrogates. These results emphasize the usefulness of HRVTs as promising, accessible, and cost-effective means for exercise and clinical prescription purposes.

Feature importance for estimating rating of perceived exertion from cardiorespiratory signals using machine learning.

Introduction: The purpose of this study is to investigate the importance of respiratory features, relative to heart rate (HR), when estimating rating of perceived exertion (RPE) using machine learning models. Methods: A total of 20 participants aged 18 to 43 were recruited to carry out Yo-Yo level-1 intermittent recovery tests, while wearing a COSMED K5 portable metabolic machine. RPE information was collected throughout the Yo-Yo test for each participant. Three regression models (linear, random forest, and a multi-layer perceptron) were tested with 8 training features (HR, minute ventilation (VE), respiratory frequency (Rf), volume of oxygen consumed (VO2), age, gender, weight, and height). Results: Using a leave-one-subject-out cross validation, the random forest model was found to be the most accurate, with a root mean square error of 1.849, and a mean absolute error of 1.461 ± 1.133. Feature importance was estimated via permutation feature importance, and VE was found to be the most important for all three models followed by HR. Discussion: Future works that aim to estimate RPE using wearable sensors should therefore consider using a combination of cardiovascular and respiratory data.

Validity of the estimated core temperature algorithm during real-world prolonged walking exercise under warm ambient conditions.

BACKGROUND: Non-invasive methods to estimate core body temperature (TC) are increasingly available. We examined the group-level and individual participant-level validity of the Estimated Core Temperature (ECTemp™) algorithm to estimate TC based on sequential heart rate (HR) measurements during real-world prolonged walking exercise in warm ambient conditions. METHODS: Participants walked 30 (n = 3), 40 (n = 13) or 50 (n = 2) km on a self-selected pace during which TC was measured every minute using an ingestible temperature capsule. HR was measured every second and used to compute the estimated core temperature (TC-est) using the ECTemp™ algorithm. Bland-Altman analyses were performed to assess agreement between TC and TC-est. A systematic bias <0.1 °C was considered acceptable. RESULTS: 18 participants (56 ± 16 years, 11 males) walked for 549 min (range 418-645 min), while ambient temperature increased from 22 °C to 29 °C. Average HR was 108 ± 13 bpm and TC ranged from 36.9 to 39.2 °C, whereas TC-est ranged from 36.8 to 38.9 °C (n = 8572 observations). Group level data revealed a systematic bias of 0.09 °C (p < 0.001) with limits of agreements of ±0.44 °C. A weak correlation was found between TC and TC-est (r = 0.28; p < 0.001). Large inter-individual differences in bias (range -0.45 °C to 0.62 °C) and correlation coefficients (range -0.09 to 0.95) were found, while only 3 participants (17%) had an acceptable systemic bias of <0.1 °C. CONCLUSION: Group level data showed that the ECTemp™ algorithm had an acceptable systematic bias during prolonged walking exercise in warm ambient conditions, but only 3 out of 18 participants had an acceptable systemic bias. Future studies are needed to improve the accuracy of the algorithm before individual users can rely on their estimated TC during real-world exercise.

Ultra-short-term stress measurement using RGB camera-based remote photoplethysmography with reduced effects of Individual differences in heart rate.

Stress is linked to health problems, increasing the need for immediate monitoring. Traditional methods like electrocardiograms or contact photoplethysmography require device attachment, causing discomfort, and ultra-short-term stress measurement research remains inadequate. This paper proposes a method for ultra-short-term stress monitoring using remote photoplethysmography (rPPG). Previous predictions of ultra-short-term stress have typically used pulse rate variability (PRV) features derived from time-segmented heart rate data. However, PRV varies at the same stress levels depending on heart rates, necessitating a new method to account for these differences. This study addressed this by segmenting rPPG data based on normal-to-normal intervals (NNIs), converted from peak-to-peak intervals, to predict ultra-short-term stress indices. We used NNI counts corresponding to average durations of 10, 20, and 30 s (13, 26, and 39 NNIs) to extract PRV features, predicting the Baevsky stress index through regressors. The Extra Trees Regressor achieved R2 scores of 0.6699 for 13 NNIs, 0.8751 for 26 NNIs, and 0.9358 for 39 NNIs, surpassing the time-segmented approach, which yielded 0.4162, 0.6528, and 0.7943 for 10, 20, and 30-s intervals, respectively. These findings demonstrate that using NNI counts for ultra-short-term stress prediction improves accuracy by accounting for individual bio-signal variations.

Using a virtual reality game to train biofeedback-based regulation under stress conditions.

Physiological regulation strategies can be effective in reducing anxiety. However, while these strategies are often learned and practised under low-stress conditions, they are more likely to be required under conditions of high stress. We created virtual reality (VR) biofeedback games to both teach participants a breathing technique and then practise that technique under stress. We present two studies: the first provides a proof of concept, demonstrating that participants can apply the breathing technique during stress, with a significant lowering of both respiration rate and increase in heart rate variability (HRV) under stress (p < .001). The second study explicitly evaluated the effectiveness of training by comparing trained and untrained groups. Training was associated with a significantly greater HRV (p = .008) under stress. In within-group comparisons of HRV during stress compared to a baseline stressor presented before training, the trained group showed a significantly greater increase compared to untrained controls (p = .025). Our results show the feasibility and potential effectiveness of VR-based games for biofeedback training under experimentally applied stress. This may offer the opportunity for clinical techniques to more closely reflect the circumstances under which those techniques will be required.

Social Context in Stress and Autism: Comparing Physiological Profiles Across Two Social Paradigms in Youth with and without Autism Spectrum Disorder.

Background: The social world is often stressful for individuals with autism spectrum disorder (ASD). Research shows youth with ASD demonstrate physiological hyperreactivity to some social stressors (e.g., interaction) but not others (e.g., evaluation); therefore, this study examined diagnosis (ASD or typical development (TD)), social context, perceived anxiety, and physiological responsivity across multiple stress systems; namely, the hypothalamic pituitary adrenal (HPA) axis and autonomic nervous system (ANS). Method: This study examined 244 ten-to-thirteen-year-olds with ASD (N = 140) or TD (N = 104). Physiological responses, measured by salivary cortisol, heart rate (HR), and respiratory sinus arrhythmia (RSA), were assessed before and after a social evaluative threat paradigm (Trier Social Stress Test; TSST) and social interaction (Trier Social Stress Test- Friendly; TSST-F). Mediation models examined the relationships between anxiety, diagnosis, and physiology. Results: Significant three-way interactions were observed for cortisol (p=0.007) and HR (p=0.002), suggesting diagnostic groups respond differently across context and time points. There was no significant interaction for RSA (p=0.149), although ASD youth had significantly lower RSA overall (p=0.038). State and trait anxiety did not mediate the relationship between diagnosis and physiology (all p>0.05). Conclusions: Findings emphasize the critical role of context and a multisystem approach in examination of physiological social stress in youth with ASD. Results provide a foundation to elucidate unique response patterns across physiological systems to more precisely identify those with heightened physiological arousal across social contexts. It is proposed that future identification of subtypes may ultimately inform approaches for enhancing social engagement.

Comparison of Heart Rate Variability Psychological Responses and Performance in Virtual and Real Archery.

BACKGROUND: This study examines the psychophysiological differences between virtual reality (VR) and real archery. It explores whether VR archery induces heart rate (HR), heart rate variability (HRV), and breathing rates similar to those experienced in real archery. Additionally, the study assesses differences in perceived anxiety, difficulty, confidence, rate of perceived exertion (RPE), and shooting performance between the two modalities, providing insights into the efficacy of VR as a training tool for archery. METHODS: Twenty-two (women: 8) individuals aged 20-24 participated in the study. We first recorded individuals' resting HR, HRV, and breathing rates during baseline. Afterward, participants shot 10 real and virtual arrows from 18 m, whereas their HR, HRV, and breathing rate were measured, each lasting 4 min. Performance in VR and real archery was determined separately as the sum of the shots. We performed paired sample t-tests to compare individuals' performance, psychological, and psychophysiological responses recorded during VR and real arrow shooting. Afterward, we compared percentage changes between VR and real archery. RESULTS: Results showed that HR and root mean square of successive differences (RMMSD) were significantly higher during real archery compared to virtual archery. In addition, VR archery led to a greater percentage change in RMSSD compared to real archery. Participants reported greater RPE and perceived difficulty after real archery. Performance was also higher during VR archery than real archery. CONCLUSIONS: Consequently, the results of the present study illustrated that VR, and real archery might lead to different autonomic response patterns in terms of vagal activity.

Evaluating the Effects of Different Cognitive Tasks on Autonomic Nervous System Responses: Implementation of a High-Precision, Low-Cost Complementary Method.

INTRODUCTION: We developed a low-cost, user-friendly complementary research tool to evaluate autonomic nervous system (ANS) activity at varying levels of cognitive workload. This was achieved using visual stimuli as cognitive tasks, administered through a specially designed computer-based test battery. METHODS: To assess sympathetic stress responses, skin conductance response (SCR) was measured, and electrocardiograms (ECG) were recorded to evaluate heart rate variability (HRV), an indicator of cardiac vagal tone. Twenty-five healthy adults participated in the study. SCR and ECG recordings were made during both tonic and phasic phases using a computer-based system designed for visual stimuli. Participants performed a button-pressing task upon seeing the target stimulus, and the relationship between reaction time (RT) and cognitive load was evaluated. RESULTS: Analysis of the data showed higher skin conductance levels (SCLs) during tasks compared to baseline, indicating successful elicitation of sympathetic responses. RTs differed significantly between simple and cognitive tasks, increasing with mental load. Additionally, significant changes in vagally mediated HRV parameters during tasks compared to baseline highlighted the impact of cognitive load on the parasympathetic branch of the ANS, thereby influencing the brain-heart connection. CONCLUSION: Our findings indicate that the developed research tool can successfully induce cognitive load, significantly affecting SCL, RTs, and HRV. This validates the tool's effectiveness in evaluating ANS responses to cognitive tasks.

Pilot turning behavior cognitive load analysis in simulated flight.

Background: To identify the cognitive load of different turning tasks in simulated flight, a flight experiment was designed based on real "preliminary screening" training modules for pilots. Methods: Heart Rate Variability (HRV) and flight data were collected during the experiments using a flight simulator and a heart rate sensor bracelet. The turning behaviors in flight were classified into climbing turns, descending turns, and level flight turns. A recognition model for the cognitive load associated with these turning behaviors was developed using machine learning and deep learning algorithms. Results: pnni_20, range_nni, rmssd, sdsd, nni_20, sd1, triangular_index indicators are negatively correlated with different turning load. The LSTM-Attention model excelled in recognizing turning tasks with varying cognitive load, achieving an F1 score of 0.9491. Conclusion: Specific HRV characteristics can be used to analyze cognitive load in different turn-ing tasks, and the LSTM-Attention model can provide references for future studies on the selection characteristics of pilot cognitive load, and offer guidance for pilot training, thus having significant implications for pilot training and flight safety.