An examination of single day vs. multi-day heart rate variability and its relationship to heart rate recovery following maximal aerobic exercise in females

Post-exercise heart rate recovery and its speed are associated with resting-reactivity cardiovagal modulation in healthy women

The present study sought to expand upon prior investigations of the relationship between post-exercise heart rate recovery (HRR) and cardiovagal resting-reactivity modulation. HRR from 1st to 5th min after maximal exercise test was correlated with a cardiovagal index of heart rate variability (SD1) at resting (supine and orthostatic positions) and its reactivity after the orthostatic stress test in 34 healthy women. Statistical analysis employed non-parametric tests with a p-value set at 5%. HRR, ∆%HRR, and coefficient of HRR (CHRR) at the 3rd and 5th min correlated with SD1 and SD1n (normalized units) in the supine position (rs = 0.36 to 0.47; p =  < 0.01). From the 1st to 5th min, HRR, ∆%HRR, and CHRR correlated with SD1 and SD1n in the orthostatic position (rs = 0.29 to 0.47; p =  ≤ 0.01 to 0.05), except for HRR at 5th min with SD1n (p = 0.06). Following the orthostatic stress test, HRR at 3rd and HRR, %∆HRR at 5th min correlated with ∆absSD1 (rs = 0.28 to 0.35; p = 0.02 to 0.05). All HRR measurements at 1st min correlated with ∆absSD1n (rs = 0.32 to 0.38; p = 0.01 to 0.03), and the CHRR at 1st min correlated with ∆%SD1(rs = 0.37; p = 0.01). After the sample was divided into high and low cardiovagal modulation subgroups, the subgroup with high modulation at rest (supine and orthostatic) and higher cardiovagal reactivity (reduction) showed faster HRR (p =  ≤ 0.01 to 0.05; ES:0.37 to 0.50). HRR throughout the 1st to 5th min positively correlates with cardiovagal modulation in the orthostatic position, and the 3rd and 5th min positively correlate with cardiovagal modulation in both postures at rest. Faster HRR following the maximal exercise test is associated with high resting-reactivity cardiovagal modulation in healthy women.

Physiological sensor data cleaning with autoencoders

Objective.Physiological sensor data (e.g. photoplethysmograph) is important for remotely monitoring patients' vital signals, but is often affected by measurement noise. Existing feature-based models for signal cleaning can be limited as they might not capture the full signal characteristics.Approach.In this work we present a deep learning framework for sensor signal cleaning based on dilated convolutions which capture the coarse- and fine-grained structure in order to classify whether a signal is noisy or clean. However, since obtaining annotated physiological data is costly and time-consuming we propose an autoencoder-based semi-supervised model which is able to learn a representation of the sensor signal characteristics, also adding an element of interpretability.Main results.Our proposed models are over 8% more accurate than existing feature-based approaches with half the false positive/negative rates. Finally, we show that with careful tuning (that can be improved further), the semi-supervised model outperforms supervised approaches suggesting that incorporating the large amounts of available unlabeled data can be advantageous for achieving high accuracy (over 90%) and minimizing the false positive/negative rates.Significance.Our approach enables us to reliably separate clean from noisy physiological sensor signal that can pave the development of reliable features and eventually support decisions regarding drug efficacy in clinical trials.

Correlation between Heart rate recovery and Left Atrial phasic functions evaluated by 2D speckle-tracking Echocardiography after Acute Myocardial infarction

BACKGROUND

Heart rate recovery (HRR) in the exercise test is the index of cardiac autonomic system function and sympathovagal balance impaired in patients with myocardial infarction (MI). An instance is left atrial (LA) phasic function, which is impaired in such patients. In this study, we investigated the role of HRR in predicting LA phasic functions in patients with MI.

METHODS

The present study recruited 144 consecutive patients with ST-elevation MI. A symptom-limited exercise test was performed about 5 weeks after MI, with echocardiography conducted just before the exercise test. The patients were divided into abnormal and normal HRR at 60 s (HRR60) and again into abnormal and normal HRR at 120 s (HRR120) after the exercise test. LA phasic functions, evaluated by 2D speckle-tracking echocardiography, were compared between the 2 groups.

RESULTS

Patients with abnormal HRR120 had lower LA strain values and strain rates during the reservoir, conduit, and contraction phases, while those with abnormal HRR60 had lower LA strain values and strain rates during the reservoir and conduit phases. The differences were lost after adjustments for possible confounders, except for LA strain and strain rate during the conduit phase, in patients with abnormal HRR120.

CONCLUSIONS

Abnormal HRR120 in the exercise test can independently predict decreased LA conduit function in patients with ST-elevation MI.