Improbable effect of carbohydrate diet on cardiac autonomic modulation during exercise

The Accuracy of Acquiring Heart Rate Variability from Portable Devices: A Systematic Review and Meta-Analysis

BACKGROUND

Advancements in wearable technology have provided practitioners and researchers with the ability to conveniently measure various health and/or fitness indices. Specifically, portable devices have been devised for convenient recordings of heart rate variability (HRV). Yet, their accuracies remain questionable.

OBJECTIVE

The aim was to quantify the accuracy of portable devices compared to electrocardiography (ECG) for measuring a multitude of HRV metrics and to identify potential moderators of this effect.

METHODS

This meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Articles published before July 29, 2017 were located via four electronic databases using a combination of the terms related to HRV and validity. Separate effect sizes (ESs), defined as the absolute standardized difference between the HRV value recorded using the portable device compared to ECG, were generated for each HRV metric (ten metrics analyzed in total). A multivariate, multi-level model, incorporating random-effects assumptions, was utilized to quantify the mean ES and 95% confidence interval (CI) and explore potential moderators.

RESULTS

Twenty-three studies yielded 301 effects and revealed that HRV measurements acquired from portable devices differed from those obtained from ECG (ES = 0.23, 95% CI 0.05-0.42), although this effect was small and highly heterogeneous (I² = 78.6%, 95% CI 76.2-80.7). Moderator analysis revealed that HRV metric (p <0.001), position (p = 0.033), and biological sex (β = 0.45, 95% CI 0.30-0.61; p <0.001), but not portable device, modulated the degree of absolute error. Within metric, absolute error was significantly higher when expressed as standard deviation of all normal-normal (R-R) intervals (SDNN) (ES = 0.44) compared to any other metric, but was no longer significantly different after a sensitivity analysis removed outliers. Likewise, the error associated with the tilt/recovery position was significantly higher than any other position and remained significantly different without outliers in the model.

CONCLUSIONS

Our results suggest that HRV measurements acquired using portable devices demonstrate a small amount of absolute error when compared to ECG. However, this small error is acceptable when considering the improved practicality and compliance of HRV measurements acquired through portable devices in the field setting. Practitioners and researchers should consider the cost-benefit along with the simplicity of the measurement when attempting to increase compliance in acquiring HRV measurements.

Heart Rate Variability of Athletes Across Concussion Recovery Milestones: A Preliminary Study

OBJECTIVE

To assess heart rate variability (HRV) in athletes with concussion across three phases of recovery.

DESIGN

A prospective matched control group design included the collection of HRV and symptoms measured by the Rivermead Post-Concussion Questionnaire. These measures were taken at 3 phases of recovery [(1) symptomatic; (2). asymptomatic; and (3) one-week after return-to-play (RTP)]. The same protocol was completed by noninjured athletes.

SETTING

Interuniversity sports teams at a single institution.

PARTICIPANTS

11 athletes, across 7 sports, diagnosed with concussion, and 11 matched-athlete controls volunteered for the study.

INTERVENTION

Physician diagnosed concussion and a sitting to standing protocol for HRV monitoring.

MAIN OUTCOME MEASURES

The frequency, time, and nonlinear domains of HRV were assessed along with the absolute difference between sitting and standing for each.

RESULTS

A 2 x 3 (group x phase) repeated-measures analysis of variance revealed significant interactions for sitting High Frequency (HF) norm, sitting Low Frequency (LF) norm, the difference between sitting and standing HF norm, and difference between sitting and standing LF norm. Acutely, athletes with concussion displayed increased LF norm and decreased HF norm while sitting and a decreased change in their HF and LF norm measures between sitting and standing. A significant group effect for sample entropy when standing was detected, with the concussed group displaying decreased values compared with the matched controls.

CONCLUSIONS

Athletes with concussion displayed autonomic dysfunction in some measures of HRV that persisted beyond RTP and were related to a previous history of concussion.

Monitoring training status with HR measures: do all roads lead to Rome?

Measures of resting, exercise, and recovery heart rate are receiving increasing interest for monitoring fatigue, fitness and endurance performance responses, which has direct implications for adjusting training load (1) daily during specific training blocks and (2) throughout the competitive season. However, these measures are still not widely implemented to monitor athletes' responses to training load, probably because of apparent contradictory findings in the literature. In this review I contend that most of the contradictory findings are related to methodological inconsistencies and/or misinterpretation of the data rather than to limitations of heart rate measures to accurately inform on training status. I also provide evidence that measures derived from 5-min (almost daily) recordings of resting (indices capturing beat-to-beat changes in heart rate, reflecting cardiac parasympathetic activity) and submaximal exercise (30- to 60-s average) heart rate are likely the most useful monitoring tools. For appropriate interpretation at the individual level, changes in a given measure should be interpreted by taking into account the error of measurement and the smallest important change of the measure, as well as the training context (training phase, load, and intensity distribution). The decision to use a given measure should be based upon the level of information that is required by the athlete, the marker's sensitivity to changes in training status and the practical constrains required for the measurements. However, measures of heart rate cannot inform on all aspects of wellness, fatigue, and performance, so their use in combination with daily training logs, psychometric questionnaires and non-invasive, cost-effective performance tests such as a countermovement jump may offer a complete solution to monitor training status in athletes participating in aerobic-oriented sports.