Effects of Strength Training on Blood Pressure and Heart Rate Variability—A Systematic Review

AbstractHeart rate variability (HRV) utilizes the electrocardiogram (ECG) and has been widely studied as a non-invasive indicator of cardiac autonomic activity. Pulse rate variability (PRV) utilizes photoplethysmography (PPG) and recently has been used as a surrogate for HRV. Several studies have found that PRV is not entirely valid as an estimation of HRV and that several physiological factors, including the pulse transit time (PTT) and blood pressure (BP) changes, may affect PRV differently than HRV. This study aimed to assess the relationship between PRV and HRV under different BP states: hypotension, normotension, and hypertension. Using the MIMIC III database, 5 min segments of PPG and ECG signals were used to extract PRV and HRV, respectively. Several time-domain, frequency-domain, and nonlinear indices were obtained from these signals. Bland–Altman analysis, correlation analysis, and Friedman rank sum tests were used to compare HRV and PRV in each state, and PRV and HRV indices were compared among BP states using Kruskal–Wallis tests. The findings indicated that there were differences between PRV and HRV, especially in short-term and nonlinear indices, and although PRV and HRV were altered in a similar manner when there was a change in BP, PRV seemed to be more sensitive to these changes.

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A preliminary systematic review and meta-analysis on the effects of heart rate variability biofeedback on heart rate variability and respiration of athletes

Journal of Complementary and Integrative Medicine ◽

10.1515/jcim-2020-0528 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Jeffrey Cayaban Pagaduan ◽

Yung-Sheng Chen ◽

James William Fell ◽

Sam Shi Xuan Wu

Keyword(s):

Systematic Review ◽

Heart Rate ◽

Heart Rate Variability ◽

Web Of Science ◽

Meta Analysis ◽

Academic Research ◽

Experimental Studies ◽

Quantitative Review ◽

Heart Rate Variability Biofeedback ◽

Randomized Control

Abstract To date, there is no quantitative review examining the influence of heart rate variability biofeedback (HRV BFB) on the athlete population. Such an undertaking may provide valuable information on the autonomic and respiration responses of athletes when performing HRV BFB. Thus, purpose of this preliminary systematic review and meta-analysis on the effects of HRV BFB on HRV and respiration of athletes. Searches of Springerlink, SportDiscus, Web of Science, PROQUEST Academic Research Library, Google Scholar, and ScienceDirect were conducted for studies that met the following criteria: (1) experimental studies involving athletes that underwent randomized control trial; (2) availability of HRV BFB as a treatment compared with a control (CON)/placebo (PLA); (3) any pre and post HRV variable and/or breathing frequency as dependent variable/s; and, (4) peer-reviewed articles written in English. Four out of 660 studies involving 115 athletes (25 females and 90 males) ages 16–30 years old were assessed in this review. Preliminary findings suggest the promising ability of HRV BFB to improve respiratory mechanics in athlete population. More work is needed to determine the autonomic modulatory effect of HRV BFB in athletes.

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Smart Devices and Wearable Technologies to Detect and Monitor Mental Health Conditions and Stress: A Systematic Review

Sensors ◽

10.3390/s21103461 ◽

2021 ◽

Vol 21 (10) ◽

pp. 3461

Author(s):

Blake Anthony Hickey ◽

Taryn Chalmers ◽

Phillip Newton ◽

Chin-Teng Lin ◽

David Sibbritt ◽

...

Keyword(s):

Mental Health ◽

Systematic Review ◽

Heart Rate ◽

Heart Rate Variability ◽

Electrodermal Activity ◽

Smart Devices ◽

Stress Detection ◽

Wearable Technologies ◽

Detection Of Stress ◽

Anxiety Depression

Recently, there has been an increase in the production of devices to monitor mental health and stress as means for expediting detection, and subsequent management of these conditions. The objective of this review is to identify and critically appraise the most recent smart devices and wearable technologies used to identify depression, anxiety, and stress, and the physiological process(es) linked to their detection. The MEDLINE, CINAHL, Cochrane Central, and PsycINFO databases were used to identify studies which utilised smart devices and wearable technologies to detect or monitor anxiety, depression, or stress. The included articles that assessed stress and anxiety unanimously used heart rate variability (HRV) parameters for detection of anxiety and stress, with the latter better detected by HRV and electroencephalogram (EGG) together. Electrodermal activity was used in recent studies, with high accuracy for stress detection; however, with questionable reliability. Depression was found to be largely detected using specific EEG signatures; however, devices detecting depression using EEG are not currently available on the market. This systematic review highlights that average heart rate used by many commercially available smart devices is not as accurate in the detection of stress and anxiety compared with heart rate variability, electrodermal activity, and possibly respiratory rate.

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