Methodological improvements in heart rate variability

Abstract

Heart rate variability (HRV) refers to the amplitude and period of fluctuations in the heart rate over time. HRV is an accessible, low-cost and straightforward technique for measuring autonomic outflow, but also a complicated epiphenomena of interacting autonomic, circulatory and respiratory factors. Confusion about the meaning of HRV is reflected in the literature establishing basic HRV theory, and in the applied literature which uses HRV as a dependent variable or predictor of psychological outcomes. Here, 2 straightforward issues present themselves: 1) best-case practice for methodological implementation is not being followed, and 2) sample sizes for between-subjects investigations of phenomena where HRV is a dependent variable are underpowered. Specifically addressing the above; 1) an attempt is made to a) understand and codify a best-case practice for methodological control in biobehavioural research, and b) investigate profound but common sources of error in HRV recording; 2) rationale for the development and field testing of a device which allows mass collection of HRV records from experimental participants is outlined. Best-case practice for experimental implementation is recommended: the use of within-subjects data, the consideration of the nature of ‘baseline’ periods against which experimental conditions are compared, and respiratory monitoring within participants to control for occasional or whole-sample artifacts. Current research is not well controlled – theoretical, statistical and practical errors are widely observed. For addressing experimental power, pulse monitoring shows acceptable reliability over time, and the device developed (a smartphone-based pulse rate monitor) shows excellent accuracy in comparison to conventional measurement. A novel solution for correcting pulse to pulse intervals is offered which improves measurement accuracy and performs well in field trials of mass-collected data.