Time-varying analysis of electrodermal activity during exercise

Abstract

The electrodermal activity (EDA) is a useful tool for assessing skin sympathetic nervous activity. Using spectral analysis of EDA data at rest, we have previously found that the spectral band which is the most sensitive to central sympathetic control is largely confined to 0.045 to 0.25 Hz. However, the frequency band associated with sympathetic control in EDA has not been studied for exercise conditions. Establishing the band limits more precisely is important to ensure the accuracy and sensitivity of the technique. As exercise intensity increases, it is intuitive that the frequencies associated with the autonomic dynamics should also increase accordingly. Hence, the aim of this study was to examine the appropriate frequency band associated with the sympathetic nervous system in the EDA signal during exercise. Eighteen healthy subjects underwent a sub-maximal exercise test, including a resting period, walking, and running, until achieving 85% of maximum heart rate. Both EDA and ECG data were measured simultaneously for all subjects. The ECG was used to monitor subjects’ instantaneous heart rate, which was used to set the experiment’s end point. We found that the upper bound of the frequency band (Fmax) containing the EDA spectral power significantly shifted to higher frequencies when subjects underwent prolonged low-intensity (Fmax ~ 0.28) and vigorous-intensity exercise (Fmax ~ 0.37 Hz) when compared to the resting condition. In summary, we have found shifting of the sympathetic dynamics to higher frequencies in the EDA signal when subjects undergo physical activity.

Innovations in Electrodermal Activity Data Collection and Signal Processing: A Systematic Review

“…The spectral content of EDA is mostly confined to 0.045-0.15 Hz [21]. Exercise increases the spectral content of EDA, exhibiting spectral content at about 0.37 Hz when subjects perform vigorous-intensity exercise [22].…”

“…The new index of sympathetic control (termed TVSymp), incorporating the components between 0.08 and 0.24 Hz, was found to be highly sensitive to orthostatic, cognitive, and physical stress, exhibiting a higher between-subject consistency than did other measures of EDA, including SCL, NSSCRs, and EDASymp. The change in the high boundary of the spectral band containing the power of EDA under physical activity was explored in a further study [22]. The evidence suggested that the boundary is about 0.37 Hz under vigorous-intensity exercise.…”

Evaluating Urban Bicycle Infrastructures through Intersubjectivity of Stress Sensations Derived from Physiological Measurements

“…In general, future work should investigate the accuracy of skin conductance decomposition into tonic and phasic signals under non-laboratory conditions, especially during physical exercise and on how MOS can be reliably detected under these circumstances. An interesting starting point can be the work by Posada-Quintero et al [49], still utilising a controlled laboratory setting with constant temperature, humidity, and low risk of motion artefacts for analysis of the effects of physical exercise on EDA. The importance of considering these influences is underlined e.g., by the results of a study on stress monitoring in real life situations by Gjoreski et al [50].…”

Fundamentals, Recent Advances, and Future Challenges in Bioimpedance Devices for Healthcare Applications

“…Sparse recovery based on the orthogonal matching pursuit algorithm has been applied in [329] to separate skin conductance response from artifacts with a high accuracy. For the analysis of EDA signals and identification of arousals, the methods range from power spectral density analysis [330,331], machine learning [332], compressed sensing [333], to nonlinear analysis based on chaotic characterization and complexity assessment [334]. EDA sensors can be based on Ag/AgCl disc electrodes attached to the palm sides of index and middle fingers, such as the prototype reported in [335], or multilayered sensor disc for use as a dry electrode [336].…”