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Objective: Sympathetic nervous system activity (SNSA) can rapidly modulate arterial stiffness, thus making it an important biomarker for SNSA evaluation. Pulse wave velocity (PWV) is a well-known quantitative indicator of arterial stiffness, but its functional responsivity to SNSA has not been elucidated. This paper reports a method to estimate rapid changes in peripheral arterial stiffness induced by SNSA using local PWV (LPWV) and to further quantify SNSA based on the estimated stiffness. Methods: LPWV was measured from the artery near the wrist to the artery near the forefinger using a biodegradable piezoelectric sensor and a photoplethysmography sensor in an electrocutaneous stimulus experiment in which pain evokes the SNSA. The relationship between LPWV, simultaneously measured peripheral arterial stiffness index, and self-reported pain intensity was quantified. Results: The stiffness estimated by LPWV alone and the stiffness estimated by LPWV and arterial pressure both approximate the peripheral arterial stiffness index (R2 = 0.9775 and 0.9719). Pain intensity can be quantitatively evaluated in a sigmoidal relationship by either the estimated stiffness based on LPWV alone (r = 0.8594) or the estimated stiffness based on LPWV and arterial pressure (r = 0.9738). Conclusion: Our results demonstrated the validity of LPWV in the quantitative evaluation of SNSA and the optionality of blood pressure correction depending on application scenarios. Significance: This study advances the understanding of sympathetic innervation of peripheral arteries through the sympathetic responsivity of LPWV and contributes a quantitative biomarker for SNSA evaluation. [ABSTRACT FROM AUTHOR]

Respiration can modulate the cardiovascular system through the autonomic nervous system (ANS), deriving numerous methods for monitoring respiration based on cardiovascular biomarkers. However, the sensitivity of the ANS to environmental changes can negatively affect these methods, which suggests the necessity to evaluate their performance in estimating respiratory rate (RR). This paper aims to propose a method for robust estimation of RR using a biodegradable piezoelectric sensor by analyzing the robustness differences of these biomarkers under pain stimulation. In an electrocutaneous stimulus experiment conducted with 15 participants, arterial pulse waves near the elbow and wrist were measured, as well as the electrocardiogram and fingertip photoplethysmogram. The robustness of six biomarkers was quantified using respiratory quality index (RQI) and mean absolute percentage error (MAPE). Heart rate derived from the arterial pulse wave near the elbow achieves the best robustness (RQI $=85.67$ ±12.84 %, MAPE $=2.22$ ±1.81 %) of all biomarkers, whereas pulse wave velocity (PWV) from the elbow to the wrist performs best (RQI $=70.39$ ±12.15 %, MAPE $=3.47$ ±1.69 %) of the three biomarkers of PWV. Therefore, the robustness of biomarkers varies, as does the same biomarker measured at different sites. Our results reveal the heterogeneity of respiratory modulation on the cardiovascular system and demonstrate the robustness of the biomarkers of the arterial pulse wave near the elbow in estimating RR. This study can help smart wearables perfect respiratory monitoring and contribute a robust method for respiratory monitoring using a biodegradable piezoelectric sensor. [ABSTRACT FROM AUTHOR]