Beat-to-Beat Estimation of Peripheral Arterial Stiffness From Local PWV for Quantitative Evaluation of Sympathetic Nervous System Activity.

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.

Pressure-based Detection of Heart and Respiratory Rates from Human Body Surface using a Biodegradable Piezoelectric Sensor.

This study investigates the relationship between respiration and autonomic nervous system (ANS) activity and proposes a parallel detection method that can simultaneously extract the heart rate (HR) and respiration rate (RR) from different pulse waves measured using a novel biodegradable piezoelectric sensor. The synchronous changes in heart rate variability and respiration reveal the interaction between respiration and the cardiovascular system and their interconnection with ANS activity. Following this principle, respiration was extracted from the HR calculated beat-by-beat from pulse waves. Pulse waves were measured using multiple biodegradable piezoelectric sensors each attached to the human body surface. The Valsalva maneuver experiment was conducted on seven healthy young adults, and the extracted respiratory wave was compared with a reference respiratory wave measured simultaneously. The experimental results are consistent with the observations from reference waves, where R2 = 0.9506, p < 0.001 for the extracted RR and the reference RR, thus demonstrating the detection capability under different respiratory statuses.

A Wearable Finger-Tapping Motion Recognition System Using Biodegradable Piezoelectric Film Sensors.

In this paper, we aimed to develop a method for the automatic recognition of individual finger-tapping motion. Biodegradable piezoelectric film sensors were attached to the skin of a forearm near the wrist (16 channels) to measure small movements of the tendons during five-finger tapping. In the proposed method, the segments in which motion occurred were detected by calculating the total activity for all channels. A neural network is trained to classify tapping motion using the extracted data based on the total activity, thereby allowing the accurate classification of flexion/extension of each finger. We collected experimental data from five healthy young adults to verify the motion recognition accuracy of the proposed method. The results revealed that the proposed method can recognize five-finger tapping motions with high accuracy (flexion/extension of each finger: 92.0%; time-series tapping motion: 88.4%).