Non-Invasive Assessment of Dynamic Cerebral Blood Flow Using Near-Field Coupling and Synchronized Electrocardiography

Dynamic assessment of cerebral blood flow (CBF) is crucial for the prevention and treatment of cerebrovascular diseases. Near-field coupling (NFC), due to its non-invasive and continuous advantages, holds significant promise in the dynamic assessment of CBF compared to traditional detection methods. However, challenges related to individual differences persist. This study integrates electrocardiographic signal with NFC to explore the feasibility of reflecting diverse individual CBF change patterns. Ten healthy volunteers were selected to undergo continuous monitoring and analysis of ECG and CBF signals in both supine rest and a 30° tilted position. Using heart rate variability (HRV) as a reference, the CBF signal feature patterns before and after tilt were analyzed. Finally, two distinct groups with different regulatory capabilities were identified based on CBF features. The results indicate that after positional changes, short-term HRV increased in all volunteers, followed by the manifestation of three different change patterns. CBF features revealed two change patterns: increase and decrease. Different patterns were associated with the main mechanisms of CBF regulation and the degree of cardiac pulsation changes. Furthermore, the significance levels for distinguishing the two groups based on the two CBF features were less than 0.05 and 0.01, respectively. NFC technology shows potential in discriminating dynamic changes in CBF among different individuals.