Abstract
Cuffless and non-invasive blood pressure (BP) monitoring remains challenging because cuff-based devices are bulky and prone to "white-coat syndrome", while optical photoplethysmography (PPG) is sensitive to skin tone. Electrocardiography (ECG) reflects cardiac electrical activity, and bioimpedance (BioZ) captures hemodynamic changes; their combination is promising for reliable cuffless BP estimation, especially in wearable form factors such as smart rings. However, no prior work has integrated ECG and BioZ into a finger ring, and existing dual-signal systems still lack the hardware optimization and signal consistency validation required for subsequent BP modeling. This study addresses these gaps with a finger-ring-based solution, laying the technical groundwork for cuffless BP monitoring. Methods: We designed a high anti-interference ECG circuit, optimized three BioZ electrode modes and 12 carrier frequencies (10kHz-1MHz), fabricated a 3D-printed ECG-BioZ integrated ring, and developed a signal-processing workflow including multi-stage filtering, optimal phase angle selection, and 3D visualization. Results: Based on a comprehensive parameter sweep on a pilot subject, Mode L1 (artery-aligned electrodes) with 50kHz was identified as the optimal configuration (SQI 88.3%, main frequency significance 26.9dB). Subsequent validation on a diverse cohort of 11 subjects confirmed that this configuration yields consistent BioZ and ECG synchronization (Pearson r=0.912, p<0.001). In the pilot BP estimation study (N = 11), the system achieved a Mean Absolute Error (MAE) of 6.56 mmHg for Systolic BP and 4.97 mmHg for Diastolic BP using a transfer-learning-based KAN model. Notably, the dual-signal integration reduced SBP error by 2.31 mmHg compared to ECG-only approaches. Conclusions: This work establishes a finger-ring-based ECG-BioZ dual-signal framework, completes system-level hardware optimization and workflow refinement, and validates cross-signal temporal consistency. It lays a solid technical foundation for subsequent development of BP estimation models integrating cardiac electrical activity and hemodynamic changes, advancing non-invasive multi-parameter physiological monitoring toward consumer applications.