Abstract Background Flexible and wearable electronic devices with lightweight are needed to monitor and guide treatment in patients with cardiovascular disease and diabetic complication. We aimed to develop self-powered wearable bio-signal sensing arrays for cardiovascular and diabetic complication diagnosis and continuous monitoring. Methods Ferroelectric composites were designed to have piezoelectric property and high flexibility. Detection of arterial pulse as ballistogram (BCG) was simultaneously compared with electrocardiogram (ECG) in 20 controls. Heart rate and components of ECG was compared with those of BCG. Then, 9 ferroelectric BCG sensors as a square type array with self-power generation were fabricated to attachable thin film. Pressure distribution with BCG sensor array attached to socks were compared between 20 controls and 20 patients with diabetic neuropathy or vasculopathy during standing and ambulation for gait pressure distribution. Pressure distribution pattern was compared to neuropathy and vasculopathy parameters. Results Heart rate between BCG and ECG was significantly correlated (interclass correlation coefficient, ICC 0.99, 95% CI 0.98-0.99, p<0.001). QRS and T wave in ECG were correlated to second and third wave in BCG. Radial artery augmentation index by blood pressure monitoring was significantly correlated to BCG pressure (ICC 0.76, 95% CI 0.38-0.90, p=0.002). Analysis of foot pressure distribution demonstrated the highest pressure point at the anterolateral plantar area below a little tow. However, pressure gradient between anterolateral and anteromedial plantar area in diabetic patients was greater than that in controls (42.3±10.2 mV vs. 31.2±8.5 mV, p=0.024). Pressure gradient in diabetic patients was correlated to ankle-brachial index (ICC 0.62, 95% CI 0.32-0.90, p=0.036), but not to neuropathy parameters. Conclusion Wearable BCG sensor could accurately detect heart rate, blood pressure index and significantly correlated to ABI. Pressure distribution pattern and gradient analysis in diabetic patients by wearable BCG sensor arrays might predict diabetic complications. Gait remedial training guided by wearable BCG sensor arrays might aid to prevent diabetic complications.