Uncovering Bioelectric Signatures: Multimodal Wearable Electrophysiology and ECG-Based HRV for Early Breast Cancer Detection and Follow-Up

Breast cancer (BC), affecting 2.3 million women annually, requires early detection and effective follow-up to achieve >90% survival rates. Current modalities (mammography: 1000 mm³, MRI: 4.2 mm³) struggle with micro-tumors and dense breasts. This work presents a smart bra integrating electrical impedance spectroscopy (EIS) and electrocardiography (ECG)-based heart rate variability (HRV) to detect tumors as small as 0.1–0.5 mm³ (~1–5 × 10⁴ cells) and monitor relapse and cardiotoxicity every 3 months post-diagnosis. The device uses 24 MNP-coated silver-nylon electrodes, a 3-lead ECG sensor (AD8232), a high-precision impedance analyzer (10 kHz–1 MHz), and multimodal sensing (EIS, temperature, HRV). A hybrid LSTM-XGBoost model with space-time attention and GAN augmentation achieves >90% sensitivity and >85% specificity. EIS detects electric fields of 18.9 mV/m (0.1 mm³, superficial), 50 mV/m (0.5 mm³, superficial), and 41.7 mV/m (0.5 mm³, deep). ECG-based HRV (SDNN < 50 ms, RMSSD < 20 ms) predicts relapse (AUC = 0.80 with CEA) and cardiotoxicity (OR = 2.7). Tumor location statistics (60–70% upper-outer quadrant, 10–15% superficial) inform electrode placement. A patient trial will validate performance against mammography, ultrasound, clinical ECG, and CEA, targeting FDA 510(k) clearance. This multimodal wearable promises transformative early detection and longitudinal monitoring.