Time-Frequency Analysis and Multimodal Sparse Alignment of Physiological Signals in WBAN

Wireless body area networks (WBANs) integrate wearable/implantable sensors to continuously monitor health conditions and transmit data to the cloud for real-time analysis via wireless communication. This study proposes Heart rate timefrequency synchronization analysis (HR-sync) atoms to analyze the time-frequency correlation between multimodal signals transmitted by WBAN; and creates a multimodal framework that can evaluate signal alignment and solve misalignment problems, sparsely representing them. This approach optimizes bandwidth utilization, enhances cross-correlation, and improves transmission efficiency without compromising accuracy.