This talk will explore the cutting-edge advancements in EdgeAI for biosignal analysis, focusing on innovative algorithms such as Spiking Neural Networks (SNNs), Transformers, and Autoencoders. As the demand for real-time, near-sensor processing of biosignals like EEG, ECG, and EMG continues to grow, traditional cloud-based methods face challenges related to latency, energy efficiency, and data privacy. We will discuss how SNNs, with their neuromorphic efficiency, Transformers, with their powerful sequence modelling, and Autoencoders, with their capacity for anomaly spotting, are being adapted for edge deployment. The talk will highlight real-world applications inside and outside the wearable healthcare domain, demonstrating how these technologies enable fast, accurate, and energy-efficient processing at the edge.