AI RESEARCH
BioTrain: Sub-MB, Sub-50mW On-Device Fine-Tuning for Edge-AI on Biosignals
arXiv CS.LG
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ArXi:2604.13359v1 Announce Type: new Biosignals exhibit substantial cross-subject and cross-session variability, inducing severe domain shifts that degrade post-deployment performance for small, edge-oriented AI models. On-device adaptation is therefore essential to both preserve user privacy and ensure system reliability. However, existing sub-100 mW MCU-based wearable platforms can only shallow or sparse adaptation schemes due to the prohibitive memory footprint and computational cost of full backpropagation (BP