A Noisy Beat is Worth 16 Words: a Tiny Transformer for Low-Power Arrhythmia Classification on Microcontrollers

arXiv:2402.10748v1 Announce Type: cross
Abstract: Wearable systems for the long-term monitoring of cardiovascular diseases are becoming widespread and valuable assets in diagnosis and therapy. A promising approach for real-time analysis of the electrocardiographic (ECG) signal and the detection of heart conditions, such as arrhythmia, is represented by the transformer machine learning model. Transformers are powerful models for the classification of time series, although efficient implementation in the wearable domain raises significant design challenges, to combine adequate accuracy and a suitable …

abstract analysis arxiv classification cs.hc cs.lg detection diagnosis diseases eess.sp long-term low microcontrollers monitoring power real-time signal systems therapy transformer type wearable words