arXiv AI July 31, 2026 By Mathieu Cherpitel, Janne Luijten, Thomas B\"ack, Camiel Verhamme, Martijn Tannemaat, Anna V. Kononova

How does downsampling affect needle electromyography signals? A generalisable workflow for understanding downsampling effects on high-frequency time series

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arXiv:2601. 10191v2 Announce Type: replace Abstract: Automated analysis of needle electromyography (nEMG) signals is emerging as a tool to support the detection of neuromuscular diseases (NMDs), yet the signals' high and heterogeneous sampling rates pose substantial computational challenges for feature-based machine-learning models, particularly for near real-time analysis.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

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