arXiv:2607. 14747v1 Announce Type: cross Abstract: Cardiovascular diseases are the leading cause of death worldwide, and conditions such as arrhythmia often require long-term monitoring for effective detection and diagnosis.
By Floriaan Bulten, Yawar Rasheed, Arlene John, Vincenzo Stoico, Ghayoor Gillani
arXiv:2607. 09680v1 Announce Type: cross Abstract: Continuous cardiac monitoring in wearable devices demands classifiers that are simultaneously accurate, energy-efficient, and deployable on resource-constrained hardware.
By Anh Tran, Khanh Tran, Cuong Do
arXiv:2508. 11664v2 Announce Type: replace-cross Abstract: Sleep stage classification is critical for diagnosing and managing disorders like sleep apnea and insomnia.
By Zahra Mohammadi, Parnian Fazel, Siamak Mohammadi
arXiv:2510. 18668v4 Announce Type: replace Abstract: Wearable cardiovascular sensor patches promise continuous, unobtrusive monitoring, but their tight energy, memory, and compute budgets make it unclear whether physiological signals should be analyzed on the device or streamed to the cloud for processing.
By Mustafa Fuad Rifet Ibrahim, Tunc Alkanat, Felix Manthey, Maurice Meijer, Alexander Schlaefer, Peer Stelldinger
arXiv:2606. 02256v1 Announce Type: new Abstract: Our work presents a method for ECG segmentation and arrhythmia detection using Tiny Machine Learning (TinyML) models for real-time, on-device inference on resource-constrained embedded systems.
By Nagarajan S, Kurian Polachan
arXiv:2504. 03772v3 Announce Type: replace-cross Abstract: Respiratory diseases account for a significant portion of global mortality.
By Anton Lambrecht, Stijn Luchie, Jaron Fontaine, Ben Van Herbruggen, Adnan Shahid, Eli De Poorter