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Despite the\u00a0numerous automated RR estimation approaches proposed in the literature, challenges persist in accurately estimating RR in noisy environments, typical of real-life situations. This becomes especially critical when periodic noise patterns interfere with the target signal. In this study, we present a parallel driver designed to address the challenges of RR estimation in real-world environments, combining multi-core architectures with parallel and high-performance techniques. The proposed system employs a nonnegative matrix factorization (NMF) approach to mitigate the impact of noise interference in the input signal. This NMF approach is guided by pre-trained bases of respiratory sounds and incorporates an orthogonal constraint to enhance accuracy. The proposed solution is tailored for real-time processing on low-power hardware. Experimental results across various scenarios demonstrate promising outcomes in terms of accuracy and computational efficiency.<\/jats:p>","DOI":"10.1007\/s11227-024-06411-3","type":"journal-article","created":{"date-parts":[[2024,8,30]],"date-time":"2024-08-30T04:02:27Z","timestamp":1724990547000},"page":"26922-26941","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Noise-tolerant NMF-based parallel algorithm for respiratory rate estimation"],"prefix":"10.1007","volume":"80","author":[{"given":"Pablo","family":"Revuelta-Sanz","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Antonio J.","family":"Mu\u00f1oz-Montoro","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Juan","family":"Torre-Cruz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francisco J.","family":"Canadas-Quesada","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jos\u00e9","family":"Ranilla","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,8,30]]},"reference":[{"key":"6411_CR1","unstructured":"Torabi Y, Shirani S, Reilly JP (2023) A new non-negative matrix factorization approach for blind source separation of cardiovascular and respiratory sound based on the periodicity of heart and lung function. 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