{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,2]],"date-time":"2026-05-02T03:57:15Z","timestamp":1777694235589,"version":"3.51.4"},"reference-count":56,"publisher":"SAGE Publications","issue":"1","license":[{"start":{"date-parts":[[2022,11,24]],"date-time":"2022-11-24T00:00:00Z","timestamp":1669248000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["ICA"],"published-print":{"date-parts":[[2022,11,24]]},"abstract":"<jats:p>In this paper, a noninvasive portable prototype is presented for biomedical audio signal processing. The proposed prototype is suitable for monitoring the health of patients. The proposed hardware setup consists of a cost-effective microphone, multipurpose microcontroller and computing node that could be a mobile phone or general-purpose computer. Using parallel and high-performance techniques, this setup allows one to register and wirelessly multicast the recorded biomedical signals to computing nodes in real time. The developed prototype was used as a case study to estimate the heart rate (HR) from the captured biomedical audio signal. In this regard, the developed algorithm for estimating HR comprises three stages: preprocessing, separation, and HR estimation. In the first stage, the signal captured by the microphone is adapted for processing. Subsequently, a separation stage was proposed to alleviate the acoustic interference between the lungs and heart. The separation is performed by combining a non-negative matrix factorization algorithm, clustering approach, and soft-filter strategy. Finally, HR estimation was obtained using a novel and efficient method based on the autocorrelation function. The developed prototype could be used not only for the estimation of the HR, but also for the retrieval of other biomedical information related to the recording of cardiac or respiratory audio signals. The proposed method was evaluated using well-known datasets and compared with state-of-the-art algorithms for source-separation. The results showed that it is possible to obtain an accurate separation and reliable real-time estimation in terms of source separation metrics and relative error in the tested scenarios by combining multi-core architectures with parallel and high-performance techniques. Finally, the proposed prototype was validated in a real-world scenario.<\/jats:p>","DOI":"10.3233\/ica-220686","type":"journal-article","created":{"date-parts":[[2022,7,5]],"date-time":"2022-07-05T11:18:50Z","timestamp":1657019930000},"page":"1-18","source":"Crossref","is-referenced-by-count":8,"title":["A system for biomedical audio signal processing based on high performance computing techniques"],"prefix":"10.1177","volume":"30","author":[{"given":"Antonio Jes\u00fas","family":"Mu\u00f1oz-Montoro","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pablo","family":"Revuelta-Sanz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alberto","family":"Villal\u00f3n-Fern\u00e1ndez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rub\u00e9n","family":"Mu\u00f1iz","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jos\u00e9","family":"Ranilla","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","reference":[{"issue":"4","key":"10.3233\/ICA-220686_ref1","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1016\/j.compbiomed.2011.02.002","article-title":"HeartSaver: A mobile cardiac monitoring system for auto-detection of atrial fibrillation, myocardial infarction, and atrio-ventricular block","volume":"41","author":"Sankari","year":"2011","journal-title":"Computers in Biology and Medicine"},{"key":"10.3233\/ICA-220686_ref2","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.neulet.2018.12.015","article-title":"Visibility graph analysis of speech evoked auditory brainstem response in persistent developmental stuttering","volume":"696","author":"Mozaffarilegha","year":"2019","journal-title":"Neuroscience Letters"},{"key":"10.3233\/ICA-220686_ref3","doi-asserted-by":"crossref","unstructured":"Mond\u00e9jar-Guerra V, Novo J, Rouco J, Penedo MG, Ortega M. Heartbeat classification fusing temporal and morphological information of ECGs via ensemble of classifiers. Biomedical Signal Processing and Control. 2019; 47: 41-8.","DOI":"10.1016\/j.bspc.2018.08.007"},{"issue":"6","key":"10.3233\/ICA-220686_ref4","doi-asserted-by":"crossref","first-page":"639","DOI":"10.1177\/1073858414549015","article-title":"Brain \u2013 computer interface after nervous system injury","volume":"20","author":"Burns","year":"2014","journal-title":"The Neuroscientist"},{"issue":"10","key":"10.3233\/ICA-220686_ref5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s10916-020-01639-x","article-title":"Upper limb movement classification via electromyographic signals and an enhanced probabilistic network","volume":"44","author":"Burns","year":"2020","journal-title":"Journal of Medical Systems"},{"issue":"3","key":"10.3233\/ICA-220686_ref6","doi-asserted-by":"crossref","first-page":"3581","DOI":"10.3233\/JIFS-181339","article-title":"A two stage recognition method of lung sounds based on multiple features","volume":"37","author":"Shi","year":"2019","journal-title":"Journal of Intelligent and Fuzzy Systems"},{"issue":"4","key":"10.3233\/ICA-220686_ref7","doi-asserted-by":"crossref","first-page":"401","DOI":"10.3233\/ICA-160517","article-title":"Automatic atrium contour tracking in ultrasound imaging","volume":"23","author":"Hsu","year":"2016","journal-title":"Integrated Computer-Aided Engineering"},{"key":"10.3233\/ICA-220686_ref8","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.future.2016.01.010","article-title":"Towards heart sound classification without segmentation via autocorrelation feature and diffusion maps","volume":"60","author":"Deng","year":"2016","journal-title":"Future Generation Computer Systems"},{"key":"10.3233\/ICA-220686_ref9","doi-asserted-by":"crossref","unstructured":"Dia N, Fontecave-Jallon J, Gum\u00e9ry PY, Rivet B. Heart rate estimation from phonocardiogram signals using non-negative matrix factorization. In: ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE; 2019. pp. 1293-7.","DOI":"10.1109\/ICASSP.2019.8682343"},{"key":"10.3233\/ICA-220686_ref10","first-page":"1","article-title":"A method for balancing a multi-labeled biomedical dataset","author":"Mukhin","year":"2022","journal-title":"Integrated Computer-Aided Engineering"},{"issue":"4","key":"10.3233\/ICA-220686_ref11","doi-asserted-by":"crossref","first-page":"770","DOI":"10.1016\/j.jpeds.2012.07.001","article-title":"Heart rate predicts sepsis","volume":"161","author":"Cuestas","year":"2012","journal-title":"Journal of Pediatrics"},{"issue":"3","key":"10.3233\/ICA-220686_ref12","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1097\/00000542-200603000-00022","article-title":"Heart rate variability predicts severe hypotension after spinal anesthesia","volume":"104","author":"Hanss","year":"2006","journal-title":"Anesthesiology"},{"issue":"11","key":"10.3233\/ICA-220686_ref13","doi-asserted-by":"crossref","first-page":"1189","DOI":"10.1111\/j.1540-8159.2005.50186.x","article-title":"Abnormal heart rate turbulence predicts the initiation of ventricular arrhythmias","volume":"28","author":"Iwasa","year":"2005","journal-title":"Pace-Pacing and Clinical Electrophysiology"},{"issue":"1","key":"10.3233\/ICA-220686_ref14","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/S0002-9378(87)80362-9","article-title":"Heart rate variation and movement incidence in growth-retarded fetuses: the significance of antenatal late heart rate decelerations","volume":"157","author":"Bekedam","year":"1987","journal-title":"American Journal of Obstetrics and Gynecology"},{"key":"10.3233\/ICA-220686_ref15","unstructured":"Hynynen K, Noksokoivisto V, Mattila M, Patomaki L. Heart-rate variation as indicator of depth of anesthesia. vol.\u00a025; 1980."},{"issue":"5","key":"10.3233\/ICA-220686_ref16","doi-asserted-by":"crossref","first-page":"917","DOI":"10.1111\/j.1528-1167.2006.00961.x","article-title":"Circadian variation in heart-rate variability in localization-related epilepsy","volume":"48","author":"Persson","year":"2007","journal-title":"Epilepsia"},{"issue":"8","key":"10.3233\/ICA-220686_ref17","doi-asserted-by":"crossref","first-page":"705","DOI":"10.1111\/j.1464-5491.1990.tb01474.x","article-title":"Spectral analysis of spontaneous heart rate variation in diabetic patients","volume":"7","author":"Lanting","year":"1990","journal-title":"Diabetic Medicine"},{"issue":"3","key":"10.3233\/ICA-220686_ref18","first-page":"641","article-title":"Variation in heart rate during submaximal exercise: Implications for monitoring training","volume":"18","author":"Lamberts","year":"2004","journal-title":"Journal of Strength and Conditioning Research"},{"issue":"6","key":"10.3233\/ICA-220686_ref19","first-page":"415","article-title":"Factors of variation of heart rate","volume":"47","author":"Siche","year":"1998","journal-title":"Annales De Cardiologie Et D Angeiologie"},{"key":"10.3233\/ICA-220686_ref20","doi-asserted-by":"crossref","first-page":"10","DOI":"10.4103\/1817-1737.165311","article-title":"Auscultation of the respiratory system \u2013 Some additional points","volume":"10","author":"Ray","year":"2015","journal-title":"Annals of Thoracic Medicine"},{"issue":"2","key":"10.3233\/ICA-220686_ref21","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1152\/jappl.1981.50.2.307","article-title":"Spectral characteristics of normal breath sounds","volume":"50","author":"Gavriely","year":"1981","journal-title":"Journal of Applied Physiology"},{"issue":"4","key":"10.3233\/ICA-220686_ref22","doi-asserted-by":"crossref","first-page":"1120","DOI":"10.1152\/jappl.1983.55.4.1120","article-title":"An accurate recording system and its use in breath sounds spectral analysis","volume":"55","author":"Charbonneau","year":"1983","journal-title":"Journal of Applied Physiology"},{"key":"10.3233\/ICA-220686_ref23","doi-asserted-by":"crossref","unstructured":"Hossain I, Moussavi Z. An overview of heart-noise reduction of lung sound using wavelet transform based filter. In: Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No. 03CH37439). vol.\u00a01. IEEE; 2003. pp. 458-61.","DOI":"10.1109\/IEMBS.2003.1279719"},{"issue":"9","key":"10.3233\/ICA-220686_ref24","doi-asserted-by":"crossref","first-page":"2383","DOI":"10.1109\/TBME.2012.2208964","article-title":"Nonlocal means denoising of ECG signals","volume":"59","author":"Tracey","year":"2012","journal-title":"IEEE Transactions on Biomedical Engineering"},{"issue":"6","key":"10.3233\/ICA-220686_ref25","doi-asserted-by":"crossref","first-page":"719","DOI":"10.1134\/S1063771014050121","article-title":"Using nonlocal means to separate cardiac and respiration sounds","volume":"60","author":"Rudnitskii","year":"2014","journal-title":"Acoustical Physics"},{"key":"10.3233\/ICA-220686_ref26","unstructured":"Sathesh K, Muniraj N. Real time heart and lung sound separation using adaptive line enhancer with NLMS. Journal of Theoretical & Applied Information Technology. 2014; 65(2)."},{"issue":"1","key":"10.3233\/ICA-220686_ref27","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1109\/JBHI.2014.2349156","article-title":"On the blind recovery of cardiac and respiratory sounds","volume":"19","author":"Shah","year":"2014","journal-title":"IEEE Journal of Biomedical and Health Informatics"},{"key":"10.3233\/ICA-220686_ref28","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/j.apacoust.2017.04.005","article-title":"A non-negative matrix factorization approach based on spectro-temporal clustering to extract heart sounds","volume":"125","author":"Canadas-Quesada","year":"2017","journal-title":"Applied Acoustics"},{"issue":"11","key":"10.3233\/ICA-220686_ref29","doi-asserted-by":"crossref","first-page":"3203","DOI":"10.1109\/JBHI.2020.3016831","article-title":"Blind monaural source separation on heart and lung sounds based on periodic-coded deep autoencoder","volume":"24","author":"Tsai","year":"2020","journal-title":"IEEE Journal of Biomedical and Health Informatics"},{"issue":"1","key":"10.3233\/ICA-220686_ref30","doi-asserted-by":"crossref","first-page":"45","DOI":"10.3233\/IDT-200038","article-title":"An innovative method for cardiovascular disease detection based on nonlinear geometric features and feature reduction combination","volume":"15","author":"Saeedi","year":"2021","journal-title":"Intelligent Decision Technologies"},{"key":"10.3233\/ICA-220686_ref31","doi-asserted-by":"crossref","unstructured":"Grooby E, He J, Fattahi D, Zhou L, King A, Ramanathan A, et al. A New Non-Negative Matrix Co-Factorisation Approach for Noisy Neonatal Chest Sound Separation. In: 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE; 2021. pp. 5668-73.","DOI":"10.1109\/EMBC46164.2021.9630256"},{"key":"10.3233\/ICA-220686_ref32","first-page":"1","article-title":"Parallel source separation system for heart and lung sounds","author":"Mu\u00f1oz-Montoro","year":"2021","journal-title":"The Journal of Supercomputing"},{"issue":"3","key":"10.3233\/ICA-220686_ref37","doi-asserted-by":"crossref","first-page":"793","DOI":"10.1162\/neco.2008.04-08-771","article-title":"Nonnegative Matrix Factorization with the Itakura-Saito Divergence: With Application to Music Analysis","volume":"21","author":"F\u00e9votte","year":"2009","journal-title":"Neural Computation"},{"key":"10.3233\/ICA-220686_ref38","doi-asserted-by":"crossref","unstructured":"Virtanen T. Monaural Sound Source Separation by Nonnegative Matrix Factorization With Temporal Continuity and Sparseness Criteria. IEEE Transactions on Audio, Speech and Language Processing. 2007 Mar; 15(3): 1066-74.","DOI":"10.1109\/TASL.2006.885253"},{"key":"10.3233\/ICA-220686_ref39","doi-asserted-by":"crossref","unstructured":"Charleston-Villalobos S, Dominguez-Robert LF, Gonzalez-Camarena R, Aljama-Corrales AT. Heart Sounds Interference Cancellation in Lung Sounds. In: 2006 International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE; 2006. pp. 1694-7.","DOI":"10.1109\/IEMBS.2006.259357"},{"key":"10.3233\/ICA-220686_ref40","doi-asserted-by":"crossref","unstructured":"Grooby E, Sitaula C, Fattahi D, Sameni R, Tan K, Zhou L, et al. Noisy Neonatal Chest Sound Separation for High-Quality Heart and Lung Sounds. arXiv preprint arXiv: 220103211. 2022.","DOI":"10.1109\/JBHI.2022.3215995"},{"key":"10.3233\/ICA-220686_ref41","doi-asserted-by":"crossref","unstructured":"Grais EM, Erdogan H. Single channel speech music separation using nonnegative matrix factorization and spectral masks. In: 2011 17th International Conference on Digital Signal Processing (DSP). IEEE; 2011. pp. 1-6.","DOI":"10.1109\/ICDSP.2011.6004924"},{"issue":"4","key":"10.3233\/ICA-220686_ref42","doi-asserted-by":"crossref","first-page":"391","DOI":"10.3233\/ICA-2011-0384","article-title":"A low-cost 3D human interface device using GPU-based optical flow algorithms","volume":"18","author":"del Riego","year":"2011","journal-title":"Integrated Computer-Aided Engineering"},{"key":"10.3233\/ICA-220686_ref43","first-page":"1","article-title":"An integrated low-cost system for object detection in underwater environments","author":"Foresti","year":"2022","journal-title":"Integrated Computer-Aided Engineering"},{"issue":"4","key":"10.3233\/ICA-220686_ref47","doi-asserted-by":"crossref","first-page":"1350","DOI":"10.1016\/j.patcog.2007.09.010","article-title":"SVD based initialization: A head start for nonnegative matrix factorization","volume":"41","author":"Boutsidis","year":"2008","journal-title":"Pattern Recognition"},{"key":"10.3233\/ICA-220686_ref48","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/j.patrec.2019.02.018","article-title":"Improved SVD-based initialization for nonnegative matrix factorization using low-rank correction","volume":"122","author":"Atif","year":"2019","journal-title":"Pattern Recognition Letters"},{"key":"10.3233\/ICA-220686_ref49","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.patrec.2015.05.019","article-title":"New SVD based initialization strategy for non-negative matrix factorization","volume":"63","author":"Qiao","year":"2015","journal-title":"Pattern Recognition Letters"},{"key":"10.3233\/ICA-220686_ref50","unstructured":"Stewart GW. Perturbation theory for the singular value decomposition; 1998."},{"key":"10.3233\/ICA-220686_ref51","doi-asserted-by":"crossref","unstructured":"Frigo M, Johnson SG. The design and implementation of FFTW3. Proceedings of the IEEE. 2005; 93(2): 216-31.","DOI":"10.1109\/JPROC.2004.840301"},{"issue":"1","key":"10.3233\/ICA-220686_ref52","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1109\/99.660313","article-title":"OpenMP: an industry standard API for shared-memory programming","volume":"5","author":"Dagum","year":"1998","journal-title":"IEEE Computational Science and Engineering"},{"issue":"4","key":"10.3233\/ICA-220686_ref53","doi-asserted-by":"crossref","first-page":"808","DOI":"10.1137\/17M1117732","article-title":"The singular value decomposition: Anatomy of optimizing an algorithm for extreme scale","volume":"60","author":"Dongarra","year":"2018","journal-title":"SIAM Review"},{"issue":"64","key":"10.3233\/ICA-220686_ref54","first-page":"175","article-title":"System of heart and lung sounds separation for store-and-forward telemedicine applications","author":"Salazar","year":"2012","journal-title":"Revista Facultad de Ingenieria"},{"key":"10.3233\/ICA-220686_ref55","doi-asserted-by":"crossref","unstructured":"Lin C, Hasting E. Blind source separation of heart and lung sounds based on nonnegative matrix factorization. In: 2013 International Symposium on Intelligent Signal Processing and Communication Systems; 2013. pp. 731-6.","DOI":"10.1109\/ISPACS.2013.6704646"},{"key":"10.3233\/ICA-220686_ref56","first-page":"135","article-title":"An Updated Set of Basic Linear Algebra Subprograms (BLAS)","volume":"28","author":"Blackford","year":"2001","journal-title":"ACM Transactions on Mathematical Software"},{"key":"10.3233\/ICA-220686_ref57","doi-asserted-by":"crossref","unstructured":"Yaseen, Son GY, Kwon S. Classification of Heart Sound Signal Using Multiple Features. Applied Sciences. 2018; 8(12).","DOI":"10.3390\/app8122344"},{"key":"10.3233\/ICA-220686_ref58","unstructured":"Bentley P, Nordehn G, Coimbra M, Mannor S, Getz R. Classifying Heart Sounds Challenge; 2011. [Accessed 16-January-2021]."},{"key":"10.3233\/ICA-220686_ref59","doi-asserted-by":"crossref","unstructured":"Vincent E, Gribonval R, Fevotte C. Performance measurement in blind audio source separation. IEEE Transactions on Audio, Speech and Language Processing. 2006 Jul; 14(4): 1462-9. http\/\/ieeexplore.ieee.org\/document\/1643671\/.","DOI":"10.1109\/TSA.2005.858005"},{"issue":"12","key":"10.3233\/ICA-220686_ref60","doi-asserted-by":"crossref","first-page":"3360","DOI":"10.1109\/TBME.2011.2162728","article-title":"Localizing heart sounds in respiratory signals using singular spectrum analysis","volume":"58","author":"Ghaderi","year":"2011","journal-title":"IEEE Transactions on Biomedical Engineering"},{"key":"10.3233\/ICA-220686_ref61","doi-asserted-by":"crossref","unstructured":"Wang Z, da Cruz JN, Wan F. Adaptive Fourier decomposition approach for lung-heart sound separation. In: 2015 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA). IEEE; 2015. pp. 1-5.","DOI":"10.1109\/CIVEMSA.2015.7158631"},{"key":"10.3233\/ICA-220686_ref62","doi-asserted-by":"publisher","DOI":"10.3109\/03091902."},{"key":"10.3233\/ICA-220686_ref65","doi-asserted-by":"crossref","unstructured":"Nedoma J, Fajkus M, Martinek R, Kepak S, Cubik J, Zabka S, et al. Comparison of BCG, PCG and ECG signals in application of heart rate monitoring of the human body. In: 2017 40th International Conference on Telecommunications and Signal Processing (TSP). IEEE; 2017. pp. 420-4.","DOI":"10.1109\/TSP.2017.8076019"}],"container-title":["Integrated Computer-Aided Engineering"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/ICA-220686","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T09:14:43Z","timestamp":1777454083000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/ICA-220686"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,24]]},"references-count":56,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.3233\/ica-220686","relation":{},"ISSN":["1069-2509","1875-8835"],"issn-type":[{"value":"1069-2509","type":"print"},{"value":"1875-8835","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,11,24]]}}}