106725 20210827115915.0 doi 10.1109/EMBC44109.2020.9175486 sideral 120316 ART-2020-120316 eng Lazaro, Jesús Universidad de Zaragoza (orcid)0000-0001-8742-0072 Electrocardiogram Derived Respiration for Tracking Changes in Tidal Volume from a Wearable Armband 2020 A pilot study on tracking changes in tidal volume (TV) using ECG signals acquired by a wearable armband is presented. The wearable armband provides three ECG channels by using three pairs of dry electrodes, resulting in a device that is convenient for long-term daily monitoring. An additional ECG channel was derived by computing the first principal component of the three original channels (by means of principal component analysis). Armband and spirometer signals were simultaneously recorded from five healthy subjects who were instructed to breathe with varying TV. Three electrocardiogram derived respiration (EDR) methods based on QRS complex morphology were studied: the QRS slopes range (SR), the R-wave angle (), and the R-S amplitude (RS). The peak-to-peak amplitudes of these EDR signals were estimated as surrogates for TV, and their correlations with the reference TV (estimated from the spirometer signal) were computed. In addition, a multiple linear regression model was calculated for each subject, using the peak-to-peak amplitudes from the three EDR methods from the four ECG channels. Obtained correlations between TV and EDR peak-to-peak amplitude ranged from 0.0448 up to 0.8491. For every subject, a moderate correlation (>0.5) was obtained for at least one EDR method. Furthermore, the correlations obtained for the subject-specific multiple linear regression model ranged from 0.8234 up to 0.9154, and the goodness of fit was 0.73±0.07 (median ± standard deviation). These results suggest that the peak-to-peak amplitudes of the EDR methods are linearly related to the TV. opening the possibility of estimating TV directly from an armband ECG device.Clinical Relevance - This opens the door to possible continuous monitoring of TV from the armband by using EDR. Access copy available to the general public Unrestricted info:eu-repo/grantAgreement/ES/DGA-FSE/T96-BSICoS info:eu-repo/grantAgreement/EC/H2020/745755/EU/Wearable Cardiorespiratory Monitor/WECARMON This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 745755-WECARMON info:eu-repo/grantAgreement/ES/ISCIII/CIBER-BBN info:eu-repo/semantics/openAccess All rights reserved http://www.europeana.eu/rights/rr-f/ info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion Reljin, N. Bailón, Raquel Universidad de Zaragoza (orcid)0000-0003-1272-0550 Gil, Eduardo Universidad de Zaragoza (orcid)0000-0001-7285-0715 Noh, Y. Laguna, Pablo Universidad de Zaragoza (orcid)0000-0003-3434-9254 Chon, K.H. 5007 520 Universidad de Zaragoza Dpto. Informát.Ingenie.Sistms. Área Ingen.Sistemas y Automát. 5008 800 Universidad de Zaragoza Dpto. Ingeniería Electrón.Com. Área Teoría Señal y Comunicac. 2020-July (2020), 596-599 Conf. proc. (IEEE Eng. Med. Biol. Soc., Conf.) Conference proceedings (IEEE Engineering in Medicine and Biology Society. Conf.) 1557-170X 379641 http://zaguan.unizar.es/record/106725/files/texto_completo.pdf Postprint 3469026 http://zaguan.unizar.es/record/106725/files/texto_completo.jpg?subformat=icon icon Postprint oai:zaguan.unizar.es:106725 articulos driver 2021-08-27-09:55:26 ARTICLE