000098285 001__ 98285 000098285 005__ 20230914083306.0 000098285 0247_ $$2doi$$a10.23919/CinC49843.2019.9005858 000098285 0248_ $$2sideral$$a122003 000098285 037__ $$aART-2019-122003 000098285 041__ $$aeng 000098285 100__ $$0(orcid)0000-0001-8742-0072$$aLázaro, J.$$uUniversidad de Zaragoza 000098285 245__ $$aHeart Rate Variability Monitoring Using a Wearable Armband 000098285 260__ $$c2019 000098285 5060_ $$aAccess copy available to the general public$$fUnrestricted 000098285 5203_ $$aA wearable electrocardiogram (ECG) monitor is evaluated as heart rate variability (HRV) monitor. The device consists of an armband designed to be worn on the left upper arm which provides 3 ECG channels based on 3 pairs of dry (no hydrogel) electrodes. Armband-ECG and conventional-Holter-ECG signals were simultaneously recorded from 14 subjects during 5 minutes in supine position. Spacial principal component analysis was used to obtain a unique armband ECG signal in which the electromyogram contribution is attenuated. QRS complexes were automatically detected. Five traditional HRV parameters were derived: SDNN, RMSSD, pNN50, and powers within low frequency (LF, [0.04, 0.15] Hz) and high frequency (HF, [0.15, 0.4] Hz) bands. The Pearson''s correlation coefficient between the measurements from the armband device and the measures from the Holter device was computed. Results show very high correlations (1.0000, 0.9999, 0.9984, 1.0000, and 0.9999 for SDNN, RMSSD, pNN50, and powers at LF and HF, respectively), suggesting that the quality of armband-ECG signals is enough to estimate HRV parameters during stationary movement restricted conditions. 000098285 536__ $$9info:eu-repo/grantAgreement/ES/ISCIII/CIBER-BBN$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 745755-WECARMON$$9info:eu-repo/grantAgreement/EC/H2020/745755/EU/Wearable Cardiorespiratory Monitor/WECARMON$$9info:eu-repo/grantAgreement/ES/DGA-FEDER/T39-17R-BSICoS 000098285 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/ 000098285 592__ $$a0.296$$b2019 000098285 593__ $$aComputer Science (miscellaneous)$$c2019 000098285 593__ $$aCardiology and Cardiovascular Medicine$$c2019 000098285 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion 000098285 700__ $$aReljin, N. 000098285 700__ $$aNoh, Y. 000098285 700__ $$0(orcid)0000-0003-3434-9254$$aLaguna, P.$$uUniversidad de Zaragoza 000098285 700__ $$aChon, K.H. 000098285 7102_ $$15008$$2800$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Teoría Señal y Comunicac. 000098285 773__ $$g46 (2019), [4 pp]$$pComput. cardiol.$$tComputing in Cardiology$$x2325-8861 000098285 8564_ $$s201933$$uhttps://zaguan.unizar.es/record/98285/files/texto_completo.pdf$$yVersión publicada 000098285 8564_ $$s2880063$$uhttps://zaguan.unizar.es/record/98285/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada 000098285 909CO $$ooai:zaguan.unizar.es:98285$$particulos$$pdriver 000098285 951__ $$a2023-09-13-10:56:10 000098285 980__ $$aARTICLE