000075985 001__ 75985
000075985 005__ 20231116120808.0
000075985 0247_ $$2doi$$a10.1155/2018/9138578
000075985 0248_ $$2sideral$$a109052
000075985 037__ $$aART-2018-109052
000075985 041__ $$aeng
000075985 100__ $$0(orcid)0000-0002-6963-0727$$aRodriguez, V.H.
000075985 245__ $$aEmbedded System Based on an ARM Microcontroller to Analyze Heart Rate Variability in Real Time Using Wavelets
000075985 260__ $$c2018
000075985 5060_ $$aAccess copy available to the general public$$fUnrestricted
000075985 5203_ $$aThe analyses of electrocardiogram (ECG) and heart rate variability (HRV) arc of primordial interest for cardiovascular diseases. The algorithm used for the detection of the QRS complex is the basis for HRV analysis and HRV quality will depend strongly on it. The aim of this paper is to implement HRV analysis in real time on an ARM microcontroller (MCU). Thus, there is no need to send raw data to a cloud server for real time HRV monitoring and, consequently, the communication requirements and the power consumption of the local sensor node would be far lower. The system would facilitate the integration into edge computing, for instance, in small local networks, such as hospitals. A QRS detector based on wavelets is proposed, which is able to autonomously select the coefficients the QRS complex will be detected with. To validate it, the MITBIH and NSRDB databases were used. This detector was implemented in real time using an MCU. Subsequently HRV analysis was implemented in the time, frequency, and nonlinear domains. When evaluating the QRS detector with the MITBIH database, 99.61% positive prediction (PP), 99.3% sensitivity (SE), and a prediction error rate (DER) of 1.12% were obtained. For the NSRDB database the results were a PP of 99.95%, an SE of 99.98%, and a DER of 0.0006%. The execution of the QRS detector in the MCU took 52 milliseconds. On the other hand, the time required to calculate the HRV depends on the data size, but it took only a few seconds to analyze several thousands of interbeat intervals. The results obtained for the detector were superior to 99%, so it is expected that the HRV is reliable. It has also been shown that the detection of QRS complex can be done in real time using advanced processing techniques such as wavelets.
000075985 536__ $$9info:eu-repo/grantAgreement/ES/DGA/FSE$$9info:eu-repo/grantAgreement/ES/DGA/T49-17R
000075985 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000075985 590__ $$a1.396$$b2018
000075985 591__ $$aCOMPUTER SCIENCE, INFORMATION SYSTEMS$$b113 / 154 = 0.734$$c2018$$dQ3$$eT3
000075985 591__ $$aENGINEERING, ELECTRICAL & ELECTRONIC$$b186 / 265 = 0.702$$c2018$$dQ3$$eT3
000075985 591__ $$aTELECOMMUNICATIONS$$b67 / 88 = 0.761$$c2018$$dQ4$$eT3
000075985 592__ $$a0.246$$b2018
000075985 593__ $$aElectrical and Electronic Engineering$$c2018$$dQ3
000075985 593__ $$aInformation Systems$$c2018$$dQ3
000075985 593__ $$aComputer Networks and Communications$$c2018$$dQ3
000075985 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000075985 700__ $$0(orcid)0000-0001-7671-7540$$aMedrano, C.$$uUniversidad de Zaragoza
000075985 700__ $$0(orcid)0000-0001-7550-6688$$aPlaza, I.$$uUniversidad de Zaragoza
000075985 7102_ $$15008$$2785$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Tecnología Electrónica
000075985 773__ $$g2018, 9138578 (2018), [14 pp.]$$pWirel. Commun. Mob. Comput.$$tWIRELESS COMMUNICATIONS & MOBILE COMPUTING$$x1530-8669
000075985 8564_ $$s931821$$uhttps://zaguan.unizar.es/record/75985/files/texto_completo.pdf$$yVersión publicada
000075985 8564_ $$s103452$$uhttps://zaguan.unizar.es/record/75985/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000075985 909CO $$ooai:zaguan.unizar.es:75985$$particulos$$pdriver
000075985 951__ $$a2023-11-16-12:00:18
000075985 980__ $$aARTICLE