doi:10.3390/s21237976engLazazzera, RemoLaguna, PabloGil, EduardoCarrault, GuyProposal for a home sleep monitoring platform employing a smart gloveART-2021-125670The present paper proposes the design of a sleep monitoring platform. It consists of an entire sleep monitoring system based on a smart glove sensor called UpNEA worn during the night for signals acquisition, a mobile application, and a remote server called AeneA for cloud computing. UpNEA acquires a 3-axis accelerometer signal, a photoplethysmography (PPG), and a peripheral oxygen saturation (SpO2) signal from the index finger. Overnight recordings are sent from the hardware to a mobile application and then transferred to AeneA. After cloud computing, the results are shown in a web application, accessible for the user and the clinician. The AeneA sleep monitoring activity performs different tasks: sleep stages classification and oxygen desaturation assessment; heart rate and respiration rate estimation; tachycardia, bradycardia, atrial fibrillation, and premature ventricular contraction detection; and apnea and hypopnea identification and classification. The PPG breathing rate estimation algorithm showed an absolute median error of 0.5 breaths per minute for the 32 s window and 0.2 for the 64 s window. The apnea and hypopnea detection algorithm showed an accuracy (Acc) of 75.1%, by windowing the PPG in one-minute segments. The classification task revealed 92.6% Acc in separating central from obstructive apnea, 83.7% in separating central apnea from central hypopnea and 82.7% in separating obstructive apnea from obstructive hypopnea. The novelty of the integrated algorithms and the top-notch cloud computing products deployed, encourage the production of the proposed solution for home sleep monitoring.2021http://zaguan.unizar.es/record/10945510.3390/s21237976http://zaguan.unizar.es/record/109455oai:zaguan.unizar.es:109455info:eu-repo/grantAgreement/ES/DGA-FSE/T39-20R-BSICoS groupinfo:eu-repo/grantAgreement/ES/MICINN/PID2019-104881RB-I00info:eu-repo/grantAgreement/ES/MINECO-FEDER/RTI2018-097723-B-I00Sensors 21, 23 (2021), s21237976 [21 pp.]byhttp://creativecommons.org/licenses/by/3.0/es/info:eu-repo/semantics/openAccess