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. 2021 Nov 29;21(23):7976.
doi: 10.3390/s21237976.

Proposal for a Home Sleep Monitoring Platform Employing a Smart Glove

Remo Lazazzera  1 , Pablo Laguna  2 , Eduardo Gil  2 , Guy Carrault  1
Affiliations

Proposal for a Home Sleep Monitoring Platform Employing a Smart Glove

Remo Lazazzera et al. Sensors (Basel). .

Abstract

The 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.

Keywords: apnea; breathing rate; heart rate variability; medical of things; sleep monitoring; smart glove.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
The UpNEA device and its prototype.
Figure 2
Figure 2
Datastream visualization for UpNEA.
Figure 3
Figure 3
UpNEA AWS architecture for cloud stream and computing, refer to text for further details.
Figure 4
Figure 4
Encoding block structure.
Figure 5
Figure 5
Apneic and hypopneic events detection flowchart.
Figure 6
Figure 6
The user interface of the UpNEA web application.
Figure 7
Figure 7
The DAP detection method is applied to a PPG signal.
See this image and copyright information in PMC

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