Analysis of Smartphone Triaxial Accelerometry for Monitoring Sleep-Disordered Breathing and Sleep Position at Home

Ignasi Ferrer-Lluis,Yolanda Castillo-Escario,Josep Maria Montserrat,Raimon Jane

doi:10.1109/access.2020.2987488

Abstract

Obstructive sleep apnea (OSA) is a sleep disorder in which repetitive upper airway obstructive events occur during sleep. These events can induce hypoxia, which is a risk factor for multiple cardiovascular and cerebrovascular diseases. OSA is also known to be position-dependent in some patients, which is referred to as positional OSA (pOSA). Screening for pOSA is necessary in order to design more personalized and effective treatment strategies. In this article, we propose analyzing accelerometry signals, recorded with a smartphone, to detect and monitor OSA at home. Our objectives were to: (1) develop an algorithm for detecting thoracic movement associated with disordered breathing events; (2) compare the performance of smartphones as OSA monitoring tools with a type 3 portable sleep monitor; and (3) explore the feasibility of using smartphone accelerometry to retrieve reliable patient sleep position data and assess pOSA. Accelerometry signals were collected through simultaneous overnight acquisition using both devices with 13 subjects. The smartphone tool showed a high degree of concordance compared to the portable device and succeeded in estimating the apnea-hypopnea index (AHI) and classifying the severity level in most subjects. To assess the agreement between the two systems, an event-by-event comparison was performed, which found a sensitivity of 90% and a positive predictive value of 80%. It was also possible to identify pOSA by determining the ratio of events occurring in a specific position versus the time spent in that position during the night. These novel results suggest that smartphones are promising mHealth tools for OSA and pOSA monitoring at home.

Highlights

Because of its critical role in human health, sleep is one of the most important aspects of daily life
The objectives of this paper are: (1) to develop an algorithm for detecting thoracic movement associated with disordered breathing events; (2) to compare the performance of smartphones as Obstructive sleep apnea (OSA) monitor tools with the performance of a type 3 portable sleep monitor; and (3) to explore the feasibility of smartphone accelerometry in retrieving reliable patient sleep position data and assessing positional OSA (pOSA)
HOME EVENT DETECTION PERFORMANCE Fig. 2 shows a five-minute time sample of the alignment between the events obtained from the reference device and the events retrieved with the automatic event detector based on smartphone accelerometry when the subject was sleeping in the supine position

Summary

Introduction

Because of its critical role in human health, sleep is one of the most important aspects of daily life. Low-quality or disturbed sleep is associated with multiple health complications, such. As mental disorders [1]–[3], and is a known risk factor for other health disorders, including increased cardiovascular and cerebrovascular morbidity and mortality [4]–[6]. Obstructive sleep apnea (OSA) is one of the most common diseases affecting sleep quality. OSA is characterized by the occurrence of obstructive events in which a partial or total occlusion of the upper airway is produced, which results. I. Ferrer-Lluis et al.: Analysis of Smartphone Triaxial Accelerometry in a disordered breathing pattern. Ferrer-Lluis et al.: Analysis of Smartphone Triaxial Accelerometry in a disordered breathing pattern This disordered breathing induces the appearance of hypoxic events and microarousals, which are a known risk factor for multiple cardiovascular diseases [7]

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