Design and preliminary evaluation of a wearable device for mass-screening of sleep apnea

Puri, Rohan; Athanassiadis, Athanasios G.; Gill, Niharika; Sathya, Sai Sri; Rathod, Geetanjali; Wahi, Akshat; Satat, Guy; Majmudar, Maulik D.; Shah, Pratik

doi:10.1109/embc.2016.7591085

Cited by 9 publications

(5 citation statements)

References 15 publications

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“…Type-4 devices consider one or two of these parameters. Studies have applied wearable devices operated using various technologies, such as actigraphy, finger-based pulse oximetry, and single-channel electrocardiography, for the home-based recording of sleep parameters [ 6 , 7 , 8 ]. More recently, a biosensor that integrates an electrocardiography module and a three-axis accelerometer was developed, demonstrating favourable reliability and accuracy in evaluating OSA severity [ 9 ].…”

Section: Introductionmentioning

confidence: 99%

Comparison of Hospital-Based and Home-Based Obstructive Sleep Apnoea Severity Measurements with a Single-Lead Electrocardiogram Patch

Liu

Lin

Tsai

et al. 2021

Sensors

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Obstructive sleep apnoea (OSA) is a global health concern, and polysomnography (PSG) is the gold standard for assessing OSA severity. However, the sleep parameters of home-based and in-laboratory PSG vary because of environmental factors, and the magnitude of these discrepancies remains unclear. We enrolled 125 Taiwanese patients who underwent PSG while wearing a single-lead electrocardiogram patch (RootiRx). After the PSG, all participants were instructed to continue wearing the RootiRx over three subsequent nights. Scores on OSA indices—namely, the apnoea–hypopnea index, chest effort index (CEI), cyclic variation of heart rate index (CVHRI), and combined CVHRI and CEI (Rx index), were determined. The patients were divided into three groups based on PSG-determined OSA severity. The variables (various severity groups and environmental measurements) were subjected to mean comparisons, and their correlations were examined by Pearson’s correlation coefficient. The hospital-based CVHRI, CEI, and Rx index differed significantly among the severity groups. All three groups exhibited a significantly lower percentage of supine sleep time in the home-based assessment, compared with the hospital-based assessment. The percentage of supine sleep time (∆Supine%) exhibited a significant but weak to moderate positive correlation with each of the OSA indices. A significant but weak-to-moderate correlation between the ∆Supine% and ∆Rx index was still observed among the patients with high sleep efficiency (≥80%), who could reduce the effect of short sleep duration, leading to underestimation of the patients’ OSA severity. The high supine percentage of sleep may cause OSA indices’ overestimation in the hospital-based examination. Sleep recording at home with patch-type wearable devices may aid in accurate OSA diagnosis.

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Section: Introductionmentioning

confidence: 99%

Comparison of Hospital-Based and Home-Based Obstructive Sleep Apnoea Severity Measurements with a Single-Lead Electrocardiogram Patch

Liu

Lin

Tsai

et al. 2021

Sensors

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“…The study proved a strong correlation between apneas and the autonomic nervous system activation, as well as the usefulness of galvanic skin response sensors in apnea detection [37]. Puri et al developed a mask called ARAM that is able to monitor sleep patterns by the means of a pressure sensor, a microphone, an accelerometer, and a temperature sensor [38]. VOCNEA detects apnea and hypopnea by using gas sensors [39].…”

Section: State Of the Art Of Wearable Wireless Devices For Srbdmentioning

confidence: 99%

A New Wearable System for Home Sleep Apnea Testing, Screening, and Classification

Manoni

Loreti

Radicioni

et al. 2020

Sensors

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We propose an unobtrusive, wearable, and wireless system for the pre-screening and follow-up in the domestic environment of specific sleep-related breathing disorders. This group of diseases manifests with episodes of apnea and hypopnea of central or obstructive origin, and it can be disabling, with several drawbacks that interfere in the daily patient life. The gold standard for their diagnosis and grading is polysomnography, which is a time-consuming, scarcely available test with many wired electrodes disseminated on the body, requiring hospitalization and long waiting times. It is limited by the night-by-night variability of sleep disorders, while inevitably causing sleep alteration and fragmentation itself. For these reasons, only a small percentage of patients achieve a definitive diagnosis and are followed-up. Our device integrates photoplethysmography, an accelerometer, a microcontroller, and a bluetooth transmission unit. It acquires data during the whole night and transmits to a PC for off-line processing. It is positioned on the nasal septum and detects apnea episodes using the modulation of the photoplethysmography signal during the breath. In those time intervals where the photoplethysmography is detecting an apnea, the accelerometer discriminates obstructive from central type thanks to its excellent sensitivity to thoraco-abdominal movements. Tests were performed on a hospitalized patient wearing our integrated system and the type III home sleep apnea testing recommended by The American Academy of Sleep Medicine. Results are encouraging: sensitivity and precision around 90% were achieved in detecting more than 500 apnea episodes. Least thoraco-abdominal movements and body position were successfully classified in lying down control subjects, paving the way toward apnea type classification.

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“…Other popular HSAT methods include the use of pulse oximetry [26], [27], [28], [29] or sound [30], [31], [32]. Lastly, there are several devices that combine multiple signals [15], [33], [34]. These devices can by categorized using the SCOPER system [35].…”

Section: Introductionmentioning

confidence: 99%

Portable Detection of Apnea and Hypopnea Events Using Bio-Impedance of the Chest and Deep Learning

Steenkiste

Groenendaal

Dreesen

et al. 2020

IEEE J. Biomed. Health Inform.

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Design and preliminary evaluation of a wearable device for mass-screening of sleep apnea

Cited by 9 publications

References 15 publications

Comparison of Hospital-Based and Home-Based Obstructive Sleep Apnoea Severity Measurements with a Single-Lead Electrocardiogram Patch

Comparison of Hospital-Based and Home-Based Obstructive Sleep Apnoea Severity Measurements with a Single-Lead Electrocardiogram Patch

A New Wearable System for Home Sleep Apnea Testing, Screening, and Classification

Portable Detection of Apnea and Hypopnea Events Using Bio-Impedance of the Chest and Deep Learning

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