Performance evaluation of a wrist-worn reflectance pulse oximeter during sleep

Jung, Hyunjun; Kim, Dongyeop; Lee, Wonkyu; Seo, Hyejung; Seo, Jeong-Hyun; Choi, Jongmin; Joo, Eun Yeon

doi:10.1016/j.sleh.2022.04.003

Cited by 16 publications

(11 citation statements)

References 33 publications

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“…From the raw data of GW, ODI was derived as the number of episode of oxygen desaturation divided by the total sleep time. The sensitivity, specificity, and accuracy of ODI ≥5/h of GW for OSA diagnosis were 89.7%, 64.1%, and 79.4%, similar to our results [15]. In this study, it was confirmed that the ODI of GW had a strong positive correlation (r=0.918) with the AHI of PSG [15].…”

supporting

confidence: 88%

“…The sensitivity, specificity, and accuracy of ODI ≥5/h of GW for OSA diagnosis were 89.7%, 64.1%, and 79.4%, similar to our results [15]. In this study, it was confirmed that the ODI of GW had a strong positive correlation (r=0.918) with the AHI of PSG [15]. Our study is different in that it directly compared the parameters displayed in SW with PSG rather than recalculated parameters.…”

supporting

confidence: 84%

“…The second significance of this study is that, unlike other studies that reanalyzed the data extracted from SWs [15], the oxygen saturation data displayed on the SW was directly compared with the that of PSG. Up to now, wearable devices have not been able to show an accuracy comparable to PSG due to various noises or limitation of the devices itself [8][9][10].…”

Section: Discussionmentioning

confidence: 99%

“…Level III HSAT lacks electroencephalography detection and can measure airflow, respiratory effort, and blood oxygenation. Recently, SWs have a built-in actigraphy and oxygen saturation sensors PPG-based, which can indirectly estimate airflow and breathing rate and intensity, and they are evolving to the level comparable to the level IV HSAT [15][16][17].…”

mentioning

confidence: 99%

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Diagnostic Performance of Photoplethysmography-Based Smartwatch for Obstructive Sleep Apnea

Kim¹,

Park

Choi

2022

J Rhinol

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Background and Objectives: Considering the prevalence and health effects of obstructive sleep apnea (OSA), early diagnosis and proper treatment are essential. Polysomnography (PSG) has limitations in diagnosing or tracking large-scale OSA patients. Smartwatches (SWs) can be equipped with a photoplethysmograph (PPG) that can indirectly measure heart rate and blood oxygen saturation by detecting the difference of light absorption through blood. The purpose of this study is to compare oxygen saturation parameters of PPG-based SWs with those of PSG to determine the diagnostic accuracy for OSA.Methods: After obtaining voluntary consent from patients who were scheduled to undergo PSG in a sleep clinic due to suspected OSA, they were randomly assigned to wear a Galaxy watch4 (GW) or Apple watch7 (AW) on their wrist. The agreement rates between the oxygen saturation parameters of the two SW types and PSG were evaluated. The accuracy, sensitivity, and specificity of the oxygen saturation parameters for diagnosis of OSA (apnea-hypopnea index [AHI] ≥5/h) were compared between the two types of SW.Results: A total of 133 patients underwent PSG while wearing an SW. Including duplicates, 109 patients wearing a GW and 69 wearing an AW were included. The diagnostic accuracy of AHI ≥5/h according to oxygen saturation time measured by a GW was less than 90%, the respective sensitivity and specificity were 82.9% and 75.8%. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was 0.807 (p<0.001). Using the lowest oxygen saturation value of GW, the sensitivity was 81.6%, the specificity was 69.7%, and the AUC of the ROC was 0.849 (p<0.001). The diagnostic accuracy of AHI ≥5/h according to the average oxygen saturation of AW, and the sensitivity and specificity were 75.6% and 70.8%, respectively. The AUC of this ROC curve was 0.757 (p<0.001). Using the lowest oxygen saturation value of AW, the sensitivity was 71.1%, the specificity was 62.5%, and the AUC of the ROC was 0.705 (p=0.005).Conclusion: This study found that the two types of SW showed considerable accuracy in diagnosing OSA, but the accuracy decreased as the severity of OSA increased.

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supporting

confidence: 88%

supporting

confidence: 84%

Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

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Diagnostic Performance of Photoplethysmography-Based Smartwatch for Obstructive Sleep Apnea

Kim¹,

Park

Choi

2022

J Rhinol

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“…Compared with similar recent studies by Quer et al [9] and Mishra et al [10] that approached the detection of COVID-19 through the use of heart rate, steps, and sleep data, the digital solution in this study also provides researchers and clinicians data about oxygenation during sleep [27], in an organic and continuous way, in addition to data on blood pressure and oxygenation, upon volunteer request. Furthermore, as very well detailed by Vijayan et al [28], smartwatches have very broad applicability in the health care field.…”

Section: Principal Findingsmentioning

confidence: 95%

Digital Platform to Continuously Monitor Patients Using a Smartwatch: Preliminary Report

Bin¹,

Pretto²,

Sanchez³

et al. 2022

JMIR Form Res

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Background: Monitoring vital signs such as oximetry, blood pressure, and heart rate is important to follow the evolution of patients. Smartwatches are a revolution in medicine allowing the collection of such data in a continuous and organic way. However, it is still a challenge to make this information available to health care professionals to make decisions during clinical follow-up.Objective: This study aims to build a digital solution that displays vital sign data from smartwatches, collected remotely, continuously, reliably, and from multiple users, with trigger warnings when abnormal results are identified.Methods: This is a single-center prospective study following the guidelines "Evaluating digital health products" from the UK Health Security Agency. A digital platform with 3 different applications was created to capture and display data from the mobile phones of volunteers with smartwatches. We selected 80 volunteers who were followed for 24 weeks each, and the synchronization interval between the smartwatch and digital solution was recorded for each vital sign collected. Results: In 14 weeks of project progress, we managed to recruit 80 volunteers, with 68 already registered in the digital solution. More than 2.8 million records have already been collected, without system downtime. Less than 5% of continuous heart rate measurements (bpm) were synchronized within 2 hours. However, approximately 70% were synchronized in less than 24 hours, and 90% were synchronized in less than 119 hours. Conclusions:The digital solution is working properly in its role of displaying data collected from smartwatches. Vital sign values are being monitored by the research team as part of the monitoring of volunteers. Although the digital solution proved unsuitable for monitoring urgent events, it is more than suitable for use in outpatient clinical use. This digital solution, which is based on cloud technology, can be applied in the future for telemonitoring in regions lacking health care professionals. Accuracy and reliability studies still need to be performed at the end of the 24-week follow-up.

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SnoreOxiNet: Non-contact Diagnosis of Nocturnal Hypoxemia Using Cross-Domain Acoustic Features

Yi,

Yang,

Xiao

et al. 2024

Lecture Notes in Computer Science

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Performance evaluation of a wrist-worn reflectance pulse oximeter during sleep

Cited by 16 publications

References 33 publications

Diagnostic Performance of Photoplethysmography-Based Smartwatch for Obstructive Sleep Apnea

Diagnostic Performance of Photoplethysmography-Based Smartwatch for Obstructive Sleep Apnea

Digital Platform to Continuously Monitor Patients Using a Smartwatch: Preliminary Report

SnoreOxiNet: Non-contact Diagnosis of Nocturnal Hypoxemia Using Cross-Domain Acoustic Features

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