Somnography using unobtrusive motion sensors and Android-based mobile phones

Gradl, Stefan; Leutheuser, Heike; Kugler, Patrick; Biermann, Teresa; Kreil, Sebastian; Kornhuber, Johannes; Bergner, Matthias; Eskofier, Bjoern M.

doi:10.1109/embc.2013.6609717

Cited by 9 publications

(5 citation statements)

References 8 publications

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“…Interestingly, investigators were recently able to demonstrate that placing wireless external sensors placed on a bed and integrating them into a mobile phone's platform is almost 80% accurate in distinguishing wakefulness, nonrapid eye movement and REM sleep in a home setting. 16 The use of such additional unobtrusive sensors, making no contact with the subject's body and therefore causing no discomfort, represents a potential means to improve the accuracy of such apps.…”

Section: (20%)mentioning

confidence: 99%

Is There a Clinical Role For Smartphone Sleep Apps? Comparison of Sleep Cycle Detection by a Smartphone Application to Polysomnography

Bhat

Ferraris

Gupta

et al. 2015

Journal of Clinical Sleep Medicine

113

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Study Objectives: Several inexpensive, readily available smartphone apps that claim to monitor sleep are popular among patients. However, their accuracy is unknown, which limits their widespread clinical use. We therefore conducted this study to evaluate the validity of parameters reported by one such app, the Sleep Time app (Azumio, Inc., Palo Alto, CA, USA) for iPhones. Methods: Twenty volunteers with no previously diagnosed sleep disorders underwent in-laboratory polysomnography (PSG) while simultaneously using the app. Parameters reported by the app were then compared to those obtained by PSG. In addition, an epoch-by-epoch analysis was performed by dividing the PSG and app graph into 15-min epochs. S martphones are now ubiquitous. As their technological capabilities continue to improve, both consumers and healthcare personnel are constantly fi nding new and innovative uses for smartphone apps in the fi eld of health and medicine.1 Apps have been incorporated into the practice of medical specialties as diverse as diabetology and neurosurgery, and have found a role in activities ranging from interpretation of radiology imaging to smoking cessation counseling. Sleep related concerns are commonplace as well, and given the burgeoning popularity and easy availability of inexpensive apps that purport to monitor multiple physiological parameters, it is not surprising that several apps have been designed to evaluate sleep quality.2 The inexorable permeation of smartphones into the fi eld of sleep medicine has resulted in the development of promising apps that screen for obstructive sleep apnea (OSA) 3,4 and periodic limb movements in sleep (PLMS). S C I E N T I F I C I N V E S T I G AT I O N Sinsomnia, circadian rhythm disorders, and hypersomnolence to have objective data about sleep patterns in order to make diagnoses and treatment recommendations. There are several apps that allow users to report and analyze their sleep quality and duration, 6 but such data are often intrinsically subjective. In-laboratory polysomnography (PSG) is the gold standard for BRIEF SUMMARY Current Knowledge/Study Rationale: There are several preexisting, widely available, inexpensive smartphone apps designed to monitor sleep, but it is unclear whether they have clinical utility. Our goal was to systematically compare the results obtained by using one such app, the Sleep Time app (Azumio, Inc.) to the gold standard, polysomnography (PSG). Study Impact: Our study shows that the absolute parameters and sleep staging reported by the Sleep Time app (Azumio, Inc.) for iPhones correlate poorly with PSG. Further studies comparing app sleep-wake detection to actigraphy may help elucidate its potential clinical utility.

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Section: (20%)mentioning

confidence: 99%

Is There a Clinical Role For Smartphone Sleep Apps? Comparison of Sleep Cycle Detection by a Smartphone Application to Polysomnography

Bhat

Ferraris

Gupta

et al. 2015

Journal of Clinical Sleep Medicine

113

View full text Add to dashboard Cite

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“…Some of these apps can also track body movement during sleep by using the nearly-universal accelerometers included in smartphones, which are affixed to patients with thoracoabdominal bands. 3,28 Prior studies 29-31 revealed that smartphones may be used to perform pre-screening exams with comparable quality to that of traditional polysomnography. To perform polysomnography, smartphones require the implementation of additional hardware, such as a pulse oximeter, accelerometer, and external microphone.…”

Section: Discussionmentioning

confidence: 99%

“…Serious doubts arise about the effectiveness of these apps that can register only snoring but not other simultaneous parameters, such as oxygen saturation or thoracic-abdominal movement. 30,31…”

Section: Discussionmentioning

confidence: 99%

Mobile Applications in Otolaryngology: A Systematic Review of the Literature, Apple App Store and the Google Play Store

Trecca

Lonigro

Gelardi

et al. 2020

Ann Otol Rhinol Laryngol

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Objectives: Although the last few years have seen an increased number of smartphone applications (apps) disseminated in the field of Otolaryngology (ORL), these apps vary widely in quality. The aim of this paper, therefore, is to systematically review ORL apps directed towards patients in mobile app stores and the current literature. Methods: The Google Play Store, Apple App Store and PubMed were searched for ORL apps for patients using various keywords pertaining to different ORL subspecialties. Apps not relevant to the scope of this research and/or duplicates, educational apps, apps promoting a business, apps requiring specific separate hardware, and apps in non-English were excluded. In PubMed, keywords pertaining to the subspecialties were combined with “mobile app” in a search query; literature reviews, editorials, case reports, conference papers, duplicate articles, and articles irrelevant to ORL apps were excluded. The quality of apps with the highest number of reviews was assessed using the “Mobile App Rating Scale” (MARS), while the quality of the articles was rated using “The Strengthening the Reporting of Observational Studies in Epidemiology” (STROBE) Statement. Results: After searching the app stores, 1074 apps were included and grouped according to their ORL subspecialties. The overall MARS score of the ten most popular apps in each category was 3.65 out of 5. A total of 636 articles were identified in the literature, and 193 were included. The mean adherence percentage of the articles to the STROBE checklist was of 84.37%. Conclusions: Although the apps currently available need further development, their application in ORL appears promising. Further dialogue between physicians and patients, as well as formal support from professional and scientific associations, should be encouraged.

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“…Additionally, these devices have demonstrated similar validation performance to consumer wearables regarding accuracy to PSG. Regarding general weaknesses, these devices tend to be less accurate for individuals who share a bed with a partner or a pet (80). These types of devices detect movement within a particular space, and thus register partner and pet movements.…”

Section: Comparisons To Wearable Actigraphy Devicesmentioning

confidence: 99%

Past, Present, and Future of Multisensory Wearable Technology to Monitor Sleep and Circadian Rhythms

Lujan

Perez-Pozuelo

Grandner

2021

Front. Digit. Health

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Movement-based sleep-wake detection devices (i.e., actigraphy devices) were first developed in the early 1970s and have repeatedly been validated against polysomnography, which is considered the “gold-standard” of sleep measurement. Indeed, they have become important tools for objectively inferring sleep in free-living conditions. Standard actigraphy devices are rooted in accelerometry to measure movement and make predictions, via scoring algorithms, as to whether the wearer is in a state of wakefulness or sleep. Two important developments have become incorporated in newer devices. First, additional sensors, including measures of heart rate and heart rate variability and higher resolution movement sensing through triaxial accelerometers, have been introduced to improve upon traditional, movement-based scoring algorithms. Second, these devices have transcended scientific utility and are now being manufactured and distributed to the general public. This review will provide an overview of: (1) the history of actigraphic sleep measurement, (2) the physiological underpinnings of heart rate and heart rate variability measurement in wearables, (3) the refinement and validation of both standard actigraphy and newer, multisensory devices for real-world sleep-wake detection, (4) the practical applications of actigraphy, (5) important limitations of actigraphic measurement, and lastly (6) future directions within the field.

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Somnography using unobtrusive motion sensors and Android-based mobile phones

Cited by 9 publications

References 8 publications

Is There a Clinical Role For Smartphone Sleep Apps? Comparison of Sleep Cycle Detection by a Smartphone Application to Polysomnography

Is There a Clinical Role For Smartphone Sleep Apps? Comparison of Sleep Cycle Detection by a Smartphone Application to Polysomnography

Mobile Applications in Otolaryngology: A Systematic Review of the Literature, Apple App Store and the Google Play Store

Past, Present, and Future of Multisensory Wearable Technology to Monitor Sleep and Circadian Rhythms

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