Literature DB >> 23771214

A review of current sleep screening applications for smartphones.

Joachim Behar1, Aoife Roebuck, João S Domingos, Elnaz Gederi, Gari D Clifford.   

Abstract

Sleep disorders are a common problem and contribute to a wide range of healthcare issues. The societal and financial costs of sleep disorders are enormous. Sleep-related disorders are often diagnosed with an overnight sleep test called a polysomnogram, or sleep study involving the measurement of brain activity through the electroencephalogram. Other parameters monitored include oxygen saturation, respiratory effort, cardiac activity (through the electrocardiogram), as well as video recording, sound and movement activity. Monitoring can be costly and removes the patients from their normal sleeping environment, preventing repeated unbiased studies. The recent increase in adoption of smartphones, with high quality on-board sensors has led to the proliferation of many sleep screening applications running on the phone. However, with the exception of simple questionnaires, no existing sleep-related application available for smartphones is based on scientific evidence. This paper reviews the existing smartphone applications landscape used in the field of sleep disorders and proposes possible advances to improve screening approaches.

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Year:  2013        PMID: 23771214     DOI: 10.1088/0967-3334/34/7/R29

Source DB:  PubMed          Journal:  Physiol Meas        ISSN: 0967-3334            Impact factor:   2.833


  32 in total

Review 1.  A review of signals used in sleep analysis.

Authors:  A Roebuck; V Monasterio; E Gederi; M Osipov; J Behar; A Malhotra; T Penzel; G D Clifford
Journal:  Physiol Meas       Date:  2013-12-17       Impact factor: 2.833

2.  A Qualitative Assessment of the Acceptability of Smartphone Applications for Improving Sleep Behaviors in Low-Income and Minority Adolescents.

Authors:  Mirja Quante; Neha Khandpur; Emily Z Kontos; Jessie P Bakker; Judith A Owens; Susan Redline
Journal:  Behav Sleep Med       Date:  2018-02-05       Impact factor: 2.964

3.  Consumer Sleep Apps: When it Comes to the Big Picture, it's All About the Frame.

Authors:  Matt T Bianchi
Journal:  J Clin Sleep Med       Date:  2015-07-15       Impact factor: 4.062

4.  Mobile Devices and Insomnia: Understanding Risks and Benefits.

Authors:  Mohammed N Khan; Rebecca Nock; Nalaka S Gooneratne
Journal:  Curr Sleep Med Rep       Date:  2015-10-19

5.  Statistical sleep pattern modelling for sleep quality assessment based on sound events.

Authors:  Hongle Wu; Takafumi Kato; Masayuki Numao; Ken-Ichi Fukui
Journal:  Health Inf Sci Syst       Date:  2017-10-30

Review 6.  Feeling validated yet? A scoping review of the use of consumer-targeted wearable and mobile technology to measure and improve sleep.

Authors:  Kelly Glazer Baron; Jennifer Duffecy; Mark A Berendsen; Ivy Cheung Mason; Emily G Lattie; Natalie C Manalo
Journal:  Sleep Med Rev       Date:  2017-12-20       Impact factor: 11.609

7.  Heart rate-based window segmentation improves accuracy of classifying posttraumatic stress disorder using heart rate variability measures.

Authors:  Erik Reinertsen; Shamim Nemati; Adriana N Vest; Viola Vaccarino; Rachel Lampert; Amit J Shah; Gari D Clifford
Journal:  Physiol Meas       Date:  2017-05-10       Impact factor: 2.833

Review 8.  Monitoring healthy and disturbed sleep through smartphone applications: a review of experimental evidence.

Authors:  Edita Fino; Michela Mazzetti
Journal:  Sleep Breath       Date:  2018-04-23       Impact factor: 2.816

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

Authors:  Sushanth Bhat; Ambra Ferraris; Divya Gupta; Mona Mozafarian; Vincent A DeBari; Neola Gushway-Henry; Satish P Gowda; Peter G Polos; Mitchell Rubinstein; Huzaifa Seidu; Sudhansu Chokroverty
Journal:  J Clin Sleep Med       Date:  2015-07-15       Impact factor: 4.062

10.  In-Home Sleep Apnea Severity Classification using Contact-free Load Cells and an AdaBoosted Decision Tree Algorithm.

Authors:  Clara Mosquera-Lopez; Joseph Leitschuh; John Condon; Chad C Hagen; Cody Hanks; Peter G Jacobs
Journal:  Annu Int Conf IEEE Eng Med Biol Soc       Date:  2018-07
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