mHealth tools for monitoring Obstructive Sleep Apnea patients at home: Proof-of-concept

Obstructive Sleep Apnea (OSA) is a sleep disorder that affects mainly the adult and elderly population. Due to the high percentage of patients who remain undiagnosed and untreated because of limitations of current diagnosis methods, the management of OSA is an important social, scientific and economic problem that will be difficult to be assumed by health systems. On the other hand, smartphone platforms (mHealth systems) are being considered as an innovative solution, thanks to the integration of the essential sensors to obtain clinically relevant parameters in the same device or in combination with wireless wearable devices.

[1]  Fadi A. Aloul,et al.  Classifying obstructive sleep apnea using smartphones , 2014, J. Biomed. Informatics.

[2]  Raimon Jané,et al.  Respiratory signal derived from the smartphone built-in accelerometer during a Respiratory Load Protocol , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[3]  Raimon Jané,et al.  Continuous analysis and monitoring of snores and their relationship to the apnea‐hypopnea index , 2010, The Laryngoscope.

[4]  R. Jané,et al.  Acoustic analysis of snoring sound in patients with simple snoring and obstructive sleep apnoea. , 1996, The European respiratory journal.

[5]  Niclas Palmius,et al.  SleepAp: An automated obstructive sleep apnoea screening application for smartphones , 2013, Computing in Cardiology 2013.

[6]  J. Remmers,et al.  Characteristics of the snoring noise in patients with and without occlusive sleep apnea. , 1993, The American review of respiratory disease.

[7]  S. Quan,et al.  Quality measures for the care of adult patients with obstructive sleep apnea. , 2015, Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine.

[8]  R. Jane,et al.  Automatic snoring signal analysis in sleep studies , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

[9]  H. Nakano,et al.  Monitoring sound to quantify snoring and sleep apnea severity using a smartphone: proof of concept. , 2014, Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine.