To improve patients’ compliance and achieve better follow-up, we developed a system that, connecting the CPAP with Internet and providing patients with an app in their smartphone, gives support to both patients and pulmonologists.

1. Automatic Support for Improving
Management and Treatment of
Patients with Obstructive Sleep
Apnea Syndrome
Xavier Rafael Palou; Cecilia Turino; Alexander Steblin; Alejandro Lopera;
Ferran Peña; Ana Mayoral; Manuel Sánchez de la Torre; Ferran Barbe;
Jordi Blanco; Eloisa Vargiu

2. Research Objective
To develop new ICT tools and remote clinical follow-up methods to
allow the creation of continuous integrated services for the
treatment of Obstructive Sleep Apnea (OSA)
To improve patients’ compliance and achieve better follow-up in
using continuous positive airway pressure (CPAP) at home
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3. Motivation
Currently in Spain, after a visit with a pulmonologist,
patients suffering from severe OSA are treated with a
CPAP machine at their home
Pulmonologists and CPAP providers guide patients on
how to use the device properly and prescribe them to
use the machine at least 4 hours daily in order to benefit
the therapy
From that moment on, the medical protocol states the
following visits after 1, 3, 6 and 12 months and then once
a year
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4. Methods
Patient’s home: CPAP machine
connected to Internet (3G
connectivity) and a smartphone
with the app.
Hospital: pulmonologists are
provided with a web-application
that summarizes relevant
information and gives also a
support in medical decisions
MyOSA platform: installed in the
cloud, it connects all the devices for
data exchanging
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5. Methods
The core of the proposed solution is the Intelligent Monitoring
System
 It is composed of a set of intelligent algorithms aimed at predicting the
expected adherence level to the therapy by a given patient
 Three predictive models have been built: at day enrollment time, at month 1,
and at month 3. All predictions regard compliance at month 6
 To provide personalized recommendations to patients according to their
adherence, clustering has been used to identify similar users
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6. Results
Through the web application
pulmonologists may access to
patients’ data
 Usage
 Adherence
 Number of leaks
 Statistics
They also receive a prediction of
how patients will follow the
therapy
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7. Results
Through the myOSA app patients may
access to their data
 Usage
 Adherence
 Number of leaks
 Statistics
They may also receive three kinds of
recommendations
 Awards
 Feedback
 Alerts
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8. Final Remarks
The trials just started and a total of 60 patients will participate in the
study
We will improve the system by relying with more data and getting
direct feedback from patients
We will also work together with pulmonologists to improve and
extend the set of recommendations
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9. eloisa.vargiu@eurecat.org
consortium
The study was funded by the Spanish Ministry of
Economy and Competitiveness in the framework of
the call Collaboration Challenges" in the State
Program for Research, Development and Innovation
Oriented to Societal Challenges" (Project myOSA, RTC-
2014-3138-1).
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