Detecting breathing and snoring episodes using a wireless tracheal sensor - a feasibility study

Marcel Młyńczak , Ewa Migacz , Maciej Migacz , Wojciech Kukwa


Objective: Sleep-disordered breathing is both a clinical and a social problem. This implies the need for convenient solutions to simplify screening and diagnosis. The aim of the study was to investigate the sensitivity and specificity of a novel wireless system in detecting breathing and snoring episodes during sleep. Methods: A wireless acoustic sensor was elaborated and implemented. Segmentation (based on spectral thresholding and heuristics) and classification of all breathing episodes during recording were implemented through a mobile application. The system was evaluated on 1,520 manually labeled episodes registered from 40 real-world, whole-night recordings of 16 generally healthy subjects. Results: The differentiation between normal breathing and snoring had 88.8% accuracy. As the system is intended for screening, high specificity of 95% is reported. Conclusions: The system is a compromise between non-medical phone applications and medical sleep studies. The presented approach enables the study to be repetitive, personal, and inexpensive. It has additional value in the form of wellrecorded data which are reliable and comparable. Significance: The system opens unexplored possibilities in sleep monitoring and study enabling a multi-night recording strategy involving the collection and analysis of abundant data from thousands of people.
Author Marcel Młyńczak IMIB
Marcel Młyńczak,,
- The Institute of Metrology and Biomedical Engineering
, Ewa Migacz
Ewa Migacz,,
, Maciej Migacz
Maciej Migacz,,
, Wojciech Kukwa
Wojciech Kukwa,,
Journal seriesIEEE Journal of Biomedical and Health Informatics, ISSN 1089-7771
Issue year2016
Publication size in sheets0.5
Keywords in English smartphone application, sleep breathing disorders, snoring, tracheal sound analysis, machine learning
Languageen angielski
Score (nominal)35
ScoreMinisterial score = 30.0, 28-11-2017, ArticleFromJournal
Ministerial score (2013-2016) = 35.0, 28-11-2017, ArticleFromJournal
Publication indicators WoS Impact Factor: 2016 = 3.451 (2) - 2016=3.485 (5)
Citation count*1 (2017-11-04)
Share Share

* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.