Your browser doesn't support javascript.
loading
Validation of a New System Using Tracheal Body Sound and Movement Data for Automated Apnea-Hypopnea Index Estimation.
Kalkbrenner, Christoph; Eichenlaub, Manuel; Rüdiger, Stefan; Kropf-Sanchen, Cornelia; Brucher, Rainer; Rottbauer, Wolfgang.
Affiliation
  • Kalkbrenner C; Faculty of Medical Engineering, University of Applied Science Ulm, Ulm, Germany.
  • Eichenlaub M; School of Engineering, University of Warwick, Coventry, United Kingdom.
  • Rüdiger S; Department of Internal Medicine II, University Hospital Ulm, Ulm, Germany.
  • Kropf-Sanchen C; Department of Internal Medicine II, University Hospital Ulm, Ulm, Germany.
  • Brucher R; Faculty of Medical Engineering, University of Applied Science Ulm, Ulm, Germany.
  • Rottbauer W; Department of Internal Medicine II, University Hospital Ulm, Ulm, Germany.
J Clin Sleep Med ; 13(10): 1123-1130, 2017 Oct 15.
Article in En | MEDLINE | ID: mdl-28859722
ABSTRACT
STUDY

OBJECTIVES:

The current gold standard for assessment of obstructive sleep apnea is the in-laboratory polysomnography. This approach has high costs and inconveniences the patient, whereas alternative ambulatory systems are limited by reduced diagnostic abilities (type 4 monitors, 1 or 2 channels) or extensive setup (type 3 monitors, at least 4 channels). The current study therefore aims to validate a simplified automated type 4 monitoring system using tracheal body sound and movement data.

METHODS:

Data from 60 subjects were recorded at the University Hospital Ulm. All subjects have been regular patients referred to the sleep center with suspicion of sleep-related breathing disorders. Four recordings were excluded because of faulty data. The study was of prospective design. Subjects underwent a full-night screening using diagnostic in-laboratory polysomnography and the new monitoring system concurrently. The apnea-hypopnea index (AHI) was scored blindly by a medical technician using in-laboratory polysomnography (AHIPSG). A unique algorithm was developed to estimate the apneahypopnea index (AHIest) using the new sleep monitor.

RESULTS:

AHIest strongly correlates with AHIPSG (r2 = .9871). A mean ± 1.96 standard deviation difference between AHIest and AHIPSG of 1.2 ± 5.14 was achieved. In terms of classifying subjects into groups of mild, moderate, and severe sleep apnea, the evaluated new sleep monitor shows a strong correlation with the results obtained by polysomnography (Cohen kappa > 0.81). These results outperform previously introduced similar approaches.

CONCLUSIONS:

The proposed sleep monitor accurately estimates AHI and diagnoses sleep apnea and its severity. This minimalistic approach may address the need for a simple yet reliable diagnosis of sleep apnea in an ambulatory setting. CLINICAL TRIAL REGISTRATION Trial name Validation of a new method for ambulant diagnosis of sleep related breathing disorders using body sound; URL https//drks-neu.uniklinik-freiburg.de/drks_web/navigate.do?navigationId=trial.HTML&TRIAL_ID=DRKS00011195; Identifier DRKS00011195.
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Trachea / Respiratory Sounds / Sleep Apnea, Obstructive / Monitoring, Physiologic Type of study: Diagnostic_studies / Observational_studies / Prognostic_studies Limits: Female / Humans / Male / Middle aged Language: En Journal: J Clin Sleep Med Year: 2017 Document type: Article Affiliation country: Germany

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Trachea / Respiratory Sounds / Sleep Apnea, Obstructive / Monitoring, Physiologic Type of study: Diagnostic_studies / Observational_studies / Prognostic_studies Limits: Female / Humans / Male / Middle aged Language: En Journal: J Clin Sleep Med Year: 2017 Document type: Article Affiliation country: Germany