Snoring detection using a piezo snoring sensor based on hidden Markov models.
Physiol Meas
; 34(5): N41-9, 2013 May.
Article
em En
| MEDLINE
| ID: mdl-23587724
ABSTRACT
This study presents a snoring detection method based on hidden Markov models (HMMs) using a piezo snoring sensor. Snoring is a major symptom of obstructive sleep apnea (OSA). In most sleep studies, snoring is detected with a microphone. Since these studies analyze the acoustic properties of snoring, they need to acquire data at high sampling rates, so a large amount of data should be processed. Recently, several sleep studies have monitored snoring using a piezo snoring sensor. However, an automatic method for snoring detection using a piezo snoring sensor has not been reported in the literature. This study proposed the HMM-based method to detect snoring using this sensor, which is attached to the neck. The data from 21 patients with OSA were gathered for training and test sets. The short-time Fourier transform and short-time energy were computed so they could be applied to HMMs. The data were classified as snoring, noise and silence according to their HMMs. As a result, the sensitivity and the positive predictivity values were 93.3% and 99.1% for snoring detection, respectively. The results demonstrated that the method produced simple, portable and user-friendly detection tools that provide an alternative to the microphone-based method.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Ronco
/
Apneia Obstrutiva do Sono
Tipo de estudo:
Diagnostic_studies
/
Health_economic_evaluation
/
Prognostic_studies
Limite:
Adult
/
Aged
/
Humans
/
Middle aged
Idioma:
En
Ano de publicação:
2013
Tipo de documento:
Article