Acoustic analyses of snoring sounds using a smartphone in patients undergoing septoplasty and turbinoplasty
Purpose Several studies have been performed using recently developed smartphone-based acoustic analysis techniques. We investigated the effects of septoplasty and turbinoplasty in patients with nasal septal deviation and turbinate hypertrophy accompanied by snoring by recording the sounds of snoring...
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Veröffentlicht in: | European archives of oto-rhino-laryngology 2021, Vol.278 (1), p.257-263 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Purpose
Several studies have been performed using recently developed smartphone-based acoustic analysis techniques. We investigated the effects of septoplasty and turbinoplasty in patients with nasal septal deviation and turbinate hypertrophy accompanied by snoring by recording the sounds of snoring using a smartphone and performing acoustic analysis.
Methods
A total of 15 male patients who underwent septoplasty with turbinoplasty for snoring and nasal obstruction were included in this prospective study. Preoperatively and 2 months after surgery, their bed partners or caregivers were instructed to record the snoring sounds. The intensity (dB), formant frequencies (F
1
, F
2
, F
3
, and F
4
), spectrogram pattern, and visual analog scale (VAS) score were analyzed for each subject.
Results
Overall snoring sounds improved after surgery in 12/15 (80%) patients, and there was significant improvement in the intensity of snoring sounds after surgery (from 64.17 ± 12.18 dB to 55.62 ± 9.11 dB,
p
= 0.018). There was a significant difference in the F
1
formant frequency before and after surgery (
p
= 0.031), but there were no significant differences in F
2
, F
3
, or F
4
. The change in F
1
indicated that patients changed from mouth breathing to normal breathing. The degree of subjective snoring sounds improved significantly after surgery (VAS: from 5.40 ± 1.55 to 3.80 ± 1.26,
p
= 0.003).
Conclusion
Our results confirm that snoring is reduced when nasal congestion is improved, and they demonstrate that smartphone-based acoustic analysis of snoring sounds can be useful for diagnosis. |
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ISSN: | 0937-4477 1434-4726 |
DOI: | 10.1007/s00405-020-06268-1 |