Computerized analysis of snoring in sleep apnea syndrome

Shiomi, Fabio Koiti; Pisa, Ivan Torres; Campos, Carlos José Reis de

doi:10.1590/s1808-86942011000400013

Cited by 11 publications

(9 citation statements)

References 17 publications

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“…The les were records taken every 600 s. Dominant frequencies for each 0.01-s segment were analyzed and plotted. Simultaneously, Hilbert amplitude envelopes were smoothed using a sample-moving average of 1000 samples with a 25% overlapping sliding window [9,10,19,20]. Visualization revealed that the clustered snores in the amplitude domains generally exhibited nearisometric spikes with a trend of initial ascension and subsequent descension.…”

Section: Snoring Rates Obtained Using Our Dependable Algorithmmentioning

confidence: 99%

Dependable Algorithm for Visualizing Snoring Duration Through Acoustic Analysis

Kao

Lin²,

Kao

et al. 2020

Preprint

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Background: Snoring is a nuisance for the bed partners of people who snore and is also associated with chronic diseases. Estimating the snoring duration from a whole-night-sleep period is challenging. We present a dependable algorithm for visualizing snoring durations through acoustic analysis.Method: Both instruments (Sony digital recorder and smartphone’s SnoreClock app) were placed within 30 cm from the examinee’s head during the sleep period. Subsequently, spectrograms were plotted based on audio files recorded from Sony recorders. We developed an algorithm to validate snoring durations through visualization of typical snoring segments.Results: In total, 37 snoring recordings obtained from six individuals were analyzed. The mean age of the participants was 44.6 ± 9.9 years. A 3-s segment demonstrated the typical dominant frequency bands and amplitude waves of two snores. Every recorded file was tailored to a regular 600-s segment and plotted. Visualization revealed that the typical features of the clustered snores in the amplitude domains were near-isometric spikes (most had an ascending–descending trend). The recorded snores exhibited one or more visibly fixed frequency bands. Intervals were noted between the snoring clusters and were incorporated into the whole-night snoring calculation. The correlative coefficients of snoring rates of digitally recorded files examined by Examiners A and B were higher (0.865, p < 0.001) than those with SnoreClock app (0.757, p < 0.001; 0.787, p < 0.001, respectively).Conclusion: A dependable algorithm with high reproducibility was developed for visualizing snoring durations.

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Section: Snoring Rates Obtained Using Our Dependable Algorithmmentioning

confidence: 99%

Dependable Algorithm for Visualizing Snoring Duration Through Acoustic Analysis

Kao

Lin²,

Kao

et al. 2020

Preprint

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“…Embletta MPR microphone (an analog omnidirectional condenser microphone) attached to nasal cannula will record the snoring sounds. All signals will be fed into analog/digital (A/D) converter with a 200 Hz sampling rate (each channel has 200 points or samples per second; Shiomi et al, 2011 ). For optimal visualization of snoring, a high-pass filter to remove very low frequencies (20 Hz) and a low-pass filter to remove high frequencies (3 kHz) will be used, this will permit acquiring relevant information of snoring sounds (Pevernagie et al, 2010 ).…”

Section: Outcome Measurements and Stepwise Proceduresmentioning

confidence: 99%

Efficacy of a Mandibular Advancement Appliance on Sleep Disordered Breathing in Children: A Study Protocol of a Crossover Randomized Controlled Trial

et al. 2016

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Background: Sleep-Disordered Breathing (SDB) varies from habitual snoring to partial or complete obstruction of the upper airway and can be found in up to 10% of children. SDB can significantly affect children's wellbeing, as it can cause growth disorders, educational and behavioral problems, and even life-threatening conditions, such as cardiorespiratory failure. Adenotonsillectomy represents the primary treatment for pediatric SDB where adeno-tonsillar hypertrophy is indicated. For those with craniofacial anomalies, or for whom adenotonsillectomy or other treatment modalities have failed, or surgery is contra-indicated, mandibular advancement splints (MAS) may represent a viable treatment option. Whilst the efficacy of these appliances has been consistently demonstrated in adults, there is little information about their effectiveness in children.Aims: To determine the efficacy of mandibular advancement appliances for the management of SDB and related health problems in children.Methods/design: The study will be designed as a single-blind crossover randomized controlled trial with administration of both an “Active MAS” (Twin-block) and a “Sham MAS.” Eligible participants will be children aged 8–12 years whose parents report they snore ≥3 nights per week. Sixteen children will enter the full study after confirming other inclusion criteria, particularly Skeletal class I or class II confirmed by lateral cephalometric radiograph. Each child will be randomly assigned to either a treatment sequence starting with the Active or the Sham MAS. Participants will wear the appliances for 3 weeks separated by a 2-week washout period. For each participant, home-based polysomnographic data will be collected four times; once before and once after each treatment period. The Apnea Hypopnea Index (AHI) will represent the main outcome variable. Secondary outcomes will include, snoring frequency, masseter muscle activity, sleep symptoms, quality of life, daytime sleepiness, children behavior, and nocturnal enuresis. In addition, blood samples will be collected to assess growth hormone changes.Trial registration: This study was registered in the Australian New Zealand Clinical Trials Registry (ANZCTR): [ACTRN12614001013651].

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“…In addition, it records how much air moves in and out of the lungs during sleep and the amount of oxygen in the blood [10,11]. It records what happens with breathing during sleeping.…”

Section: Introductionmentioning

confidence: 99%