Preliminary study for the personal handheld device based snoring detection in ordinary sleep situation

Shin, Hyunki; Choi, Wangrim; Kim, Yi-Gon; Cho, Jaegeol

doi:10.1109/embc.2014.6944423

Cited by 2 publications

(2 citation statements)

References 9 publications

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“…Many sleep monitoring systems now integrate ambient sound acquisition to help people analyze the causes of poor sleep. Some sounds may prevent a person from falling asleep, while white noise has shown sleep-aiding effects in many studies [ 202 ]. Chen et al integrated ambient sound sensors into the sleep monitoring system, which automatically plays white noise to mask the noise affecting people’s sleep when ambient noise is detected, and the body sensors in the system monitor sleep quality in real time [ 203 ].…”

Section: Biomechanical Signal Monitoringmentioning

confidence: 99%

“…If just collecting the sound in the room, perhaps no special equipment is needed. Snoring signals have strong penetration, so sensing these can often be implemented directly with the help of a smartphone [ 202 ]. Xin et al prepared acoustic sensors using flexible piezoelectric films to detect snoring, but there is no significant advantage over existing integrated microphones [ 144 , 204 ].…”

Section: Biomechanical Signal Monitoringmentioning

confidence: 99%

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Recent Progress in Long-Term Sleep Monitoring Technology

Yin

Ren

2023

Biosensors

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Sleep is an essential physiological activity, accounting for about one-third of our lives, which significantly impacts our memory, mood, health, and children’s growth. Especially after the COVID-19 epidemic, sleep health issues have attracted more attention. In recent years, with the development of wearable electronic devices, there have been more and more studies, products, or solutions related to sleep monitoring. Many mature technologies, such as polysomnography, have been applied to clinical practice. However, it is urgent to develop wearable or non-contacting electronic devices suitable for household continuous sleep monitoring. This paper first introduces the basic knowledge of sleep and the significance of sleep monitoring. Then, according to the types of physiological signals monitored, this paper describes the research progress of bioelectrical signals, biomechanical signals, and biochemical signals used for sleep monitoring. However, it is not ideal to monitor the sleep quality for the whole night based on only one signal. Therefore, this paper reviews the research on multi-signal monitoring and introduces systematic sleep monitoring schemes. Finally, a conclusion and discussion of sleep monitoring are presented to propose potential future directions and prospects for sleep monitoring.

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Section: Biomechanical Signal Monitoringmentioning

confidence: 99%

Section: Biomechanical Signal Monitoringmentioning

confidence: 99%

Recent Progress in Long-Term Sleep Monitoring Technology

Yin

Ren

2023

Biosensors

View full text Add to dashboard Cite

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Acoustic analysis of snoring sounds recorded with a smartphone according to obstruction site in OSAS patients

Koo¹,

Kwon

Kim³

et al. 2016

Eur Arch Otorhinolaryngol

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Snoring is a sign of increased upper airway resistance and is the most common symptom suggestive of obstructive sleep apnea. Acoustic analysis of snoring sounds is a non-invasive diagnostic technique and may provide a screening test that can determine the location of obstruction sites. We recorded snoring sounds according to obstruction level, measured by DISE, using a smartphone and focused on the analysis of formant frequencies. The study group comprised 32 male patients (mean age 42.9 years). The spectrogram pattern, intensity (dB), fundamental frequencies (F ), and formant frequencies (F, F , and F) of the snoring sounds were analyzed for each subject. On spectrographic analysis, retropalatal level obstruction tended to produce sharp and regular peaks, while retrolingual level obstruction tended to show peaks with a gradual onset and decay. On formant frequency analysis, F (retropalatal level vs. retrolingual level: 488.1 ± 125.8 vs. 634.7 ± 196.6 Hz) and F (retropalatal level vs. retrolingual level: 1267.3 ± 306.6 vs. 1723.7 ± 550.0 Hz) of retrolingual level obstructions showed significantly higher values than retropalatal level obstruction (p < 0.05). This suggests that the upper airway is more severely obstructed with retrolingual level obstruction and that there is a greater change in tongue position. Acoustic analysis of snoring is a non-invasive diagnostic technique that can be easily applied at a relatively low cost. The analysis of formant frequencies will be a useful screening test for the prediction of occlusion sites. Moreover, smartphone can be effective for recording snoring sounds.

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Preliminary study for the personal handheld device based snoring detection in ordinary sleep situation

Cited by 2 publications

References 9 publications

Recent Progress in Long-Term Sleep Monitoring Technology

Recent Progress in Long-Term Sleep Monitoring Technology

Acoustic analysis of snoring sounds recorded with a smartphone according to obstruction site in OSAS patients

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