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A study on the application of artificial intelligence snoring loudness model in screening for obstructive sleep apnea in adults

A study on the application of artificial intelligence snoring loudness model in screening for obstructive sleep apnea in adults

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500100708
Enrollment
Unknown
Registered
2025-04-14
Start date
2025-04-30
Completion date
Unknown
Last updated
2025-04-21

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Obstructive sleep apnoea is characterised by repetitive episodes of apnoea or hypopnea that are caused by upper airway obstruction occurring during sleep. These events often result in reductions in blood oxygen saturation and are usually terminated by brief arousals from sleep. Excessive sleepiness is a major presenting complaint in many but not all cases. Reports of insomnia, poor sleep quality,

Interventions

Patients with mild OSA:None
Patients with moderate OSA:None
Patients with severe OSA:None
People without the disease:None

Sponsors

Shanghai Stomatological Hospital, Fudan University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
3 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1.People aged 6-80 years; 2.People with or without usual symptoms of OSA; 3.People who were interested in PSG monitoring and who voluntarily signed an informed consent form.

Exclusion criteria

Exclusion criteria: 1.Patients who are unable to undergo PSG monitoring.

Design outcomes

Primary

MeasureTime frame
The number of problematic frames was recorded after processing the snoring data using the snoring recognition model and compared to a frame count threshold of 0.2;

Countries

China

Contacts

Public ContactJie Pan

Shanghai Stomatological Hospital, Fudan University

shuimupanda@sina.cn+86 21 6360 1894

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026