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临床试验/NCT04208672
NCT04208672Unknown不适用

Validation of a Handy Sleep Monitoring Device: UMindSleep in Patients With Obstructive Sleep Apnea

Chinese University of Hong Kong1 个研究点 分布在 1 个国家目标入组 100 人开始时间: 2020年1月16日最近更新:
适应症

试验速览

阶段
不适用
入组人数
100
试验地点
1
主要终点
sleep apnea

研究概览

简要总结

This is a validation study recruiting subjects with and without obstructive sleep apnea. All subjects will undergo a nocturnal standard polysomnography and UMindSleep assessment. Sleep parameters, such as sleep stages and apnea UMindSleep software. Correlation in each parameter between PSG and events in polysomnography (PSG) will be scored according to the AASM criteria while the sleep parameters will be automatically scored by the UMindSleep will be analyzed to determine the magnitude of agreement between UMindSleep and PSG.

详细描述

Obstructive sleep apnea (OSA) is a common sleep disorder in the general population with a prevalence ranging from 4-30%. OSA has been shown to be a significant risk factor of many cardiovascular diseases and mental disorders. However, OSA is a neglected problem in the general population. In addition, there is a significant unmet need for the treatment of OSA. One of the major reason for the under-diagnosis and under-treatment of OSA in the general population is a lack of reliable screening tool in detecting OSA. In this regard, several devices, such as ApneaLink, have been developed for the screening of OSA. However, as this kind of device only employs time in bed rather than actual sleep time to calculate the apnea index or desaturation index, they tend to underestimate the severity of sleep apnea. In this regard, it is timely need to develop and validate new device that can integrate the actual sleep time and apnea or desaturation events for the precise calculation of sleep apnea index or desaturation index.

The UMindSleep is a handy and wearable device to acquire EEG, heart rate, saturation, snoring and temperature. The signal will be uploaded to a smartphone through Bluetooth. By integrating these signals, the system can automatically analyze several key parameters by the algorithms, such as sleep stages and desaturation events.

研究设计

研究类型
Interventional
分配方式
Na
干预模型
Single Group
主要目的
Diagnostic
盲法
None

入排标准

年龄范围
18 Years 至 65 Years(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • complain of habitual snoring;
  • AHI as measured by standard PSG > 5/hour

排除标准

  • Aged 17 years old or below
  • patients with narcolepsy and REM sleep behavior disorder

结局指标

主要结局

sleep apnea

时间窗: 6 months

The correlation of Sleep staging and Apnea-hyponea index measured by PSG and UMindSleep will be measured.

次要结局

未报告次要终点

研究者

申办方类型
Other
责任方
Principal Investigator
主要研究者

Dr. Zhang Jihui

Assistant Professor

Chinese University of Hong Kong

研究点 (1)

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