Validation of Sleep Monitoring Algorithm Based on Smart Watches
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Obstructive Sleep Apnea Syndrome
- Sponsor
- National Taiwan University Hospital
- Enrollment
- 35
- Locations
- 1
- Primary Endpoint
- sleep stages derived from smartwatch
- Status
- Completed
- Last Updated
- last year
Overview
Brief Summary
In recent years, wearable devices are booming to enable not only the health monitoring but also the sleep efficiency assessment. To validate the algorithm of sleep staging and efficiency, this study will use a dedicated prototype to acquire photoplethysmogram (PPG), body movements, skin temperature, and galvanic skin response by recruiting 35 subjects. PSG will be used as gold standard for statistical analysi.
Detailed Description
Sleep efficiency has a great impact on the performance of work and learning during the day. If persons lack of sleep for a long time, they might be prone to memory loss and emotional instability. Traditionally, polysomnography (PSG) has been proved as golden results to assess the sleep efficiency. However, to accomplish the assessment, subjects are asked to sleep in a certified sleep laboratory or a sleep centers for nights. Under the supervision of nurses, subjects are put many adhesive electrodes on the body and connect wires to PSG, which causes discomfort. In recent years, wearable devices are booming to enable not only the health monitoring but also the sleep efficiency assessment. To validate the algorithm of sleep staging and efficiency, this study will use a dedicated prototype to acquire photoplethysmogram (PPG), body movements, skin temperature, and galvanic skin response by recruiting 35 subjects. PSG will be used as gold standard for statistical analysi.
Investigators
Eligibility Criteria
Inclusion Criteria
- •Forty male or female subjects are recruited from those visiting Department of Medicine for health check up
- •Subjects aged 20 to 65
Exclusion Criteria
- •Refuse to participate
- •Active infection
- •Active neurologic event
- •Shift worker
- •Substance abuse
- •Fitted with implantable medical electronics, such as cardiac pacemakers and defibrillators
Outcomes
Primary Outcomes
sleep stages derived from smartwatch
Time Frame: 12 months
Comparing sleep stages detected by a smartwatch(hh:mm) with the sleep stages of an overnight PSG(N1 (%), N2 (%), N3 (%), REM(%), Arousal index (/h) to validate the effectiveness of the smartwatch.
Secondary Outcomes
- sleep efficiency derived from smartwatch(12 months)