Obstructive Sleep Apnea Syndrome
Conditions
Keywords
Polysomnography, sleep staging, sleep efficiency, wearable devices, smart watches
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.
Interventions
DEVICEsmart watches(wearable devices)
Participants will be asked to wear two smart watches simultaneously. The first smart watch is a dedicated prototype for validating algorithm developed by MediaTek. The second smart watch is Basis Peak. These watches are going to acquire PPG, body movements, skin temperature, and skin conductance.
Sponsors
National Taiwan University Hospital
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
DIAGNOSTIC
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
20 Years to 65 Years
Healthy volunteers
Yes
Inclusion criteria
1. Forty male or female subjects are recruited from those visiting Department of Medicine for health check up 2. Subjects aged 20 to 65
Exclusion criteria
1. Refuse to participate 2. Arrhythmia 3. Active infection 4. Active neurologic event 5. Shift worker 6. Substance abuse 7. Fitted with implantable medical electronics, such as cardiac pacemakers and defibrillators
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| sleep stages derived from smartwatch | 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
| Measure | Time frame | Description |
|---|---|---|
| sleep efficiency derived from smartwatch | 12 months | Comparing sleep efficiency(%) detected by a smartwatch with the sleep efficiency(%) from an overnight PSG to validate the effectiveness of the smartwatch. |
Countries
Taiwan
Outcome results
None listed