Not provided
Not provided
Not provided
| ID | Type | Description | Link |
|---|---|---|---|
| N202303101 | Other Identifier | TMU-Joint Institutional Review Board |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
The clinical study aims to develop and validate the TipTraQ system, created by PranaQ, a home sleep test for sleep apnea screening. The system comprises a wearable device and a cloud-based AI for estimating Total Sleep Time (TST) and Apnea-Hypopnea Index (AHI).
Sleep-disordered breathing is a common disease that affects life function and quality of life, and it also imposes a great burden on the public health system. Obstructive sleep apnea accounts for the largest proportion of sleep-disordered breathing, and because of the oriental facial structure, the prevalence of sleep-disordered breathing is relatively high. The current gold standard for diagnosis OSA is polysomnography (PSG). Although the physiological information collected by PSG is complete and detailed, it requires a considerable amount of manpower and medical resources, and changes in the sleep environment also cause bias in the accuracy of inspection. So far, the tools for simple and accurate screening and diagnosis OSA are relatively limited. In this study, TipTraQ, a wearable device developed by PranaQ, was used to collect photoplethysmography (PPG) of patients during the night of PSG inspection. The reliability and validity analysis was carried out by comparing with the corresponding indicators of PSG, and the feasibility of TipTraQ as a tool for home sleep test (HST).
Not provided
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Healthy or people who has indication to conduct polysomnography (PSG). |
Not provided
| Measure | Description | Time Frame |
|---|---|---|
| Apnea Hypopnea Index(AHI) | The combined average number of apneas and hypopneas that occur per hour of sleep | From the start of a single polysomnography study to the end of the recording, 1 night. |
| Oxygen Desaturation Index(ODI) | Average desaturation episodes with a decrease in the oxygen saturation of ≥4% or 3% per hour | From the start of a single polysomnography study to the end of the recording, 1 night. |
| Total Sleep Time(TST) | Total sleep time during the polysomnography (PSG) | From the start of a single polysomnography study to the end of the recording, 1 night. |
Not provided
Not provided
Inclusion Criteria:
Subjects from the age of 20 and older that have an indication for an in-lab PSG study.
Exclusion Criteria:
Not provided
Not provided
Healthy or people who has indication to conduct polysomnography (PSG).
Not provided
Not provided
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Taipei Medical University-Shuang Ho Hospital,Ministry of Health and Welfare | New Taipei City | Taiwan | 23561 | Taiwan |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 39821673 | Derived | Chen KW, Tseng CH, Lee HC, Liu WT, Chou KT, Wu HT. Validation of a fingertip home sleep apnea testing system using deep learning AI and a temporal event localization analysis. Sleep. 2025 May 12;48(5):zsae317. doi: 10.1093/sleep/zsae317. |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D020181 | Sleep Apnea, Obstructive |
| ID | Term |
|---|---|
| D012891 | Sleep Apnea Syndromes |
| D001049 | Apnea |
| D012120 | Respiration Disorders |
| D012140 | Respiratory Tract Diseases |
Not provided
Not provided
Not provided
Not provided
Not provided
| D020919 |
| Sleep Disorders, Intrinsic |
| D020920 | Dyssomnias |
| D012893 | Sleep Wake Disorders |
| D009422 | Nervous System Diseases |