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| ID | Type | Description | Link |
|---|---|---|---|
| 2220124 | Other Grant/Funding Number | Scientific and Technological Research Council of Türkiye (TÜBİTAK) | |
| 1065371 | Other Grant/Funding Number | Small and Medium Enterprises Development Organization (KOSGEB) |
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| Name | Class |
|---|---|
| Analog Devices | UNKNOWN |
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In this study, a two-part recursive convolutional neural networks model was developed, extracting features for each epoch window independently from before and after sleep onset (epoch encoder), and then trained in the context of long-term relationships in the sleep process (sequence encoder), using an approach similar to human expert classification based on information from single-channel forehead EEG and PPG (IR, Green, Red). The classification is based on guidelines from the American Academy of Sleep Medicine and calculated six parameters: total sleep duration (TST), wake (W), N1, N2, N3, and REM.
The validation study of the developed model and the device was conducted at the Sleep Disorders Centre of the Istanbul Medical Faculty using concurrent polysomnographic data from 305 male and female patients aged 18 to 65 years.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Female | Participants aged 18-65 who identify as female for biological |
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| Male | Participants aged 18-65 who identify as male for biological |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Sleep tracking device | Device | In addition to polysomnography, a device containing EEG+PPG sensors for sleep classification was placed on the forehead, and another device containing PPG and accelerometer sensors was placed on the wrist. The wrist to which the device is attached is randomly assigned. |
| Measure | Description | Time Frame |
|---|---|---|
| Sleep Stages Classification Accuracy | The collected EEG data were classified according to Cohen's kappa (>85), which is considered successful in the literature. Initially the open source codes YASA, tinysleepnet and attentionsleep have been implemented. These codes yielded kappa 0.64, accuracy 0.80, kappa 0.69, accuracy 0.79 and kappa 0.65, accuracy 0.78 respectively. The values obtained do not correspond to those reported in the classification articles. Subsequently, 29 participants from our own dataset were tested in these classifications as a preliminary test, with poor results. On an individual basis, the highest cappa score was 0.51. Development of our own classification system is in progress. | 4-5 months |
| Interoception analysis from PPG data collected from facial skin | According to our preliminary analyses, we found that the intermediary rhythm (0.12-0.18 Hz) associated with interoception is also present in sleep patients. In one participant, for example, a value of 0.19 was obtained as a ratio of total sleep time. In addition, an intermediary rhythm is observed in all stages of sleep, including wakefulness, light sleep, deep sleep and REM. | 4-5 months |
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Inclusion Criteria:
Exclusion Criteria:
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The study population includes individuals aged between 18 and 65 who have voluntarily agreed to undergo sleep measurements specifically individuals suffering from sleep disorders such as sleep apnea. Participants in the study have been referred for polysomnography (PSG) testing by neurologists, pulmonologists, psychiatrists, and otolaryngologists.
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| Name | Affiliation | Role |
|---|---|---|
| Asuman Çevik, Master's | PNAPS Health Informatics & Space Technologies Inc. | Study Chair |
| Hasan Birol Çotuk, PhD | Marmara University | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Pnaps Health Informatics and Space Technologies Inc | Istanbul | Başıbüyük, Maltepe | 34854 | Turkey (Türkiye) |
The PSG data will be shared, but the main structure is not yet planned.
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot | Yes | No | No | Study Protocol | Mar 9, 2023 | Apr 4, 2024 | Prot_000.pdf |
| ICF | No | No | Yes | Informed Consent Form | Mar 9, 2023 | Apr 4, 2024 | ICF_001.pdf |
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| ID | Term |
|---|---|
| D012893 | Sleep Wake Disorders |
| ID | Term |
|---|---|
| D009422 | Nervous System Diseases |
| D009461 | Neurologic Manifestations |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
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| D001523 | Mental Disorders |