Validation Study of Sleep Tracking Devices

Sleep Clinical Trial

Official title: Validation Study of an Artificial Intelligence-based Sleep Stage Classification for a Home Sleep Tracking Device

Status Completed

Clinical Trial Summary

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.

Clinical Trial Description

n/a

Related Conditions & MeSH terms

• Sleep
• Sleep Disorder
• Sleep Wake Disorders

• NCT number: NCT06357039
• Study type: Observational
• Source: PNAPS Health Informatics and Space Technologies Inc.
• Status: Completed
• Start date: March 21, 2023
• Completion date: July 17, 2023