Validation Study of Sleep Tracking Devices

NCT06357039 | Completed

• 3 other identifiers: 09.2023.42222201241065371
• Study Type: observational
• Target: 305
• Locations: 1 country
• Sites: 1

Brief 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.

Conditions

Sleep; Sleep Disorder

Keywords

Sleep; Polysomnography; EEG; PPG; Wearable Device

Outcome Measures

Primary Outcomes (2)

• 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

Study Arms (2)

Female

Participants aged 18-65 who identify as female for biological

Device: Sleep tracking device

Male

Participants aged 18-65 who identify as male for biological

Device: Sleep tracking device

Interventions

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.

Female; Male

Eligibility Criteria

• Age: 18 Years - 65 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

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.

You may qualify if:

• Participants suffering from sleep disorders
• Participants sent to PSG test by neurologists, pulmonologists, psychiatrists, and otolaryngologists

You may not qualify if:

• Anyone who has been diagnosed as having a contagious skin disease
• Participants who do not have consent to have an additional device in their forehead area
• Incomplete of sleep measurement

Sponsors & Collaborators

• PNAPS Health Informatics and Space Technologies Inc.: lead
• Analog Devices: collaborator

Study Sites (1)

Pnaps Health Informatics and Space Technologies Inc

Istanbul, Başıbüyük, Maltepe, 34854, Turkey (Türkiye)

Location

MeSH Terms

Conditions

Sleep Wake Disorders

Condition Hierarchy (Ancestors)

Nervous System Diseases; Neurologic Manifestations; Signs and Symptoms; Pathological Conditions, Signs and Symptoms; Mental Disorders

Study Officials

• Asuman Çevik, Master's

  PNAPS Health Informatics & Space Technologies Inc.

  STUDY CHAIR

• Hasan Birol Çotuk, PhD

  Marmara University

  STUDY DIRECTOR

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: February 22, 2024
• First Posted: April 10, 2024
• Study Start: March 21, 2023
• Primary Completion: May 31, 2023
• Study Completion: July 17, 2023
• Last Updated: April 25, 2024

Record last verified: 2024-04

Locations

TU (1)