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Accuracy Assessment of Sleep Monitoring Technology

To Evaluate the Accuracy of Sleep Parameters Evaluated by Wearable Sleep Devices

Status
UNKNOWN
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT05636930
Enrollment
50
Registered
2022-12-05
Start date
2022-10-01
Completion date
2022-12-30
Last updated
2022-12-05

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Wearable Devices

Brief summary

As a necessary process of life, sleep is an important link for the body to recover, integrate and consolidate memory. However, the fast pace of life in modern society and people's bad living habits are easy to cause sleep disorders. Sleep disorders are often the main factors that induce or aggravate cardiovascular and cerebrovascular diseases. Sleep staging is an important basis for sleep quality assessment and related disease diagnosis. At present, electroencephalography (EEG) has become the gold standard for judging sleep stages. However, this kind of method requires long-term contact of multiple electrodes with the human body, which is easy to affect the natural sleep of the subjects, so it is not suitable for sleep monitoring in home environment. Studies have shown that sleep is related to the regulation of autonomic nervous system, and heart rate variability (HRV) in sleep also shows periodic changes similar to brain waves. Smartwatch/bracelet can continuously monitor the user's pulse wave and acceleration data comfortably and without feeling. HRV features can be extracted using pulse wave data, and then sleep staging can be realized based on the correlation between HRV and brain waves, and sleep quality can be evaluated. Therefore, healthy sleep research aims to use smart devices to achieve sleep monitoring in the home environment and improve people's sleep quality

Interventions

OTHERTest the accuracy of the wearable device

No intervention was done for the subjects

Sponsors

Shanshan Lu
Lead SponsorOTHER

Study design

Observational model
OTHER
Time perspective
CROSS_SECTIONAL

Eligibility

Sex/Gender
ALL
Age
18 Years to 60 Years
Healthy volunteers
Yes

Inclusion criteria

* a. Adults aged 18 and above and under the age of 60; The age of the subjects was divided into two age groups: 18-44, 45-60, and the ratio between the two groups was 1:1.2-1:0.8. The ratio of female to male is between 1:1.1 and 1:1.0; b. No patients with serious cardiovascular and cerebrovascular diseases, moderate degree of depression, anxiety disorder or severe apnea; HAMD\<=20;HAMA \<=13;AHI\< 30 c. Subjects did not drink alcohol or take sleep intervention drugs during the program; d. People with sleep disorders and insomnia can be included in the subjects, but the total number is no more than 50%, and should be clearly marked; e. Having Chinese nationality and residing in China; f. Agree to be monitored by PSG and wear wearable devices; Voluntary entry, informed consent or consent to privacy agreement.

Exclusion criteria

* a. Patients with a history of depression, anxiety and other mental disorders; HAMD\>20;HAMA\>13 b. Patients with existing atherosclerotic cardiovascular diseases, such as coronary heart disease and severe peripheral atherosclerotic disease; c. age \>60 d. Patients with obstructive sleep apnea (AHI \>30); Use of drugs or substances affecting the central nervous system in the preceding 2 weeks.

Design outcomes

Primary

MeasureTime frameDescription
Accuracy of sleep parameters of wearable devices8-10AMSleep Latency,sleep efficiency

Countries

China

Contacts

Primary ContactShanShanLu S Lu
lushanshan819@163.com86515963126547

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026