Skip to content

Improvement the accuracy of sleep bruxism identification

Improvement the accuracy of sleep bruxism identification - Improvement the accuracy of sleep bruxism identification

Status
Active, not recruiting
Phases
Unknown
Study type
Interventional
Source
JPRN
Registry ID
JPRN-UMIN000041169
Enrollment
12
Registered
2020-07-21
Start date
2020-08-26
Completion date
Unknown
Last updated
2026-06-29

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

Conditions

sleep bruxism

Interventions

In the supine position, subjects are asked to bite and tighten at the molars. Continue this task for 10 seconds and perform it 3 times. Rest for 20 seconds between each task. In the supine position, s

Sponsors

Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Department of Oral Rehabilitation and Regenerative Medicine
Lead Sponsor
The university of Tokyo Graduate School of Engineering,
Collaborator

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: A healthy person who is willing to participate and have obtained the consent of the research.

Exclusion criteria

Exclusion criteria: subject who is malocclusion or receiving the dynamic orthodontic treatment Those who have taken sleep or masticatory muscle movements within the past 6 months (psychotropic drugs (antipsychotics, mood stabilizers, antidepressants, anxiolytics, sleeping pills)) Those who have abused substances within the past 6 months Those who cannot refrain from drinking on the day of inspection Those who have smoked within the last 6 months

Design outcomes

Primary

MeasureTime frame
After obtaining the EMG of true bruxism and bruxism like muscle hyper activity events, these will be compared and analyzed by the hidden Markov model. Then, Mel Frequency Cepstral Coefficient will be calculated individually.

Secondary

MeasureTime frame
After obtaining the auscultatory sound of true bruxism and bruxism like muscle hyper activity events, these will be compared and analyzed by fast Fourier transform. Then specific frequency that can distinguish between the true bruxism and bruxism like muscle hyperactivity events will be evaluated. the hidden Markov model. Then, Mel Frequency Cepstral Coefficient will be calculated individually.

Countries

Japan

Contacts

Public ContactHajime Minakuchi

Okayama University Hospital Crown Bridge Prosthetics and Oral Implantology Department

hajime@md.okayama-u.ac.jp086-235-6682

Outcome results

None listed

Source: JPRN (via WHO ICTRP) · Data processed: Jul 3, 2026