Pulse Diagnosis Thai Traditional Medicine Cardiovascular Physiology Artificial Intelligence in Medicine Pulse Examination Thai Traditional Medicine Artificial Intelligence Machine Learning Medical Device Pulse Wave Analysis Digital Health Biosensor Signal Processing Cardiovascular Monitoring
Conditions
Interventions
Healthy volunteers aged 18 to 70 years without acute medical conditions who undergo pulse examination using the AI based pulse detection device according to Thai Traditional Medicine. Pulse signals fr
Diagnostic,Diagnostic
Healthy Participants,Participants with Underlying Diseases
Sponsors
None listed
Eligibility
Sex/Gender
All
Age
18 Years to 70 Years
Inclusion criteria
Inclusion criteria: 1.Participants aged 18 to 70 years 2.Able to provide written informed consent 3.Able to complete pulse examination procedures according to study protocol
Exclusion criteria
Exclusion criteria: 1.Known cardiac arrhythmia including atrial fibrillation frequent ectopic beat or pacemaker rhythm 2.Critically ill participants or participants unable to cooperate with the study 3.Acute illness on the examination day such as fever diarrhea or acute inflammatory conditions 4.Skin abnormalities at the pulse examination site including wound rash or infection 5.Use of uncontrolled medications or substances affecting pulse signals on the examination day
Design outcomes
Primary
| Measure | Time frame |
|---|---|
| Signal Quality Index During pulse examination session Percentage of pulse signals passing predefined signal quality criteria during pulse acquisition | — |
Secondary
| Measure | Time frame |
|---|---|
| Successful Signal Acquisition Rate During pulse examination session Percentage of successful pulse signal recordings from all pulse measurement attempts | — |
Countries
Thailand
Contacts
Public ContactPravit Akarasereenont
Faculty of Medicine Siriraj Hospital Mahidol University
Outcome results
None listed