FindTrial
Sign In

An Easy and Accurate Way to Diagnose Leg Swelling with Artificial Intelligence

Development of an AI-based Bioimpedance Data-Driven System for the Diagnosis of Lower-Extremity Edema

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
CRIS
Registry ID
KCT0011047
Enrollment
30
Registered
2025-09-19
Start date
2025-09-18
Completion date
Unknown
Last updated
2025-11-10

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

Conditions

None listed

Interventions

None listed

Sponsors

Chung-Ang University Gwangmyeong Hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: Adults aged 20 years or older who are overweight, obese, or have lower limb edema

Exclusion criteria

Exclusion criteria: (1) Pregnant or breastfeeding women (2) Adolescents under 19 years of age (minors) (3) Individuals who refuse to give voluntary consent or do not sign the consent form

Design outcomes

Primary

MeasureTime frame
1+ (Mild edema): Indentation depth 2 mm, disappears within 5 seconds 2+ (Moderate edema): Indentation depth 4 mm, disappears within 10 seconds 3+ (Severe edema): Indentation depth 6 mm, persists for 10–20 seconds 4+ (Very severe edema): Indentation depth 8 mm, persists for =30 seconds—

Secondary

MeasureTime frame
Body composition data—

Countries

Korea, Republic of

Contacts

Public ContactYun Hwan Oh

Chung-Ang University Gwangmyeong Hospital

swimayo@cause.or.kr+82-2-1811-7800

Outcome results

None listed

Source: CRIS (via WHO ICTRP) · Data processed: Feb 4, 2026