Trials / Recruiting
RecruitingNCT06315829
Artificial Intelligence-based Video Analysis to Detect Infantile Spasms
A Machine Learning Approach to Infantile Spasms Recognition in Video Recordings
- Status
- Recruiting
- Phase
- —
- Study type
- Observational
- Enrollment
- 200 (estimated)
- Sponsor
- Johns Hopkins University · Academic / Other
- Sex
- All
- Age
- 2 Years
- Healthy volunteers
- Not accepted
Summary
Infantile spasms are a type of seizure linked to developmental issues. Unfortunately, they are often misdiagnosed, causing delays in treatment. The purpose of this study is to develop a computer program that can reliably differentiate infantile spasms from similar, yet benign movements in videos. This computer program will learn from videos taken by parents of study participants. Quickly recognizing and treating infantile spasms is crucial for ensuring the best developmental outcomes.
Conditions
Interventions
| Type | Name | Description |
|---|---|---|
| DEVICE | Spasm Vision | Machine learning software developed to analyze videos and accurately distinguish infantile spasms from visually similar movements. |
Timeline
- Start date
- 2024-08-26
- Primary completion
- 2026-05-01
- Completion
- 2026-05-01
- First posted
- 2024-03-18
- Last updated
- 2025-08-19
Locations
1 site across 1 country: United States
Source: ClinicalTrials.gov record NCT06315829. Inclusion in this directory is not an endorsement.