Artificial Intelligence-based Video Analysis to Detect Infantile Spasms

A Machine Learning Approach to Infantile Spasms Recognition in Video Recordings

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.

Inclusion Criteria:

• Participant age less than 24 months
• Participant evaluated in the Johns Hopkins Outpatient Center, Johns Hopkins Pediatric Emergency Department or Johns Hopkins Inpatient Units due to spells of abnormal movement or seizure
• Participant evaluated by a pediatric neurologist during the outpatient or inpatient visit at Johns Hopkins Hospital
• At least one video recording of the spell of abnormal movement produced by the parent/guardian available for provider review

Exclusion Criteria:

• Poor video recording quality
• Entire patient is not in frame