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Updated: Jun 22, 2026
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Frame-by-Frame Video Analysis of Idiosyncratic Reach-to-Grasp Movements in Humans
Published on: January 15, 2018
Using computer-based video analysis in the study of fidgety movements.
Lars Adde1, Jorunn L Helbostad, Alexander Refsum Jensenius
1Department of Clinical Services, Physiotherapy section, St. Olav University Hospital, Trondheim, Norway. lars.adde@ntnu.no
Early Human Development
|May 26, 2009
Summary
Computer analysis of infant movements using the General Movement Toolbox (GMT) can reliably detect fidgety movements (FM), aiding in early cerebral palsy (CP) risk assessment. This technology assists in identifying infants who may not exhibit FMs.
Area of Science:
- Neurology
- Developmental Pediatrics
- Biomedical Engineering
Background:
- Absence of fidgety movements (FM) in high-risk infants is a key indicator for later cerebral palsy (CP).
- General Movement Assessment (GMA) classifies FMs based on visual Gestalt perception.
- Objective, computer-based movement analysis offers potential improvements over traditional methods.
Purpose of the Study:
- To evaluate the feasibility of computer-based video analysis for classifying fidgety movements (FM) in infants.
- To explore objective quantification of spontaneous infant movements.
- To assess the utility of a novel software tool in movement analysis.
Main Methods:
- General Movement Assessment (GMA) was conducted on videos of 82 term and preterm infants at varying CP risk levels.
- A developed software, General Movement Toolbox (GMT), was used for qualitative and quantitative video analysis.
- Quantitative analysis involved calculating pixel displacement to derive movement variables.
Main Results:
- GMT's visual output clearly depicted FM patterns.
- Variability in spatial center of active pixels showed the highest sensitivity (81.5%) and specificity (70.0%) for FM classification.
- Implementing triage thresholds at 90% sensitivity and specificity reduced the need for further referral by 70%.
Conclusions:
- Video analysis using GMT enables both qualitative and quantitative assessment of FMs.
- GMT is practical for clinical implementation and aids in identifying infants lacking FMs.
- Computer-based analysis offers a valuable tool for early detection of movement disorders.
