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Technology-assisted quantification of movement to predict infants at high risk of motor disability: A systematic
Christian B Redd1, Mohan Karunanithi2, Roslyn N Boyd3
1CSIRO, The Australian e-Health Research Centre, Brisbane, Australia; The University of Queensland, Queensland Cerebral Palsy and Rehabilitation Research Centre, Child Health Research Centre, Faculty of Medicine, Brisbane, Australia.
Insights
Technology-assisted infant movement analysis shows promise for predicting motor disabilities in infants under six months corrected age. While feasible, further validation is needed for wider clinical adoption.
Area of Science:
- Developmental pediatrics
- Movement science
- Biomedical engineering
Background:
- Early identification of motor disabilities in infants is crucial for timely intervention.
- Technology-assisted assessments offer objective quantification of infant movement.
- Predictive validity of these tools for identifying high-risk infants needs systematic evaluation.
Purpose of the Study:
- To systematically review the literature on the predictive validity of technology-assisted infant movement measures.
- To assess the ability of these measures to identify infants at high risk of motor disability before six months corrected age.
Main Methods:
- A comprehensive literature search was conducted across five databases up to February 2021.
- Included studies quantified infant movement using technology before six months corrected age and compared it to clinical neurodevelopmental assessments.
- Methodological quality was assessed using the Downs and Black scale.
Main Results:
- Twenty-three studies met the inclusion criteria, utilizing various technologies like 2D video, accelerometry, and motion tracking.
- Technology-assisted assessments showed promising results in identifying cerebral palsy (CP) (sensitivity 44-100%) and typical development (specificity 88-95%).
- Methodological quality varied, and analytical approaches were diverse.
Conclusions:
- Technology-assisted movement assessments in infants under six months corrected age are feasible with current technologies.
- Limited validation exists for many measurement tools.
- Despite promising results, clinical uptake remains restricted due to validation and implementation challenges.
Aim:
To systematically review the scientific literature to determine the predictive validity of technology-assisted measures of observable infant movement in infants less than six months of corrected age (CA) to identify high-risk of motor disability.
Method:
A comprehensive search for randomised and non-randomised controlled trials, cohort studies and cross-comparison trials was performed on five electronic databases up to Feb 2021. Studies were included if they quantified infant movement before 6 months CA using some method of technology-assistance and compared the instrumented measure to a diagnostic clinical measure of neurodevelopment. Studies were excluded if they did not report a technology-assisted measure of infant movement. Methodological quality of the included studies was assessed using the Downs and Black scale.
Results:
23 studies met the full inclusion and exclusion criteria. Methodological quality of the included papers ranged from 9 to 24 (out of 26) on the Downs and Black scale. Infant movement assessments included the General Movements Assessment (GMA) and domains of the Hammersmith Infant Neurological Assessment (HINE). Studies used 2D video recordings, RGB-Depth recordings, accelerometry, and electromagnetic motion tracking technologies to quantify movement. Analytical approaches and movement features of interest were individual and varied. Technology assisted quantitative assessments identified cases of later diagnosed CP with sensitivity 44-100 %, specificity 59-95 %, Area under the ROC Curve 82-93 %; and typical development with sensitivity range 30-46 %, specificity 88-95 %, Area under the ROC Curve 68 %.
Interpretation:
Technology-assisted assessments of movement in infants less than 6 months CA using current technologies are feasible. Validation of measurement tools are limited. Although methods and results appear promising clinical uptake of technology-assisted assessments remains limited.
