Determining if wearable sensors affect infant leg movement frequency

ABSTRACT

Purpose: There is interest in using wearable sensors to measure infant leg movement patterns; however, they were not developed for infant use and their presence may adversely affect infant movement production. Their weight may discourage leg movement production, or their presence may annoy an infant and encourage higher rates of leg movement production. Our purpose was to determine whether wearable sensors affected the frequency of infant leg movements produced. Method: We included 10 infants with typical development and 10 infants at risk of developmental delay, between 2 and 10 months’ chronological age. Results: After collecting and analyzing video recordings of infants, we found a negligible difference between the numbers of spontaneous leg movements made while infants wore sensors, compared to those without sensors. Conclusions: Wearable sensors have a negligible effect on the frequency of infant leg movement production, supporting their use in infant movement analysis.

KEYWORDS:

• Infant
• leg movement
• movement system
• wearable sensor

Acknowledgments

We thank all the infants and their families for supporting this research and Mara Harris and Tessa Gordon for their assistance. We also thank Children’s Hospital Los Angeles and Eisner Pediatric and Family Medicine Center.

Funding

This study was supported in part by funding from the National Institutes of Health [K12-HD055929] (PI: Ottenbacher) and the University of Southern California Undergraduate Research Associates Program (PI: Smith) and Provost’s Undergraduate Research Fellowships (PI: Jiang). This study was supported in part by funding from the National Institutes of Health from the National Center for Advancing Translational Science [UL1TR001855 and UL1TR000130].

Declaration of interest

The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Study data were collected and managed using REDCap electronic data capture tools hosted at the Southern California Clinical and Translational Science Institute at the University of Southern California. REDCap (Research Electronic Data Capture) is a secure, web-based application designed to support data capture for research studies, providing (1) an intuitive interface for validated data entry; (2) audit trails for tracking data manipulation and export procedures; (3) automated export procedures for seamless data downloads to common statistical packages; and (4) procedures for importing data from external sources. Funding bodies did not have a role in the design of the study and collection, analysis, interpretation of data or in writing the manuscript.

Additional information

Funding

This study was supported in part by funding from the National Institutes of Health [K12-HD055929] (PI: Ottenbacher) and the University of Southern California Undergraduate Research Associates Program (PI: Smith) and Provost’s Undergraduate Research Fellowships (PI: Jiang). This study was supported in part by funding from the National Institutes of Health from the National Center for Advancing Translational Science [UL1TR001855 and UL1TR000130].