A video/IMU hybrid system for movement estimation in infants

Archana Machireddy, Jan Van Santen, Jenny L. Wilson, Julianne Myers, Mijna Hadders-Algra, Xubo Song

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Cerebral palsy is a non-progressive neurological disorder occurring in early childhood affecting body movement and muscle control. Early identification can help improve outcome through therapy-based interventions. Absence of so-called 'fidgety movements' is a strong predictor of cerebral palsy. Currently, infant limb movements captured through either video cameras or accelerometers are analyzed to identify fidgety movements. However both modalities have their limitations. Video cameras do not have the high temporal resolution needed to capture subtle movements. Accelerometers have low spatial resolution and capture only relative movement. In order to overcome these limitations, we have developed a system to combine measurements from both camera and sensors to estimate the true underlying motion using extended Kalman filter. The estimated motion achieved 84% classification accuracy in identifying fidgety movements using Support Vector Machine.

Original languageEnglish (US)
Title of host publication2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Subtitle of host publicationSmarter Technology for a Healthier World, EMBC 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages730-733
Number of pages4
ISBN (Electronic)9781509028092
DOIs
StatePublished - Sep 13 2017
Event39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017 - Jeju Island, Korea, Republic of
Duration: Jul 11 2017Jul 15 2017

Other

Other39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017
CountryKorea, Republic of
CityJeju Island
Period7/11/177/15/17

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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  • Cite this

    Machireddy, A., Van Santen, J., Wilson, J. L., Myers, J., Hadders-Algra, M., & Song, X. (2017). A video/IMU hybrid system for movement estimation in infants. In 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society: Smarter Technology for a Healthier World, EMBC 2017 - Proceedings (pp. 730-733). [8036928] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/EMBC.2017.8036928