Detecting falls by analyzing angular momentum

Dario Martelli, Vito Monaco, Silvestro Micera

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

Abstract

The aim of the present pilot study is to investigate the hypothesis that fall detection systems based on sensors placed on the distal segments of the body are more effective than solution based on placing sensors on the trunk. To test this hypothesis, we observed the contribution of all body segments to the 3D angular momentum. Five healthy adults were enrolled for the experimental sessions. A set of 39 spherical markers was located on body landmarks and subjects underwent perturbed walking while a Motion Analysis System recorded 3D kinematics. From a biomechanical model, the angular momentum pattern related to each body segment was estimated. Data were post-processed with a threshold-based algorithm used to detect which among body segments allows detect as soon as possible and with limited false alarms the perturbation. Results showed that hands-forearms and chest-head are the most sensitive to external moments orientated along respectively the anterior-posterior and medio-lateral directions.

Original languageEnglish
Title of host publicationIEEE International Conference on Rehabilitation Robotics
DOIs
Publication statusPublished - 2011
EventRehab Week Zurich 2011 - 2011 IEEE International Conference on Rehabilitation Robotics, ICORR 2011 - Zurich, Switzerland
Duration: Jun 27 2011Jul 1 2011

Other

OtherRehab Week Zurich 2011 - 2011 IEEE International Conference on Rehabilitation Robotics, ICORR 2011
CountrySwitzerland
CityZurich
Period6/27/117/1/11

Keywords

  • angular momentum
  • biomechanical model
  • fall detection
  • movement analysis

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Rehabilitation
  • Medicine(all)

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  • Cite this

    Martelli, D., Monaco, V., & Micera, S. (2011). Detecting falls by analyzing angular momentum. In IEEE International Conference on Rehabilitation Robotics [5975404] https://doi.org/10.1109/ICORR.2011.5975404