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Portable Activity Monitoring System for Temporal Parameters of Gait Cycles

Published: 01 October 2010 Publication History

Abstract

A portable and wireless activity monitoring system was developed for the estimation of temporal gait parameters. The new system was built using three-axis accelerometers to automatically detect walking steps with various walking speeds. The accuracy of walking step-peak detection algorithm was assessed by using a running machine with variable speeds. To assess the consistency of gait parameter analysis system, estimated parameters, such as heel-contact and toe-off time based on accelerometers and footswitches were compared for consecutive 20 steps from 19 individual healthy subjects. Accelerometers and footswitches had high consistency in the temporal gait parameters. The stance, swing, single-limb support, and double-limb support time of gait cycle revealed ICCs values of 0.95, 0.93, 0.86, and 0.75 on the right and 0.96, 0.86, 0.93, 0.84 on the left, respectively. And the walking step-peak detection accuracy was 99.15% ( 0.007) for the proposed method compared to 87.48% ( 0.033) for a pedometer. Therefore, the proposed activity monitoring system proved to be a reliable and useful tool for identification of temporal gait parameters and walking pattern classification.

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Cited By

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  • (2014)Better Physical Activity Classification using Smartphone Acceleration SensorJournal of Medical Systems10.1007/s10916-014-0095-038:9(1-10)Online publication date: 1-Sep-2014
  • (2013)Step count algorithm adapted to indoor localizationProceedings of the International C* Conference on Computer Science and Software Engineering10.1145/2494444.2494457(128-129)Online publication date: 10-Jul-2013
  • (2012)Mixture modeling of gait patterns from sensor dataProceedings of the 5th International Conference on PErvasive Technologies Related to Assistive Environments10.1145/2413097.2413157(1-4)Online publication date: 6-Jun-2012
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Information & Contributors

Information

Published In

cover image Journal of Medical Systems
Journal of Medical Systems  Volume 34, Issue 5
October 2010
186 pages

Publisher

Plenum Press

United States

Publication History

Published: 01 October 2010

Author Tags

  1. Accelerometer
  2. Activity monitoring
  3. Gait analysis
  4. Step-peak
  5. Temporal parameter
  6. Walking

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Cited By

View all
  • (2014)Better Physical Activity Classification using Smartphone Acceleration SensorJournal of Medical Systems10.1007/s10916-014-0095-038:9(1-10)Online publication date: 1-Sep-2014
  • (2013)Step count algorithm adapted to indoor localizationProceedings of the International C* Conference on Computer Science and Software Engineering10.1145/2494444.2494457(128-129)Online publication date: 10-Jul-2013
  • (2012)Mixture modeling of gait patterns from sensor dataProceedings of the 5th International Conference on PErvasive Technologies Related to Assistive Environments10.1145/2413097.2413157(1-4)Online publication date: 6-Jun-2012
  • (2011)A method with triaxial acceleration sensor for fall detection of the elderly in daily activitiesProceedings of the 6th international conference on Universal access in human-computer interaction: context diversity - Volume Part III10.5555/2022539.2022555(121-130)Online publication date: 9-Jul-2011
  • (2010)Towards ubiquitous acquisition and processing of gait parametersProceedings of the 9th Mexican international conference on Advances in artificial intelligence: Part I10.5555/1927149.1927191(410-421)Online publication date: 8-Nov-2010

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