Towards Ubiquitous Acquisition and Processing of Gait Parameters

  • Irvin Hussein López-Nava
  • Angélica Muñoz-Meléndez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6437)

Abstract

Gait analysis is the process of measuring and evaluating gait and walking spatio-temporal patterns, namely of human locomotion. This process is usually performed on specialized equipment that is capable of acquiring extensive data and providing a gait analysis assessment based on reference values. Based on gait assessments, therapists and physicians can prescribe medications and provide physical therapy rehabilitation to patients with gait problems. This work is oriented to support the design of ambulatory and ubiquitous technologies for gait monitoring. A probabilistic method to automatically detect human strides from raw signals provided by wireless accelerometers is presented. Local thresholds are extracted from raw acceleration signals, and used to distinguish actual strides from characteristic peaks commonly produced by significant shifts of the acceleration signals. Then, a bayesian classifier is trained with these peaks to detect and count strides. The proposed method has a good precision for classifying strides of raw acceleration signals for both, young and elderly individuals. Strides detection is required to calculate gait parameters and provide a clinical assessment.

Keywords

Gait parameters processing wireless triaxial accelerometer characteristic peaks detector bayesian classifier 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Irvin Hussein López-Nava
    • 1
  • Angélica Muñoz-Meléndez
    • 1
  1. 1.National Institute for Astrophysics, Optics and ElectronicsTonantzintlaMexico

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