Your browser does not support JavaScript!

Computational methods to detect step events for normal and pathological gait evaluation using accelerometer

Computational methods to detect step events for normal and pathological gait evaluation using accelerometer

For access to this article, please select a purchase option:

Buy article PDF
(plus tax if applicable)
Buy Knowledge Pack
10 articles for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
Electronics Letters — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

The presented study highlights the feasibility and accuracy of novel computational methods based on a morphological filter and a least square acceleration filter to detect step events for evaluating normal and pathological gait parameters using a single accelerometer. This is the first evidence that demonstrates the feasibility and accuracy of the novel accelerometer-based system and methods in both normal and pathological populations.


    1. 1)
      • W. Zijstra , A.L. Hof . Assessment of spatio-temporal gait parameters from trunk accelerations during human walking. Gait Posture , 2 , 1 - 10
    2. 2)
      • M.J. Mathie , A.C. Coster , N.H. Lovell , B.G. Celler . Accelerometry: providing an integrated, practical method for long-term, ambulatory monitoring of human movement. Physiol. Meas. , 2 , R1 - R20
    3. 3)
      • C.H. Chu , E.J. Delp . Impulsive noise suppression and background normalization of electrocardiogram signals using morphological operators. IEEE Trans. Biomed. Eng. , 2 , 262 - 273
    4. 4)
    5. 5)
      • M.G. Frei , R.L. Davidchack , I. Osorio . Least squares acceleration filtering for the estimation of signal derivatives and sharpness at extrema. IEEE Trans. Biomed. Eng. , 8 , 971 - 977
    6. 6)

Related content

This is a required field
Please enter a valid email address