Publications:A Symbol-Based Approach to Gait Analysis From Acceleration Signals : Identification and Detection of Gait Events and a New Measure of Gait Symmetry

From CERES
Revision as of 05:41, 26 June 2014 by Slawek (Talk | contribs)

(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to: navigation, search

Do not edit this section

Keep all hand-made modifications below

Title A Symbol-Based Approach to Gait Analysis From Acceleration Signals : Identification and Detection of Gait Events and a New Measure of Gait Symmetry
Author Anita Sant'Anna and Nicholas Wickström
Year 2010
PublicationType Journal Paper
Journal IEEE transactions on information technology in biomedicine
HostPublication
DOI http://dx.doi.org/10.1109/TITB.2010.2047402
Conference
Diva url http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:345706
Abstract Gait analysis can convey important information about one’s physical and cognitive condition. Wearable inertial sensor systems can be used to continuously and unobtrusively assess gait during everyday activities in uncontrolled environments. An important step in the development of such systems is the processing and  analysis of the sensor data. This paper presents a symbol-based method used to detect the phases of gait and convey important dynamic information from accelerometer signals. The addition of expert knowledge substitutes the need for supervised learning techniques, rendering the system easy to interpret and easy to improve incrementally. The proposed method is compared to an approach based on peak-detection. A new symbol-based symmetry index is created and compared to a traditional temporal symmetry index and a symmetry measure based on cross-correlation. The symbol-based symmetry index exemplifies how the proposed method can extract more information from the acceleration signal than previous approaches