Automatic Identification of Gait Events Using an Instrumented Sock
By Preece, Stephen J.; Kenney, Laurence P.; Major, Matthew J.; Dias, Tilak; Lay, Edward; Fernandes, Bosco T.; Journal of NeuroEngineering and Rehabilitation, Vol. 8, No. 32Publication Date: May 27, 2011
Study investigated the output of a knitted resistive strain sensor during walking. The strain sensor used is defined as a textile-based transducer in which piezo-resistive properties incorporated into a sock are used to measure an applied strain. This technology offers the potential to detect critical events during the stance phase of the gait cycle, which could prove useful in applications such as functional electrical stimulation systems to assist gait. Study participants were 8 women and 12 men with a mean age of 43 years. Each participant performed 10 walking trials at their self-selected walking speed in both a sock-only condition and a shod condition wearing their normal shoes. During trials, the degree of similarity between the sensor output and the ankle angle in the sagittal plane was determined. In addition, the possibility of predicting 3 key gait events, heel strike, heel lift, and toe off, was investigated using a relatively straightforward algorithm. This worked by predicting gait events to occur at fixed time offsets from specific peaks in the sensor signal. Results showed that, for all 20 participants, the sensor output exhibited the same general characteristics as the ankle joint angle. However, there were large differences between participants in the degree of similarity between the two curves. Despite this variability, it was possible to predict gait events accurately using the algorithm, which displayed high levels of trial-to-trial repeatability.
Published by: BioMed Central Ltd (Website:http://www.biomedcentral.com)
Link to text: http://www.jneuroengrehab.com/content/8/1/32/abstract
