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. 2017 Jan;15(1):13-24.
doi: 10.1007/s12021-016-9313-x.

Classification of Normal and Pathological Gait in Young Children Based on Foot Pressure Data

Guodong Guo  1   2   3 , Keegan Guffey  4 , Wenbin Chen  5 , Paola Pergami  6
Affiliations

Classification of Normal and Pathological Gait in Young Children Based on Foot Pressure Data

Guodong Guo et al. Neuroinformatics. 2017 Jan.

Abstract

Human gait recognition, an active research topic in computer vision, is generally based on data obtained from images/videos. We applied computer vision technology to classify pathology-related changes in gait in young children using a foot-pressure database collected using the GAITRite walkway system. As foot positioning changes with children's development, we also investigated the possibility of age estimation based on this data. Our results demonstrate that the data collected by the GAITRite system can be used for normal/pathological gait classification. Combining age information and normal/pathological gait classification increases the accuracy of the classifier. This novel approach could support the development of an accurate, real-time, and economic measure of gait abnormalities in children, able to provide important feedback to clinicians regarding the effect of rehabilitation interventions, and to support targeted treatment modifications.

Keywords: GAITRite walkway system; Health application; Medical instrument; Normal/pathological gait recognition.

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Figures

Fig. 1
Fig. 1
Examples of children’s footprint images captured by the sensor array of the GAITRite system: a healthy child; b moderate toe-walking; c severe toe-walking
Fig. 2
Fig. 2
For GAITRite system automatically encloses each footprint with a quadrilateral. Sensor 1 and 3 are the two most outer sensors on the medial side of the footprint. They define the medial line AG. The lateral line LR is defined by sensors 5 and 6, which are the two most outer sensors on the lateral side. Each footstep consists of 3 areas, fore-foot, mid-foot, and heel
Fig. 3
Fig. 3
The proposed framework for gait pattern and age classification using the foot pressure data. DAGPR denotes direct age and gait pattern recognition. JAGPR denotes joint age and gait pattern recognition
Fig. 4
Fig. 4
Confusion matrices of isolated age classification, using the whole dataset (Left) and only normal gait samples (Right)
Fig. 5
Fig. 5
Confusion matrices of joint age and normal/pathological gait recognition under two settings: 6 classes (Left) and 4 classes (Right)
Fig. 6
Fig. 6
Confusion matrices of derived normal/pathological gait pattern classification under two settings: 6 classes (Left) and 4 classes (Right)
Fig. 7
Fig. 7
ROC curves for normal/pathological gait pattern classification without age information (Top) and with age information (Bottom)
See this image and copyright information in PMC

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