This paper addressed a novel intelligent model for
automatic evaluation of the change of elder gait function based
on kinematic gait data. In order to recognize the change of
elderly gait patterns with higher accuracy, the wavelet analysis
technique was proposed as a new approach to extract gait
features, and then those obtained gait features were initiated the
training set of gait classifier such as artifical neural network
(ANN). The gait data of two groups including young and old
subjects were acquired during normal walking, and were
analyzed using the proposed method. The experimental results
indicated that the gait features exacted by the wavelet analysis
technique, as the input of ANN, could provide more
discriminating information than the traditional gait features
selected such as maximal value or values obtained from the
different occurrences based on gait events, and the proposed
classification model could identify young and elderly gait
patterns with higher accuracy. It is hopeful that the proposed
model can be used as an effective tool for diagnosing the change
of gait function for old people in clinical application.
This paper addressed a novel intelligent model for automatic evaluation of the change of elder gait function based on kinematic gait data. In order to recognize the change of elderly gait patterns with higher accuracy, the wavelet analysis technique was proposed as a new approach to extract gait features, and then those obtained gait features were initiated the training set of gait classifier such as artifical neural network (ANN). The gait data of two groups including young and old subjects were acquired during normal walking, and were analyzed using the proposed method. The experimental results indicated that the gait features exacted by the wavelet analysis technique, as the input of ANN, could provide more discriminating information than the traditional gait features selected such as maximal value or values obtained from the different occurrences based on gait events, and the proposed classification model could identify young and elderly gait patterns with higher accuracy. It is hopeful that the proposed model can be used as an effective tool for diagnosing the change of gait function for old people in clinical application.
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