Analysis of gait in patients with normal pressure hydrocephalus
Proceedings of the First ACM Workshop on Mobile Systems, Applications, and Services for Healthcare
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Detection of gait characteristics has found considerable interest in fields of biomechanics and rehabilitation sciences. In this paper an approach for abnormal gait detection employing Discrete Fourier Transform (DFT) analysis has been presented. The joint angle characteristics in frequency domain have been analyzed and using the harmonic coefficients, recognition for abnormal gait has been performed. The experimental results and analysis represent that the proposed algorithm based on DFT can not only reduce the gait data dimensionality effectively, but also lightens the computation cost, with a satisfactory distinction. In order to make the algorithm more generic, a Mean Square Error (MSE) analysis is also presented. Future work will be the expansion of the detection introduced in this system to include abnormality detection instead of just an abnormal or normal detection that would prove to be a valuable addition for use in a variety of applications, including unobtrusive clinical gait analysis, automated surveillance etc.