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Fig. 2 | BioMedical Engineering OnLine

Fig. 2

From: Machine-learning-based children’s pathological gait classification with low-cost gait-recognition system

Fig. 2

The procedure of gait feature extraction from gait cycle. a 30 sensor blocks with the red mark are selected for feature extraction. b Sliding window method (Hanning window with 512-sample intervals width) is applied to all n sensor blocks and transformed to frequency domain later. c Dividing five frequency bands from FFT frequency spectrum, 0 (exclude)–2 Hz, 2 (exclude)–4 Hz, 4 (exclude)–6 Hz, 6 (exclude)–8 Hz, and 8 (exclude)–10 Hz, and summing all the frequent value in each frequency band to generate a five-elements vector for each sensor. d Joining all the five-element vector from each sensor together and normalizing to a 150-element unit vector

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