Study on Tripping Risks in Fast Walking through Cadence-Controlled Gait Analysis

Algorithm 1

Gait cycle segmentation (GCS).

Step 1.	Signal extrema depiction: apply an MMW algorithm to the accelerometrical signals (Figure 9(a)) to produce signals’ peaks and valleys (Figure 9(b)).
Step 2.	“V-IC” extraction: apply a threshold to filter out those illegal extrema as shown in Figure 9(c). For extracting “V-IC”,(1)retain with for the V-IC of the ith cycle, where is the signal of the ith V-IC;(2)for all consecutive and , compute in the unit of signal points, where indicates the temporal position of ;(3)if signal points (since the normal cadence in walking is about 60140 BPM), retain both of the and ;(4)if not, discard the bigger one.
Step 3.	“IC-P” extraction: do the same way as the last step to “V-IC” and then produce .
Step 4.	IC extraction: for the ith IC, search a point between and with ; mark as the IC characteristic as shown in Figure 9(d).
Step 5.	Gait cycle segmentation: for each neighboring pair (, ) in the gait signals of one foot, compute in the unit of signal points.