Abstract
All people have a fingerprint that is unique to them and persistent
throughout life. Similarly, we propose that people have a gaitprint, a
persistent walking pattern that contains unique information about an
individual. To provide evidence of a unique gaitprint, we aimed to
identify individuals based on basic spatiotemporal variables. Healthy
young adults were recruited to walk overground on an indoor track at
their own pace for four minutes wearing inertial measurement units. A
total of 18 trials per participant were completed between two days, one
week apart. Four methods of pattern analysis, a) Euclidean distance, b)
cosine similarity, c) random forest, and d) support vector machine, were
applied to our basic spatiotemporal variables such as step and stride
lengths to accurately identify people. Our best accuracy (99.38%) was
achieved by the support vector machine and by the top 5 and top 10 most
similar trials from cosine similarity. Our results clearly demonstrate a
persistent walking pattern with sufficient information about the
individual to make them identifiable, suggesting the existence of a
gaitprint.