Abstract:
Collecting large datasets of amputee gait data is notoriously difficult. Additionally, collecting
data on less prevalent amputations or on gait activities other than level walking and running on
hard surfaces is rarely attempted. However, with the wealth of user-generated content on the
Internet, the scope for collecting amputee gait data from alternative sources other than traditional
gait labs is intriguing. Here we investigate the potential of YouTube videos to provide gait data
on amputee walking. We use an example dataset of trans-femoral amputees level walking at self selected speeds to collect temporal gait parameters and calculate gait asymmetry. We compare
our YouTube data with typical literature values, and show that our methodology produces results
that are highly comparable to data collected in a traditional manner. The similarity between the
results of our novel methodology and literature values lends confidence to our technique.
Nevertheless, clear challenges with the col-lection and interpretation of crowd-sourced gait data
remain, including long term access to datasets, and a lack of validity and reliability studies in this
area.
