  The impact of physical exercise on emotional well-being is one of the most
important factors that drive sustained physical activity engagement. It is also
one of the least studied topics on account of the rather elaborated setups
required to quantify emotional expression during exercise. The wide adoption of
at-home, physical exercise solutions has compounded this problem due to the
secluded nature of these activities. We propose here a new methodology that
would allow for mass emotional expression and physical activity data gathering
using publicly available sources such as at-home exercise videos. We have shown
that the methodology is robust enough to extract high resolution, reliable data
from home videos posted on popular video share sites. The source-code and
instructions for practical use are published online such that researchers can
access data pertinent to emotional response during exertion in real world
situations with applicability for prospective and retrospective studies.
