  In this work, an extensive review of literature in the field of gesture
recognition carried out along with the implementation of a simple
classification system for hand hygiene stages based on deep learning solutions.
A subset of robust dataset that consist of handwashing gestures with two hands
as well as one-hand gestures such as linear hand movement utilized. A
pretrained neural network model, RES Net 50, with image net weights used for
the classification of 3 categories: Linear hand movement, rub hands palm to
palm and rub hands with fingers interlaced movement. Correct predictions made
for the first two classes with > 60% accuracy. A complete dataset along with
increased number of classes and training steps will be explored as a future
work.
