Performance analysis of self-organising neural networks tracking algorithms for intake monitoring using kinect
Samuele Gasparrini, Enea Cippitelli, Ennio Gambi, Susanna Spinsante, Francisco Flórez‐Revuelta · 2015
The analysis of intake behaviour is a key factor to understand the health condition of a subject, such as elderly or people affected by diet-related disorders. The technology can be exploited for this purpose to promptly identify anomalous situations. This paper presents a comparison between three unsupervised machine learning algorithms used to track the movements performed by a person during an intake action and provides experimental results showing the best performing algorithm among those compared.