  Lately, there has been an increasing interest in hand gesture analysis
systems. Recent works have employed pattern recognition techniques and have
focused on the development of systems with more natural user interfaces. These
systems may use gestures to control interfaces or recognize sign language
gestures, which can provide systems with multimodal interaction; or consist in
multimodal tools to help psycholinguists to understand new aspects of discourse
analysis and to automate laborious tasks. Gestures are characterized by several
aspects, mainly by movements and sequence of postures. Since data referring to
movements or sequences carry temporal information, this paper presents a
literature review about temporal aspects of hand gesture analysis, focusing on
applications related to natural conversation and psycholinguistic analysis,
using Systematic Literature Review methodology. In our results, we organized
works according to type of analysis, methods, highlighting the use of Machine
Learning techniques, and applications.
