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Human activity recognition (HAR) is determined through the acquisition of images or kinematic states, which are analyzed by prediction models. The goal of these systems is to correctly classify the data into one of the following categories: gestures, elementary actions that are components of complex activities, human-object or human-human interactions, and group actions.
HAR plays a fundamental role in health monitoring systems through the acquisition of information about the health and psychological statuses of subjects. The development of new medical and assistive technologies has created environmental conditions for the independent living among the elderly and has contributed to the improvement of their quality of life. In this Special Issue, we present the constant development of new data, applications and analysis techniques.
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