A concise review on sensor signal acquisition and transformation applied to human activity recognition and human–robot interaction. (June 2019)

• Record Type: Journal Article
• Authors: Martínez-Villaseñor, Lourdes; Ponce, Hiram
• Is Part Of: International journal of distributed sensor networks. Volume 15:Number 6(2019)
• Publication Date: 2019-06
• Subjects: Human activity recognition -- human–computer interaction -- sensor signals -- machine learning; Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1177/1550147719853987
• Languages: English
• ISSNs: 1550-1329

Abstract

Human activitiy recognition deals with the integration of sensing and reasoning aiming to understand better people's actions. Moreover, it plays an important role in human interaction, human–robot interaction, and brain–computer interaction. When these approaches have to be developed, different efforts from signal processing and artificial intelligence are considered. In that sense, this article aims to present a concise review of signal processing in human activitiy recognition systems and describe two examples and applications both in human activity recognition and robotics: human–robot interaction and socialization, and imitation learning in robotics. In addition, it presents ideas and trends in the context of human activity recognition for human–robot interaction that are important when processing signals within that systems.