A concise review on sensor signal acquisition and transformation applied to human activity recognition and human–robot interaction

Lourdes Martínez-Villaseñor,Hiram Ponce

doi:10.1177/1550147719853987

Lourdes Martínez-Villaseñor, Hiram Ponce

Open Access

https://doi.org/10.1177/1550147719853987

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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.

Highlights

Current trends in computer science and the integration of signal processing in embedded devices have been rapidly growing
The goal of human activity recognition (HAR) is to classify and identify activities based on the collected data from different devices such as sensors or cameras, mainly processed by machine learning methods and pattern recognition techniques.[3,6]
This article aims to present a review on the different steps of signal processing in the context of HAR. It provides two examples and applications in signal processing dedicated to HAR and robotics: (1) human–robot interaction (HRI) and socialization, highlighting the importance of recognizing human activities for the context of robots and how those interact in a social way with humans; and (2) imitation learning, as one high-level task in robots to extract knowledge from humans to learn and later to recognize and to perform demonstrated actions for better interaction between humans and robots

Summary

Introduction

Current trends in computer science and the integration of signal processing in embedded devices have been rapidly growing. From the point of view of signal processing, in general, HAR systems perform the following steps: data acquisition, windowing, feature extraction, feature selection, building activity models, and classification.

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Conclusion