Development of the flexible observation system for a virtual reality excavator using the head tracking system

Le, Quang Hoan; Bae, Jong-Il; Jeong, Yu Mi; Nguyên, Chi Thành; Yang, Soon-Yong

doi:10.1109/iccas.2015.7364738

Cited by 3 publications

(1 citation statement)

References 7 publications

(5 reference statements)

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“…For data analysis and validation, the MATLAB development environment was utilized. Another category of applications related to head motion analysis is human-computer interaction (HCI) devices, which have general applicability [27,45,46,[59][60][61][62]. The main purpose of most of these systems is to determine an accurate solution for the augmented reality field.…”

Section: Head Motion Systemsmentioning

confidence: 99%

Using Inertial Sensors to Determine Head Motion—A Review

Severin

Dobrea

2021

J. Imaging

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Human activity recognition and classification are some of the most interesting research fields, especially due to the rising popularity of wearable devices, such as mobile phones and smartwatches, which are present in our daily lives. Determining head motion and activities through wearable devices has applications in different domains, such as medicine, entertainment, health monitoring, and sports training. In addition, understanding head motion is important for modern-day topics, such as metaverse systems, virtual reality, and touchless systems. The wearability and usability of head motion systems are more technologically advanced than those which use information from a sensor connected to other parts of the human body. The current paper presents an overview of the technical literature from the last decade on state-of-the-art head motion monitoring systems based on inertial sensors. This study provides an overview of the existing solutions used to monitor head motion using inertial sensors. The focus of this study was on determining the acquisition methods, prototype structures, preprocessing steps, computational methods, and techniques used to validate these systems. From a preliminary inspection of the technical literature, we observed that this was the first work which looks specifically at head motion systems based on inertial sensors and their techniques. The research was conducted using four internet databases—IEEE Xplore, Elsevier, MDPI, and Springer. According to this survey, most of the studies focused on analyzing general human activity, and less on a specific activity. In addition, this paper provides a thorough overview of the last decade of approaches and machine learning algorithms used to monitor head motion using inertial sensors. For each method, concept, and final solution, this study provides a comprehensive number of references which help prove the advantages and disadvantages of the inertial sensors used to read head motion. The results of this study help to contextualize emerging inertial sensor technology in relation to broader goals to help people suffering from partial or total paralysis of the body.

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