scholarly journals Effects of Neuro-Cognitive Load on Learning Transfer Using a Virtual Reality-Based Driving System

2021 ◽  
Vol 5 (4) ◽  
pp. 54
Author(s):  
Usman Alhaji Abdurrahman ◽  
Shih-Ching Yeh ◽  
Yunying Wong ◽  
Liang Wei
Keyword(s):  
Virtual Reality ◽  
Data Fusion ◽  
Cognitive Load ◽  
Learning Transfer ◽  
Mental Workload ◽  
Eye Gaze ◽  
Machine Learning Algorithms ◽  
Driving System ◽  
User Classification ◽  
Multimodal Data Fusion

Understanding the ways different people perceive and apply acquired knowledge, especially when driving, is an important area of study. This study introduced a novel virtual reality (VR)-based driving system to determine the effects of neuro-cognitive load on learning transfer. In the experiment, easy and difficult routes were introduced to the participants, and the VR system is capable of recording eye-gaze, pupil dilation, heart rate, as well as driving performance data. So, the main purpose here is to apply multimodal data fusion, several machine learning algorithms, and strategic analytic methods to measure neurocognitive load for user classification. A total of ninety-eight (98) university students participated in the experiment, in which forty-nine (49) were male participants and forty-nine (49) were female participants. The results showed that data fusion methods achieved higher accuracy compared to other classification methods. These findings highlight the importance of physiological monitoring to measure mental workload during the process of learning transfer.

scholarly journals Cognitive Load Measurement in a Virtual Reality-Based Driving System for Autism Intervention

2017 ◽  
Vol 8 (2) ◽  
pp. 176-189 ◽  
Author(s):  
Lian Zhang ◽  
Joshua Wade ◽  
Dayi Bian ◽  
Jing Fan ◽  
Amy Swanson ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Cognitive Load ◽  
Driving System ◽  
Load Measurement ◽  
Autism Intervention ◽  
Cognitive Load Measurement

Investigating a Virtual Reality-based Emergency Response Scenario and Intelligent User Interface for First Responders

2020 ◽  
Vol 64 (1) ◽  
pp. 2114-2118
Author(s):  
Randall Spain ◽  
Jason Saville ◽  
Barry Lui ◽  
Donia Slack ◽  
Edward Hill ◽  
...  
Keyword(s):  
Virtual Reality ◽  
User Interface ◽  
Emergency Response ◽  
User Interfaces ◽  
Mental Workload ◽  
First Responders ◽  
Lessons Learned ◽  
Future Research ◽  
Intelligent User Interfaces ◽  
Intelligent User Interface

Because advances in broadband capabilities will soon allow first responders to access and use many forms of data when responding to emergencies, it is becoming critically important to design heads-up displays to present first responders with information in a manner that does not induce extraneous mental workload or cause undue interaction errors. Virtual reality offers a unique medium for envisioning and testing user interface concepts in a realistic and controlled environment. In this paper, we describe a virtual reality-based emergency response scenario that was designed to support user experience research for evaluating the efficacy of intelligent user interfaces for firefighters. We describe the results of a usability test that captured firefighters’ feedback and reactions to the VR scenario and the prototype intelligent user interface that presented them with task critical information through the VR headset. The paper concludes with lessons learned from our development process and a discussion of plans for future research.

Multimodal data fusion framework enhanced robot-assisted minimally invasive surgery

2021 ◽  
pp. 014233122098435
Author(s):  
Wen Qi ◽  
Hang Su ◽  
Ke Fan ◽  
Ziyang Chen ◽  
Jiehao Li ◽  
...  
Keyword(s):  
Minimally Invasive Surgery ◽  
Minimally Invasive ◽  
Data Fusion ◽  
Invasive Surgery ◽  
Robot Control ◽  
Surgical Robot ◽  
Robot Assisted ◽  
Multimodal Data ◽  
Multimodal Data Fusion ◽  
Fusion Framework

The generous application of robot-assisted minimally invasive surgery (RAMIS) promotes human-machine interaction (HMI). Identifying various behaviors of doctors can enhance the RAMIS procedure for the redundant robot. It bridges intelligent robot control and activity recognition strategies in the operating room, including hand gestures and human activities. In this paper, to enhance identification in a dynamic situation, we propose a multimodal data fusion framework to provide multiple information for accuracy enhancement. Firstly, a multi-sensors based hardware structure is designed to capture varied data from various devices, including depth camera and smartphone. Furthermore, in different surgical tasks, the robot control mechanism can shift automatically. The experimental results evaluate the efficiency of developing the multimodal framework for RAMIS by comparing it with a single sensor system. Implementing the KUKA LWR4+ in a surgical robot environment indicates that the surgical robot systems can work with medical staff in the future.

scholarly journals Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation

2020 ◽  
Vol 64 ◽  
pp. 149-187 ◽  
Author(s):  
Yu-Dong Zhang ◽  
Zhengchao Dong ◽  
Shui-Hua Wang ◽  
Xiang Yu ◽  
Xujing Yao ◽  
...  
Keyword(s):  
Data Fusion ◽  
Multimodal Data ◽  
Multimodal Data Fusion

scholarly journals Presence Effects in Virtual Reality Based on User Characteristics: Attention, Enjoyment, and Memory

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1051
Author(s):  
Si Jung Kim ◽  
Teemu H. Laine ◽  
Hae Jung Suk
Keyword(s):  
Virtual Reality ◽  
Emotional State ◽  
Eye Gaze ◽  
Emotional Valence ◽  
Media Content ◽  
Eye Tracker ◽  
User Characteristics ◽  
Head Mounted Display ◽  
Age Range ◽  
Different Levels

Presence refers to the emotional state of users where their motivation for thinking and acting arises based on the perception of the entities in a virtual world. The immersion level of users can vary when they interact with different media content, which may result in different levels of presence especially in a virtual reality (VR) environment. This study investigates how user characteristics, such as gender, immersion level, and emotional valence on VR, are related to the three elements of presence effects (attention, enjoyment, and memory). A VR story was created and used as an immersive stimulus in an experiment, which was presented through a head-mounted display (HMD) equipped with an eye tracker that collected the participants’ eye gaze data during the experiment. A total of 53 university students (26 females, 27 males), with an age range from 20 to 29 years old (mean 23.8), participated in the experiment. A set of pre- and post-questionnaires were used as a subjective measure to support the evidence of relationships among the presence effects and user characteristics. The results showed that user characteristics, such as gender, immersion level, and emotional valence, affected their level of presence, however, there is no evidence that attention is associated with enjoyment or memory.

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