A Novel Human Computer Interface based on Electrooculogram Signal for Smart Assistive Robots

Sun, Lei; Wang, Sunan; Chen, Hua; Chen, YangQuan

doi:10.1109/icma.2018.8484540

Cited by 3 publications

(1 citation statement)

References 11 publications

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“…However, for decades, researchers in academia and industry have tried to develop more innovative and more inclusive types of interfaces. Voice control and speech recognition systems [40], electrooculography-based interfaces [41], eye-gaze detection devices [42], vision-based gesture recognition algorithms [43], and bio signal-based interfaces [44] are developed to translate user intentions to robot commands to perform specific tasks. In addition to the standard interfaces, various approaches were also proposed for intelligent detection and grasping of objects within the workspace of the ARM [45].…”

Section: Assistive Robotic Manipulatorsmentioning

confidence: 99%

Human-Robot Interaction in Rehabilitation and Assistance: a Review

Mohebbi

2020

Curr Robot Rep

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Purpose of Review Research in assistive and rehabilitation robotics is a growing, promising, and challenging field emerged due to various social and medical needs such as aging populations, neuromuscular, and musculoskeletal disorders. Such robots can be used in various day-today scenarios or to support motor functionality, training, and rehabilitation. This paper reflects on the human-robot interaction perspective in rehabilitation and assistive robotics and reports on current issues and developments in the field. Recent Findings The survey on the literature reveals that new efforts are put on utilizing machine learning approaches alongside novel developments in sensing technology to adapt the systems with user routines in terms of activities for assistive systems and exercises for rehabilitation devices to fit each user's need and maximize their effectiveness. Summary A review of recent research and development efforts on human-robot interaction in assistive and rehabilitation robotics is presented in this paper. First, different subdomains in assistive and rehabilitation robotic research are identified, and accordingly, a survey on the background and trends of such developments is provided.

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Section: Assistive Robotic Manipulatorsmentioning

confidence: 99%

Human-Robot Interaction in Rehabilitation and Assistance: a Review

Mohebbi

2020

Curr Robot Rep

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Human Computer Interaction Based on Gestural Cues Recognition/Sign Language to Text Conversion

Murtaza

Akmal

Afzal

et al. 2019

2019 International Conference on Engineering and Emerging Technologies (ICEET)

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EOG-Based Human–Computer Interface: 2000–2020 Review

Belkhiria

Boudir

Hurter

et al. 2022

Sensors

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Electro-oculography (EOG)-based brain–computer interface (BCI) is a relevant technology influencing physical medicine, daily life, gaming and even the aeronautics field. EOG-based BCI systems record activity related to users’ intention, perception and motor decisions. It converts the bio-physiological signals into commands for external hardware, and it executes the operation expected by the user through the output device. EOG signal is used for identifying and classifying eye movements through active or passive interaction. Both types of interaction have the potential for controlling the output device by performing the user’s communication with the environment. In the aeronautical field, investigations of EOG-BCI systems are being explored as a relevant tool to replace the manual command and as a communicative tool dedicated to accelerating the user’s intention. This paper reviews the last two decades of EOG-based BCI studies and provides a structured design space with a large set of representative papers. Our purpose is to introduce the existing BCI systems based on EOG signals and to inspire the design of new ones. First, we highlight the basic components of EOG-based BCI studies, including EOG signal acquisition, EOG device particularity, extracted features, translation algorithms, and interaction commands. Second, we provide an overview of EOG-based BCI applications in the real and virtual environment along with the aeronautical application. We conclude with a discussion of the actual limits of EOG devices regarding existing systems. Finally, we provide suggestions to gain insight for future design inquiries.

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A Novel Human Computer Interface based on Electrooculogram Signal for Smart Assistive Robots

Cited by 3 publications

References 11 publications

Human-Robot Interaction in Rehabilitation and Assistance: a Review

Human-Robot Interaction in Rehabilitation and Assistance: a Review

Human Computer Interaction Based on Gestural Cues Recognition/Sign Language to Text Conversion

EOG-Based Human–Computer Interface: 2000–2020 Review

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