Visual Versus Kinesthetic Motor Imagery for BCI Control of Robotic Arms (Mercury 2.0)

Arfaras, George; Athanasiou, Alkinoos; Pandria, Niki; Rafailia, Kavazidi Kyriaki; Kartsidis, Panagiotis; Astaras, A.; Bamidis, Panagiotis D.

doi:10.1109/cbms.2017.34

Cited by 9 publications

(12 citation statements)

References 19 publications

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“…While participants appeared to perform better using VMI rather than KMI as an imagery modality for BCI control, our analysis did not prove a statistically significant correlation [ 50 ]. Individual differences could play a role, since some participants performed better with KMI; it is worthwhile to explore this difference, as BCI control should be tailored to the needs of each individual [ 50 ]. Perception of the robot did not correlate to either performance or the sex of the operator.…”

Section: Resultsmentioning

confidence: 97%

“…The first of the two illustrative experimental applications was a qualitative assessment study, comparing MI modalities for control of the BCI-controlled robotic arms by healthy individuals with regard to BCI training and optimal performance [ 50 ]. The participants were trained to use visual and kinesthetic cues to control simple motor tasks of the two robotic arms and we assessed their skill training and success rates.…”

Section: Methodsmentioning

confidence: 99%

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Towards Rehabilitation Robotics: Off-the-Shelf BCI Control of Anthropomorphic Robotic Arms

Athanasiou

Xygonakis

Pandria

et al. 2017

BioMed Research International

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Advances in neural interfaces have demonstrated remarkable results in the direction of replacing and restoring lost sensorimotor function in human patients. Noninvasive brain-computer interfaces (BCIs) are popular due to considerable advantages including simplicity, safety, and low cost, while recent advances aim at improving past technological and neurophysiological limitations. Taking into account the neurophysiological alterations of disabled individuals, investigating brain connectivity features for implementation of BCI control holds special importance. Off-the-shelf BCI systems are based on fast, reproducible detection of mental activity and can be implemented in neurorobotic applications. Moreover, social Human-Robot Interaction (HRI) is increasingly important in rehabilitation robotics development. In this paper, we present our progress and goals towards developing off-the-shelf BCI-controlled anthropomorphic robotic arms for assistive technologies and rehabilitation applications. We account for robotics development, BCI implementation, and qualitative assessment of HRI characteristics of the system. Furthermore, we present two illustrative experimental applications of the BCI-controlled arms, a study of motor imagery modalities on healthy individuals' BCI performance, and a pilot investigation on spinal cord injured patients' BCI control and brain connectivity. We discuss strengths and limitations of our design and propose further steps on development and neurophysiological study, including implementation of connectivity features as BCI modality.

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Section: Resultsmentioning

confidence: 97%

Section: Methodsmentioning

confidence: 99%

Towards Rehabilitation Robotics: Off-the-Shelf BCI Control of Anthropomorphic Robotic Arms

Athanasiou

Xygonakis

Pandria

et al. 2017

BioMed Research International

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“…As the experimental procedures have been also described in detail [12,29], we will provide an overview hereby. The subjects were asked to perform Visual Motor Imagery (VMI), meaning they had to mentally rehearse 32 different movements of the upper extremities, while watching a set of arms performing randomly those movements on a computer screen.…”

Section: Experimental Procedurementioning

confidence: 99%

“…Subjects wore an Emotiv EPOC headset and they began training of the BCI modality using kinesthetic motor imagery (KMI) of movements of the left and the right arms. Action power threshold was set at 50% and all subjects were above threshold during training [29]. Three imagery classes were trained (resting state, left, and right).…”

Section: Experimental Procedurementioning

confidence: 99%

“…In our previous work we have presented our progress towards developing 8-DoF anthropomorphic robotic arms, controlled by wireless off-the-shelf BCI, for AT and rehabilitation applications [12]. We have accounted for development of the robotic arms and electronics, for implementation of the BCI control module, and we have presented pilot experimental applications of the Brain-Robot Interface (BRI) on healthy and disabled individuals [29,30].…”

Section: Introductionmentioning

confidence: 99%

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Wireless Brain-Robot Interface: User Perception and Performance Assessment of Spinal Cord Injury Patients

Athanasiou

Arfaras

Pandria

et al. 2017

Wireless Communications and Mobile Computing

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Patients suffering from life-changing disability due to Spinal Cord Injury (SCI) increasingly benefit from assistive robotics technology. The field of brain-computer interfaces (BCIs) has started to develop mature assistive applications for those patients. Nonetheless, noninvasive BCIs still lack accurate control of external devices along several degrees of freedom (DoFs). Unobtrusiveness, portability, and simplicity should not be sacrificed in favor of complex performance and user acceptance should be a key aim among future technological directions. In our study 10 subjects with SCI (one complete) and 10 healthy controls were recruited. In a single session they operated two anthropomorphic 8-DoF robotic arms via wireless commercial BCI, using kinesthetic motor imagery to perform 32 different upper extremity movements. Training skill and BCI control performance were analyzed with regard to demographics, neurological condition, independence, imagery capacity, psychometric evaluation, and user perception. Healthy controls, SCI subgroup with positive neurological outcome, and SCI subgroup with cervical injuries performed better in BCI control. User perception of the robot did not differ between SCI and healthy groups. SCI subgroup with negative outcome rated Anthropomorphism higher. Multi-DoF robotics control is possible by patients through commercial wireless BCI. Multiple sessions and tailored BCI algorithms are needed to improve performance.

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Comparison of Visual and Kinesthetic Motor Imagery for Upper Limb Activity

Torres-Narváez,

Müller,

Orjuela-Cañon

2024

Communications in Computer and Information Science

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Visual Versus Kinesthetic Motor Imagery for BCI Control of Robotic Arms (Mercury 2.0)

Cited by 9 publications

References 19 publications

Towards Rehabilitation Robotics: Off-the-Shelf BCI Control of Anthropomorphic Robotic Arms

Towards Rehabilitation Robotics: Off-the-Shelf BCI Control of Anthropomorphic Robotic Arms

Wireless Brain-Robot Interface: User Perception and Performance Assessment of Spinal Cord Injury Patients

Comparison of Visual and Kinesthetic Motor Imagery for Upper Limb Activity

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