Literature DB >> 31726745

Physiological Responses During Hybrid BNCI Control of an Upper-Limb Exoskeleton.

Francisco J Badesa1,2,3, Jorge A Diez1,3, Jose Maria Catalan1,3, Emilio Trigili4, Francesca Cordella5, Marius Nann6, Simona Crea4,7,8, Surjo R Soekadar9, Loredana Zollo5, Nicola Vitiello4,7,8, Nicolas Garcia-Aracil1,3.   

Abstract

When combined with assistive robotic devices, such as wearable robotics, brain/neural-computer interfaces (BNCI) have the potential to restore the capabilities of handicapped people to carry out activities of daily living. To improve applicability of such systems, workload and stress should be reduced to a minimal level. Here, we investigated the user's physiological reactions during the exhaustive use of the interfaces of a hybrid control interface. Eleven BNCI-naive healthy volunteers participated in the experiments. All participants sat in a comfortable chair in front of a desk and wore a whole-arm exoskeleton as well as wearable devices for monitoring physiological, electroencephalographic (EEG) and electrooculographic (EoG) signals. The experimental protocol consisted of three phases: (i) Set-up, calibration and BNCI training; (ii) Familiarization phase; and (iii) Experimental phase during which each subject had to perform EEG and EoG tasks. After completing each task, the NASA-TLX questionnaire and self-assessment manikin (SAM) were completed by the user. We found significant differences (p-value < 0.05) in heart rate variability (HRV) and skin conductance level (SCL) between participants during the use of the two different biosignal modalities (EEG, EoG) of the BNCI. This indicates that EEG control is associated with a higher level of stress (associated with a decrease in HRV) and mental work load (associated with a higher level of SCL) when compared to EoG control. In addition, HRV and SCL modulations correlated with the subject's workload perception and emotional responses assessed through NASA-TLX questionnaires and SAM.

Entities:  

Keywords:  Assistive technologies; brain-computer interfaces; exoskeleton

Year:  2019        PMID: 31726745     DOI: 10.3390/s19224931

Source DB:  PubMed          Journal:  Sensors (Basel)        ISSN: 1424-8220            Impact factor:   3.576


  3 in total

Review 1.  EOG-Based Human-Computer Interface: 2000-2020 Review.

Authors:  Chama Belkhiria; Atlal Boudir; Christophe Hurter; Vsevolod Peysakhovich
Journal:  Sensors (Basel)       Date:  2022-06-29       Impact factor: 3.847

2.  Assistance Robotics and Biosensors 2019.

Authors:  Andrés Úbeda; Fernando Torres; Santiago T Puente
Journal:  Sensors (Basel)       Date:  2020-02-29       Impact factor: 3.576

Review 3.  Measuring mental workload in assistive wearable devices: a review.

Authors:  Charlotte Marchand; Jozina B De Graaf; Nathanaël Jarrassé
Journal:  J Neuroeng Rehabil       Date:  2021-11-07       Impact factor: 4.262

  3 in total

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