An EEG Source Imaging-based Feature Extraction Method for Motor Imagery Classification

Li, Junhan; Zheng, Nengheng

doi:10.1109/smc53654.2022.9945567

Cited by 2 publications

(1 citation statement)

References 19 publications

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“…The use of brain-computer interfaces (BCIs), or brain-machine interfaces (BMIs), whereby brain activity is recorded and decoded in real time to control an avatar in an immersive virtual reality (VR) environment or a device, combined with tactile and thermal feedback has led to beneficial neuroplasticity effects [5][6][7][8][9][10][11][12]. Improvement in BCIs has been achieved both through improvements in the use of different classifiers [13][14][15][16][17], as well as through spinal cord stimulation [18], functional electrical Life 2024, 14, 396 2 of 22 stimulation [8], but also by improving immersiveness. We recently presented a BCI that innovated through the introduction of multiple complex virtual reality scenarios that allowed for simultaneous visual, auditory, and tactile feedback [10,19].…”

Section: Introductionmentioning

confidence: 99%

Activation of a Rhythmic Lower Limb Movement Pattern during the Use of a Multimodal Brain–Computer Interface: A Case Study of a Clinically Complete Spinal Cord Injury

Pais-Vieira,

Figueiredo,

Perrotta

et al. 2024

Life

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Brain–computer interfaces (BCIs) that integrate virtual reality with tactile feedback are increasingly relevant for neurorehabilitation in spinal cord injury (SCI). In our previous case study employing a BCI-based virtual reality neurorehabilitation protocol, a patient with complete T4 SCI experienced reduced pain and emergence of non-spastic lower limb movements after 10 sessions. However, it is still unclear whether these effects can be sustained, enhanced, and replicated, as well as the neural mechanisms that underlie them. The present report outlines the outcomes of extending the previous protocol with 24 more sessions (14 months, in total). Clinical, behavioral, and neurophysiological data were analyzed. The protocol maintained or reduced pain levels, increased self-reported quality of life, and was frequently associated with the appearance of non-spastic lower limb movements when the patient was engaged and not experiencing stressful events. Neural activity analysis revealed that changes in pain were encoded in the theta frequency band by the left frontal electrode F3. Examination of the lower limbs revealed alternating movements resembling a gait pattern. These results suggest that sustained use of this BCI protocol leads to enhanced quality of life, reduced and stable pain levels, and may result in the emergence of rhythmic patterns of lower limb muscle activity reminiscent of gait.

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