A virtual reality and brain computer interface system for upper limb rehabilitation of post stroke patients

Achanccaray, David; Acuna, Kevin; Carranza, Erick; Andreu-Pérez, Javier

doi:10.1109/fuzz-ieee.2017.8015726

Cited by 16 publications

(12 citation statements)

References 10 publications

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“…In recent years, the combination of BCI and VR has provided practical benefits for training and evaluation (Achanccaray et al, 2017). In VR training, BCI can be used to analyze brain activity synchronously in real time (Martišius and Damaševičius, 2016).…”

Section: Research Status Of Scet With Bci-vr Research Value Of Bci-vrmentioning

confidence: 99%

The Current Research of Spatial Cognitive Evaluation and Training With Brain–Computer Interface and Virtual Reality

Zhou

Dong

et al. 2020

Front. Neurosci.

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Section: Research Status Of Scet With Bci-vr Research Value Of Bci-vrmentioning

confidence: 99%

The Current Research of Spatial Cognitive Evaluation and Training With Brain–Computer Interface and Virtual Reality

Zhou

Dong

et al. 2020

Front. Neurosci.

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“…The most widely used techniques include band-pass (BP) filtering and notch filtering to avoid the power-line interference if the pass-band includes the power line frequency. Other popular noise reduction steps include Common Average Reference (CAR) and Weighted Average Reference (WAR) [1,26,38]. For feature extraction, the common spatial pattern (CSP) filter and its variants (e.g.…”

Section: Related Work 21 Classical Machine Learningmentioning

confidence: 99%

“…For feature extraction, the common spatial pattern (CSP) filter and its variants (e.g. filter bank CSP (FBCSP)) are the widely used approach [1,44]. Other works employ independent or principal component analysis (ICA,PCA) [16,43].…”

Section: Related Work 21 Classical Machine Learningmentioning

confidence: 99%

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Brain Computer Interface for Neuro-rehabilitation With Deep Learning Classification and Virtual Reality Feedback

Karácsony

Hansen

Iversen

et al. 2019

Proceedings of the 10th Augmented Human International Conference 2019

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Though Motor Imagery (MI) stroke rehabilitation effectively promotes neural reorganization, current therapeutic methods are immeasurable and their repetitiveness can be demotivating. In this work, a real-time electroencephalogram (EEG) based MI-BCI (Brain Computer Interface) system with a virtual reality (VR) game as a motivational feedback has been developed for stroke rehabilitation. If the subject successfully hits one of the targets, it explodes and thus providing feedback on a successfully imagined and virtually executed movement of hands or feet. Novel classification algorithms with deep learning (DL) and convolutional neural network (CNN) architecture with a unique trial onset detection technique was used. Our classifiers performed better than the previous architectures on datasets from PhysioNet offline database. It provided fine classification in the real-time game setting using a 0.5 second 16 channel input for the CNN architectures. Ten participants reported the training to be interesting, fun and immersive. "It is a bit weird, because it feels like it would be my hands", was one of the comments from a test person. The VR system induced a slight discomfort and a moderate effort for MI activations was reported. We conclude that MI-BCI-VR systems with classifiers based on DL for real-time game applications should be considered for motivating MI stroke rehabilitation. CCS CONCEPTS • Human-centered computing → Empirical studies in HCI; Virtual reality; Usability testing.

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“…These rely on the weak Electroencephalogram (EEG) signals that arise from the neural activities and are measured using non-invasive electrodes suitably placed on the skull's surface. Introduced by Vidal in 1973 [1], BCI is currently an active research direction with applications in diverse areas including intelligent home control [2], speech synthesis [3], spelling applications [4], readiness detection [5], Epilepsy Prognosis [6], wheelchair control [7], microsleep prevention [8], limb rehabilitation [9], mobile robots [10,11], drowsiness control [12], and assistive systems for people with severe handicaps enabling them, for example, to control electronic devices [13] or browse the internet [14] .…”

Section: Introductionmentioning

confidence: 99%

Versatile Brain-Computer-Interface for Severely -Disabled People

Masaad¹,

Jassim²,

Mahdi³

et al. 2021

IJCDS

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A virtual reality and brain computer interface system for upper limb rehabilitation of post stroke patients

Cited by 16 publications

References 10 publications

The Current Research of Spatial Cognitive Evaluation and Training With Brain–Computer Interface and Virtual Reality

The Current Research of Spatial Cognitive Evaluation and Training With Brain–Computer Interface and Virtual Reality

Brain Computer Interface for Neuro-rehabilitation With Deep Learning Classification and Virtual Reality Feedback

Versatile Brain-Computer-Interface for Severely -Disabled People

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