Quality parameters for a multimodal EEG/EMG/kinematic brain-computer interface (BCI) aiming to suppress neurological tremor in upper limbs [v2; ref status: indexed, http://f1000r.es/3aq]
Tremor is the most common movement disorder encountered during daily neurological practice. Tremor in the upper limbs causes functional disability and social inconvenience, impairing daily life activities. The response of tremor to pharmacotherapy is variable. Therefore, a combination of drugs is of...
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| Format: | Article |
| Language: | English |
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F1000 Research Ltd
2014-04-01
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| Series: | F1000Research |
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| Online Access: | http://f1000research.com/articles/2-282/v2 |
| _version_ | 1818441745811111936 |
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| author | Giuliana Grimaldi Mario Manto Yassin Jdaoudi |
| author_facet | Giuliana Grimaldi Mario Manto Yassin Jdaoudi |
| author_sort | Giuliana Grimaldi |
| collection | DOAJ |
| description | Tremor is the most common movement disorder encountered during daily neurological practice. Tremor in the upper limbs causes functional disability and social inconvenience, impairing daily life activities. The response of tremor to pharmacotherapy is variable. Therefore, a combination of drugs is often required. Surgery is considered when the response to medications is not sufficient. However, about one third of patients are refractory to current treatments. New bioengineering therapies are emerging as possible alternatives. Our study was carried out in the framework of the European project “Tremor” (ICT-2007-224051). The main purpose of this challenging project was to develop and validate a new treatment for upper limb tremor based on the combination of functional electrical stimulation (FES; which has been shown to reduce upper limb tremor) with a brain-computer interface (BCI). A BCI-driven detection of voluntary movement is used to trigger FES in a closed-loop approach. Neurological tremor is detected using a matrix of EMG electrodes and inertial sensors embedded in a wearable textile. The identification of the intentionality of movement is a critical aspect to optimize this complex system. We propose a multimodal detection of the intentionality of movement by fusing signals from EEG, EMG and kinematic sensors (gyroscopes and accelerometry). Parameters of prediction of movement are extracted in order to provide global prediction plots and trigger FES properly. In particular, quality parameters (QPs) for the EEG signals, corticomuscular coherence and event-related desynchronization/synchronization (ERD/ERS) parameters are combined in an original algorithm which takes into account the refractoriness/responsiveness of tremor. A simulation study of the relationship between the threshold of ERD/ERS of artificial EEG traces and the QPs is also provided. Very interestingly, values of QPs were much greater than those obtained for the corticomuscular module alone. |
| first_indexed | 2024-12-14T18:33:08Z |
| format | Article |
| id | doaj.art-67eb90d4550b4c1883a845bfe2129956 |
| institution | Directory Open Access Journal |
| issn | 2046-1402 |
| language | English |
| last_indexed | 2024-12-14T18:33:08Z |
| publishDate | 2014-04-01 |
| publisher | F1000 Research Ltd |
| record_format | Article |
| series | F1000Research |
| spelling | doaj.art-67eb90d4550b4c1883a845bfe21299562022-12-21T22:51:43ZengF1000 Research LtdF1000Research2046-14022014-04-01210.12688/f1000research.2-282.v24274Quality parameters for a multimodal EEG/EMG/kinematic brain-computer interface (BCI) aiming to suppress neurological tremor in upper limbs [v2; ref status: indexed, http://f1000r.es/3aq]Giuliana Grimaldi0Mario Manto1Yassin Jdaoudi2Unité d’Etude du Mouvement, Université Libre de Bruxelles, Erasme, Bruxelles, 1070, BelgiumFonds de la Recherche Scientifique, Université Libre de Bruxelles, Bruxelles, 1070, BelgiumUnité d’Etude du Mouvement, Université Libre de Bruxelles, Erasme, Bruxelles, 1070, BelgiumTremor is the most common movement disorder encountered during daily neurological practice. Tremor in the upper limbs causes functional disability and social inconvenience, impairing daily life activities. The response of tremor to pharmacotherapy is variable. Therefore, a combination of drugs is often required. Surgery is considered when the response to medications is not sufficient. However, about one third of patients are refractory to current treatments. New bioengineering therapies are emerging as possible alternatives. Our study was carried out in the framework of the European project “Tremor” (ICT-2007-224051). The main purpose of this challenging project was to develop and validate a new treatment for upper limb tremor based on the combination of functional electrical stimulation (FES; which has been shown to reduce upper limb tremor) with a brain-computer interface (BCI). A BCI-driven detection of voluntary movement is used to trigger FES in a closed-loop approach. Neurological tremor is detected using a matrix of EMG electrodes and inertial sensors embedded in a wearable textile. The identification of the intentionality of movement is a critical aspect to optimize this complex system. We propose a multimodal detection of the intentionality of movement by fusing signals from EEG, EMG and kinematic sensors (gyroscopes and accelerometry). Parameters of prediction of movement are extracted in order to provide global prediction plots and trigger FES properly. In particular, quality parameters (QPs) for the EEG signals, corticomuscular coherence and event-related desynchronization/synchronization (ERD/ERS) parameters are combined in an original algorithm which takes into account the refractoriness/responsiveness of tremor. A simulation study of the relationship between the threshold of ERD/ERS of artificial EEG traces and the QPs is also provided. Very interestingly, values of QPs were much greater than those obtained for the corticomuscular module alone.http://f1000research.com/articles/2-282/v2Motor SystemsMovement DisordersNeuromuscular DiseasesNeurorehabilitation & CNS Trauma |
| spellingShingle | Giuliana Grimaldi Mario Manto Yassin Jdaoudi Quality parameters for a multimodal EEG/EMG/kinematic brain-computer interface (BCI) aiming to suppress neurological tremor in upper limbs [v2; ref status: indexed, http://f1000r.es/3aq] F1000Research Motor Systems Movement Disorders Neuromuscular Diseases Neurorehabilitation & CNS Trauma |
| title | Quality parameters for a multimodal EEG/EMG/kinematic brain-computer interface (BCI) aiming to suppress neurological tremor in upper limbs [v2; ref status: indexed, http://f1000r.es/3aq] |
| title_full | Quality parameters for a multimodal EEG/EMG/kinematic brain-computer interface (BCI) aiming to suppress neurological tremor in upper limbs [v2; ref status: indexed, http://f1000r.es/3aq] |
| title_fullStr | Quality parameters for a multimodal EEG/EMG/kinematic brain-computer interface (BCI) aiming to suppress neurological tremor in upper limbs [v2; ref status: indexed, http://f1000r.es/3aq] |
| title_full_unstemmed | Quality parameters for a multimodal EEG/EMG/kinematic brain-computer interface (BCI) aiming to suppress neurological tremor in upper limbs [v2; ref status: indexed, http://f1000r.es/3aq] |
| title_short | Quality parameters for a multimodal EEG/EMG/kinematic brain-computer interface (BCI) aiming to suppress neurological tremor in upper limbs [v2; ref status: indexed, http://f1000r.es/3aq] |
| title_sort | quality parameters for a multimodal eeg emg kinematic brain computer interface bci aiming to suppress neurological tremor in upper limbs v2 ref status indexed http f1000r es 3aq |
| topic | Motor Systems Movement Disorders Neuromuscular Diseases Neurorehabilitation & CNS Trauma |
| url | http://f1000research.com/articles/2-282/v2 |
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