Abstract
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.
Highlights
Tremor is the most common movement disorder encountered during daily practice[1]
Recent studies aim to develop and validate a new treatment for upper limb tremor based on the combination of functional electrical stimulation (FES) with a brain-computer interface (BCI)[2,3]
We found no significant difference between the quality parameters (QPs) calculated from β/α ratio and β2/α ratio (p = 0.502)[8]
Summary
Tremor is the most common movement disorder encountered during daily practice[1]. Recent studies aim to develop and validate a new treatment for upper limb tremor based on the combination of functional electrical stimulation (FES) with a brain-computer interface (BCI)[2,3]. The intentionality of movement is tracked by the BCI, in order to trigger FES in the upper limbs. Such concepts open new doors for the treatment of numerous neurological disorders affecting the upper limbs. The fact that movement disorders often show up with brain atrophy or neuroplastic changes makes it difficult to generalize BCI markers that have been tested in a healthy population to patients with varying pathologies. I think this variance is a major reason why your multimodal processing could do so much better than a BCI-system that is solely based on EEG analysis
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