CLINATEC^® BCI platform based on the ECoG-recording implant WIMAGINE^® and the innovative signal-processing: Preclinical results

Abstract

The goal of the CLINATEC® Brain Computer Interface (BCI) Project is to improve tetraplegic subjects' quality of life by allowing them to interact with their environment through the control of effectors, such as an exoskeleton. The BCI platform is based on a wireless 64-channel ElectroCorticoGram (ECoG) recording implant WIMAGINE®, designed for long-term clinical application, and a BCI software environment associated to a 4-limb exoskeleton EMY (Enhancing MobilitY). Innovative ECoG signal decoding algorithms will allow the control of the exoskeleton by the subject's brain activity. Currently, the whole BCI platform was tested in real-time in preclinical experiments carried out in nonhuman primates. In these experiments, the exoskeleton arm was controlled by means of the decoded neuronal activity.

Development and evaluation of a new methodology for the fast generation of patient-specific Finite Element models of the buttock for sitting-acquired deep tissue injury prevention

“…This would allow to obtain data on vulnerable populations and to have a quantitative estimation of sub-dermal soft tissue biomechanical response in new seat and cushion designs. This could also potentially have an impact on the design of exoskeletons such as EMY (Enhancing MobilitY) (Morinière et al, 2015) developed in the BCI project (Eliseyev et al, 2014) for disabled persons and where the mechanical interfaces are paramount. From that perspective, the combined use of calibrated biplanar X-ray imaging and B-mode Ultrasound imaging could potentially improve on the shortcomings with MRI/CT imaging in that (i) due to the relatively short time (5 h per subject) necessary to develop patient specific models, many subjects can easily be analysed providing valuable insight into inter-individual variability (ii) realistic unloaded / loaded sitting position can easily be acquired.…”

Neuromodulation in the restoration of function after spinal cord injury

“…These systems necessitate repositioning of numerous external electrodes prior to every session, need continuous calibration and are not yet suitable for independent use. Advances in wireless devices, currently being utilised in primate studies [67][68][69] , may be a crucial step to more widespread use of this technology. Despite these challenges, the number of BMI-based clinical trials for SCI is increasing (Figure 2), although these are mainly small-scale openlabel trials involving low participant numbers (Table 1).…”

“…Although BMI applications have adopted sophisticated recording and stimulating technology, such as implantable intracortical microelectrode arrays together with multiple implanted percutaneous electrodes in the upper extremities (NCT00912041, Table 1) 14 , these systems are not yet fully wireless in that they still require an external connection to the computer interface. Progress in the design of multichannel wireless electrocorticography (ECoG) devices offers the potential for completely implantable systems, with initial evidence for wireless control of an arm prosthesis during primate reaching 67 . Subdural or epidurally implanted ECoG electrode arrays offer enhanced spatiotemporal resolution compared to EEG electrodes and are less invasive than intraparenchymal microelectrode arrays 67 .…”

Single-paradigm and hybrid brain computing interfaces and their use by disabled patients

“…Recently, Ramsey and co-workers at UMC Utrecht (Vansteensel et al, 2016) reported a breakthrough in realtime, long-term use of ECoG-based BCI in a patient with late-stage ALS (for a recent assessment of long-term ECoG monitoring, see Nurse et al, 2018). At Clinatec Grenoble (Eliseyev et al, 2014), a preclinical study is conducted to also assess long-term stability of ECoG-based BCI in a tetraplegic patient with the aim to control a limb exoskeleton. And ECoG has also provided access to another, perhaps more "natural" communication paradigm: the reconstruction of speech from brain signals, albeit more research is needed to improve intelligibility (for a recent discussion, see Akbari et al, 2018).…”