EEG and ECoG features for Brain Computer Interface in Stroke Rehabilitation

The ability of non-invasive Brain-Computer Interface (BCI) to control an exoskeleton was used for motor rehabilitation in stroke patients or as an assistive device for the paralyzed. However, there is still a need to create a more reliable BCI that could be used to control several degrees of Freedom (DoFs) that could improve rehabilitation results. Decoding different movements from the same limb, high accuracy and reliability are some of the main difficulties when using conventional EEG-based BCIs and the challenges we tackled in this thesis. In this PhD thesis, we investigated that the classification of several functional hand reaching movements from the same limb using EEG is possible with acceptable accuracy. Moreover, we investigated how the recalibration could affect the classification results. For this reason, we tested the recalibration in each multi-class decoding for within session, recalibrated between-sessions, and between sessions. It was shown the great influence of recalibrating the generated classifier with data from the current session to improve stability and reliability of the decoding. Moreover, we used a multiclass extension of the Filter Bank Common Spatial Patterns (FBCSP) to improve the decoding accuracy based on features and compared it to our previous study using CSP. Sensorimotor-rhythm-based BCI systems have been used within the same frequency ranges as a way to influence brain plasticity or controlling external devices. However, neural oscillations have shown to synchronize activity according to motor and cognitive functions. For this reason, the existence of cross-frequency interactions produces oscillations with different frequencies in neural networks. In this PhD, we investigated for the first time the existence of cross-frequency coupling during rest and movement using ECoG in chronic stroke patients. We found that there is an exaggerated phase-amplitude coupling between the phase of alpha frequency and the amplitude of gamma frequency, which can be used as feature or target for neurofeedback interventions using BCIs. This coupling has been also reported in another neurological disorder affecting motor function (Parkinson and dystonia) but, to date, it has not been investigated in stroke patients. This finding might change the future design of assistive or therapeuthic BCI systems for motor restoration in stroke patients

Human Ipsilateral Motor Physiology and Neuroprosthetic Applications in Chronic Stroke

Improving the recovery of lost motor function in hemiplegic chronic stroke survivors is a critical need to improve the lives of these patients. Over the last several decades, neuroprosthetic systems have emerged as novel tools with the potential to restore function in a variety of patient populations. While traditional neuroprosthetics have focused on using neural activity contralateral to a moving limb for device control, an alternative control signal may be necessary to develop brain-computer interface (BCI) systems in stroke survivors that suffer damage to the cortical hemisphere contralateral to the affected limb. While movement-related neural activity also occurs in the hemisphere ipsilateral to a moving limb, it is uncertain if these signals can be used within BCI systems. This dissertation examines the motor activity ipsilateral to a moving limb and the potential use of these signals for neuroprosthetic applications in chronic stroke survivors. Patients performed three-dimensional (3D) reaching movements with the arm ipsilateral to an electrocorticography (ECoG) array in order to assess the extent of kinematic information that can be decoded from the cortex ipsilateral to a moving limb. Additionally, patients performed the same task with the arm contralateral to the same ECoG arrays, allowing us to compare the neural representations of contralateral and ipsilateral limb movements. While spectral power changes related to ipsilateral arm movements begin later and are lower in amplitude than power changes related to contralateral arm movements, 3D kinematics from both contralateral and ipsilateral arm trajectories can be decoded with similar accuracies. The ability to decode movement kinematics from the ipsilateral cortical hemisphere demonstrates the potential to use these signals within BCI applications for controlling multiple degrees of freedom. Next we examined the relationship between electrode invasiveness and signal quality. The ability to decode movement kinematics from neural activity was significantly decreased in simulated electroencephalography (EEG) signals relative to ECoG signals, indicating that invasive signals would be necessary to implement BCI systems with multiple degrees of freedom. For ECoG signals, the human dura also causes a significant decrease in signal quality when electrodes with small spatial sizes are used. This tradeoff between signal quality and electrode invasiveness should therefore be taken into account when designing ECoG BCI systems. Finally, chronic stroke survivors used activity associated with affected hand motor intentions, recorded from their unaffected hemisphere using EEG, to control simple BCI systems. This demonstrates that motor signals from the ipsilateral hemisphere are viable for BCI applications, not only in motor-intact patients, but also in chronic stroke survivors. Taken together, these experiments provide initial demonstrations that it is possible to develop BCI systems using the unaffected hemisphere in stroke survivors with multiple degrees of freedom. Further development of these BCI systems may eventually lead to improving function for a significant population of patients

Epileptic Seizure Detection on an Ultra-Low-Power Embedded RISC-V Processor Using a Convolutional Neural Network

The treatment of refractory epilepsy via closed-loop implantable devices that act on seizures either by drug release or electrostimulation is a highly attractive option. For such implantable medical devices, efficient and low energy consumption, small size, and efficient processing architectures are essential. To meet these requirements, epileptic seizure detection by analysis and classification of brain signals with a convolutional neural network (CNN) is an attractive approach. This work presents a CNN for epileptic seizure detection capable of running on an ultra-low-power microprocessor. The CNN is implemented and optimized in MATLAB. In addition, the CNN is also implemented on a GAP8 microprocessor with RISC-V architecture. The training, optimization, and evaluation of the proposed CNN are based on the CHB-MIT dataset. The CNN reaches a median sensitivity of 90% and a very high specificity over 99% corresponding to a median false positive rate of 6.8 s per hour. After implementation of the CNN on the microcontroller, a sensitivity of 85% is reached. The classification of 1 s of EEG data takes t=35 ms and consumes an average power of P≈140 μW. The proposed detector outperforms related approaches in terms of power consumption by a factor of 6. The universal applicability of the proposed CNN based detector is verified with recording of epileptic rats. This results enable the design of future medical devices for epilepsy treatment

Closed-loop stimulation for upper limb rehabilitation following spinal cord injury and stroke

PhD ThesisInnovation is required to improve upper limb rehabilitation for neurological conditions such as stroke and spinal cord injury (SCI). There is growing appreciation of the importance of neural plasticity in recovery, and how this can be facilitated by synchronous activity in peripheral neural circuits and central brain areas. However, despite increasing scientific evidence, technological solutions that exploit associative plasticity have not yet been widely evaluated in clinical practice. In this thesis, I report the development and initial evaluation of a novel device which enabled a reaching and grasping motion in the affected limb by combining assistive functional electrical stimulation (FES) with inferred voluntary brain activity. The device was designed to enable translation from laboratory-to-clinic by overcoming common practical barriers to translational research, such as adaptability and ease of use. The device was demonstrated to be usable by individuals with either chronic stroke or SCI, and received positive qualitative feedback. Some participants showed modest improvements on assessments of upper limb function following a short intervention period. A study with healthy able-bodied volunteers indicated that after using the device, corticospinal pathways to the antagonist (flexor) muscle may be facilitated, and this facilitation might be increased by adjusting the relative timing of stimulation and inferred brain activity. The device could also deliver alternative stimulation techniques, and an exploratory study into transcutaneous spinal cord stimulation (tSCS) was conducted with healthy able-bodied volunteers. It was found that tSCS may activate peripheral and spinal pathways within acceptable comfort levels, but the parameters used in this study did not to generate functional contractions. An unexpected oscillatory motor response provided insights into how tSCS acts upon the motor system. Prior to a large scale evaluation of clinical effectiveness, further research is required to: further develop a theoretical basis for the intervention; demonstrate the mechanisms of action; and to evaluate the efficacy of the device.Wellcome Trust, postgraduate research studentship (2015 to 2018) • EPSRC Preparing for GCRF Award (PI: Dr Andrew Jackson) - Low cost rehabilitation of hand function following stroke (2016 to 2017

De animais a máquinas : humanos tecnicamente melhores nos imaginários de futuro da convergência tecnológica

Dissertação (mestrado)—Universidade de Brasília, Instituto de Ciências Sociais, Departamento de Sociologia, 2020.O tema desta investigação é discutir os imaginários sociais de ciência e tecnologia que emergem a partir da área da neuroengenharia, em sua relação com a Convergência Tecnológica de quatro disciplinas: Nanotecnologia, Biotecnologia, tecnologias da Informação e tecnologias Cognitivas - neurociências- (CT-NBIC). Estas áreas desenvolvem-se e são articuladas por meio de discursos que ressaltam o aprimoramento das capacidades físicas e cognitivas dos seres humanos, com o intuito de construir uma sociedade melhor por meio do progresso científico e tecnológico, nos limites das agendas de pesquisa e desenvolvimento (P&D). Objetivos: Os objetivos nesse cenário, são discutir as implicações éticas, econômicas, políticas e sociais deste modelo de sistema sociotécnico. Nos referimos, tanto as aplicações tecnológicas, quanto as consequências das mesmas na formação dos imaginários sociais, que tipo de relações se estabelecem e como são criadas dentro desse contexto. Conclusão: Concluímos na busca por refletir criticamente sobre as propostas de aprimoramento humano mediado pela tecnologia, que surgem enquanto parte da agenda da Convergência Tecnológica NBIC. No entanto, as propostas de melhoramento humano vão muito além de uma agenda de investigação. Há todo um quadro de referências filosóficas e políticas que defendem o aprimoramento da espécie, vertentes estas que se aliam a movimentos trans-humanistas e pós- humanistas, posições que são ao mesmo tempo éticas, políticas e econômicas. A partir de nossa análise, entendemos que ciência, tecnologia e política estão articuladas, em coprodução, em relação às expectativas de futuros que são esperados ou desejados. Ainda assim, acreditamos que há um espaço de diálogo possível, a partir do qual buscamos abrir propostas para o debate público sobre questões de ciência e tecnologia relacionadas ao aprimoramento da espécie humana.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)The subject of this research is to discuss the social imaginaries of science and technology that emerge from the area of neuroengineering in relation with the Technological Convergence of four disciplines: Nanotechnology, Biotechnology, Information technologies and Cognitive technologies -neurosciences- (CT-NBIC). These areas are developed and articulated through discourses that emphasize the enhancement of human physical and cognitive capacities, the intuition it is to build a better society, through the scientific and technological progress, at the limits of the research and development (R&D) agendas. Objectives: The objective in this scenery, is to discuss the ethic, economic, politic and social implications of this model of sociotechnical system. We refer about the technological applications and the consequences of them in the formation of social imaginaries as well as the kind of social relations that are created and established in this context. Conclusion: We conclude looking for critical reflections about the proposals of human enhancement mediated by the technology. That appear as a part of the NBIC technologies agenda. Even so, the proposals of human enhancement go beyond boundaries that an investigation agenda. There is a frame of philosophical and political references that defend the enhancement of the human beings. These currents that ally to the transhumanism and posthumanism movements, positions that are ethic, politic and economic at the same time. From our analysis, we understand that science, technology and politics are articulated, are in co-production, regarding the expected and desired futures. Even so, we believe that there is a space of possible dialog, from which we look to open proposals for the public discussion on questions of science and technology related to enhancement of human beings

A Fully Implantable Wireless ECoG 128-Channel Recording Device for Human Brain–Machine Interfaces: W-HERBS

Brain–machine interfaces (BMIs) are promising devices that can be used as neuroprostheses by severely disabled individuals. Brain surface electroencephalograms (electrocorticograms, ECoGs) can provide input signals that can then be decoded to enable communication with others and to control intelligent prostheses and home electronics. However, conventional systems use wired ECoG recordings. Therefore, the development of wireless systems for clinical ECoG BMIs is a major goal in the field. We developed a fully implantable ECoG signal recording device for human ECoG BMI, i.e., a wireless human ECoG-based real-time BMI system (W-HERBS). In this system, three-dimensional (3D) high-density subdural multiple electrodes are fitted to the brain surface and ECoG measurement units record 128-channel (ch) ECoG signals at a sampling rate of 1 kHz. The units transfer data to the data and power management unit implanted subcutaneously in the abdomen through a subcutaneous stretchable spiral cable. The data and power management unit then communicates with a workstation outside the body and wirelessly receives 400 mW of power from an external wireless transmitter. The workstation records and analyzes the received data in the frequency domain and controls external devices based on analyses. We investigated the performance of the proposed system. We were able to use W-HERBS to detect sine waves with a 4.8-μV amplitude and a 60–200-Hz bandwidth from the ECoG BMIs. W-HERBS is the first fully implantable ECoG-based BMI system with more than 100 ch. It is capable of recording 128-ch subdural ECoG signals with sufficient input-referred noise (3 μVrms) and with an acceptable time delay (250 ms). The system contributes to the clinical application of high-performance BMIs and to experimental brain research

Spinal Cord Injury and Transcutaneous Spinal Cord Stimulation

Recent research of epidural and transcutaneous electrical spinal cord stimulation has demonstrated unprecedented improvements in motor function thought to be irreversibly lost due to chronic, severe spinal cord injury. Studies in parallel assess these methods for spasticity management as an alternative to medications that are often accompanied by deleterious side effects. As a noninvasive intervention, transcutaneous spinal cord stimulation holds the great potential to find its way into wide clinical application. Its firm establishment and lasting acceptance as clinical practice in spinal cord injury will not only hinge on the demonstration of safety and efficacy, but also on the delineation of a conceptual framework of the underlying physiological mechanisms. This will also require advancing our understanding of immediate and temporary effects of transcutaneous spinal cord on neuronal circuits in the intact and injured spinal cord. The purpose of this collection of papers is to bring together peers in the field to share—and eventually fuse—their pertinent research into current neurorehabilitation practice by providing a clinical perspective and novel insights into the underlying mechanisms

Closed-loop approaches for innovative neuroprostheses

The goal of this thesis is to study new ways to interact with the nervous system in case of damage or pathology. In particular, I focused my effort towards the development of innovative, closed-loop stimulation protocols in various scenarios: in vitro, ex vivo, in vivo

In Vivo Imaging to Characterize Dynamic Tissue Responses after Neural Electrode Implantation

Implantable neural electrodes are promising technologies to restore motor, sensory, and cognitive function in many neural pathologies through brain-computer interfacing (BCI). Many BCI applications require electrode implantation within neural tissue to resolve and/or modulate the physiological activity of individual neurons via electrical recording and stimulation. This invasive implantation leads to acute and long-term deterioration of both the electrode device as well as the neurons surrounding the device. Ultimately, damage to the electrode and neural tissue results in electrode recording failure within the first years after implantation. Many strategies to improve BCI longevity focus on mitigating tissue damage through improving neuronal survival or reducing inflammatory activity around implants. Despite incremental improvements, electrode failure persists as an obstacle to wide-spread clinical deployment of BCIs. This can be partly attributed to an incomplete understanding of the biological correlates of recording performance. These correlates have largely been identified through post-mortem histological staining, which cannot capture dynamic changes in cellular physiology and morphology. In the following dissertation, we use longitudinal two-photon in vivo imaging to quantify how neurons, microglia, and meningeal immune cells are affected by an intracortical electrode during and after implantation in mouse cortex. We go beyond conventional histological techniques to show the time-course of neuronal injury and microglial recruitment after implantation. Neuronal injury occurs instantaneously, with prolonged, high calcium levels evident in neurons within 100 µm of implants. Microglial activation occurs within minutes of implantation and subsequent microglial encapsulation of electrodes can be modulated by bioactive surface coatings. Within the first day post-implant, there is high trafficking of peripheral immune cells through venules at the surface of the brain as well as along the electrode’s shank at the surface of the brain. Over the next month, calcium activity in neurons increases while the collagenous meningeal tissues at the surface of the brain thicken. We further show that meningeal thickening can have profound implications for devices implanted into non-human primates as well. In sum, these results define new potential therapeutic targets and windows that could improve the longevity of implantable neural electrodes