Moregrasp: Restoration of Upper Limb Function in Individuals with High Spinal Cord Injury by Multimodal Neuroprostheses for Interaction in Daily Activities

The aim of the MoreGrasp project is to develop a noninvasive, multimodal user interface including a brain-computer interface (BCI) for intuitive control of a grasp neuroprosthesis to support individuals with high spinal cord injury (SCI) in everyday activities. We describe the current state of the project, including the EEG system, preliminary results of natural movements decoding in people with SCI, the new electrode concept for the grasp neuroprosthesis, the shared control architecture behind the system and the implementation of a user-centered design

An Electrocorticographic Brain Interface in an Individual with Tetraplegia

Brain-computer interface (BCI) technology aims to help individuals with disability to control assistive devices and reanimate paralyzed limbs. Our study investigated the feasibility of an electrocorticography (ECoG)-based BCI system in an individual with tetraplegia caused by C4 level spinal cord injury. ECoG signals were recorded with a high-density 32-electrode grid over the hand and arm area of the left sensorimotor cortex. The participant was able to voluntarily activate his sensorimotor cortex using attempted movements, with distinct cortical activity patterns for different segments of the upper limb. Using only brain activity, the participant achieved robust control of 3D cursor movement. The ECoG grid was explanted 28 days post-implantation with no adverse effect. This study demonstrates that ECoG signals recorded from the sensorimotor cortex can be used for real-time device control in paralyzed individuals

Spatial distribution of HD-EMG improves identification of task and force in patients with incomplete spinal cord injury

Background: Recent studies show that spatial distribution of High Density surface EMG maps (HD-EMG) improves the identification of tasks and their corresponding contraction levels. However, in patients with incomplete spinal cord injury (iSCI), some nerves that control muscles are damaged, leaving some muscle parts without an innervation. Therefore, HD-EMG maps in patients with iSCI are affected by the injury and they can be different for every patient. The objective of this study is to investigate the spatial distribution of intensity in HD-EMG recordings to distinguish co-activation patterns for different tasks and effort levels in patients with iSCI. These patterns are evaluated to be used for extraction of motion intention.; Method: HD-EMG was recorded in patients during four isometric tasks of the forearm at three different effort levels. A linear discriminant classifier based on intensity and spatial features of HD-EMG maps of five upper-limb muscles was used to identify the attempted tasks. Task and force identification were evaluated for each patient individually, and the reliability of the identification was tested with respect to muscle fatigue and time interval between training and identification. Results: Three feature sets were analyzed in the identification: 1) intensity of the HD-EMG map, 2) intensity and center of gravity of HD-EMG maps and 3) intensity of a single differential EMG channel (gold standard).; Results show that the combination of intensity and spatial features in classification identifies tasks and effort levels properly (Acc = 98.8 %; S = 92.5 %; P = 93.2 %; SP = 99.4 %) and outperforms significantly the other two feature sets (p < 0.05).; Conclusion: In spite of the limited motor functionality, a specific co-activation pattern for each patient exists for both intensity, and spatial distribution of myoelectric activity. The spatial distribution is less sensitive than intensity to myoelectric changes that occur due to fatigue, and other time-dependent influences.Peer ReviewedPostprint (published version

Optimisation of hand posture stimulation using an electrode array and iterative learning control.

Nonlinear optimisation-based search algorithms have been developed for the precise stimulation of muscles in the wrist and hand, to enable stroke patients to attain predefined gestures. These have been integrated in a system comprising a 40 element surface electrode array that is placed on the forearm, an electrogoniometer and data glove supplying position data from 16 joint angles, and custom signal generation and switching hardware to route the electrical stimulation to individual array elements. The technology will be integrated in a upper limb rehabilitation system currently undergoing clinical trials to increase their ability to perform functional tasks requiring fine hand and finger movement. Initial performance results from unimpaired subjects show the successful reproduction of six reference hand postures using the system

Quantifying Performance of Bipedal Standing with Multi-channel EMG

Spinal cord stimulation has enabled humans with motor complete spinal cord injury (SCI) to independently stand and recover some lost autonomic function. Quantifying the quality of bipedal standing under spinal stimulation is important for spinal rehabilitation therapies and for new strategies that seek to combine spinal stimulation and rehabilitative robots (such as exoskeletons) in real time feedback. To study the potential for automated electromyography (EMG) analysis in SCI, we evaluated the standing quality of paralyzed patients undergoing electrical spinal cord stimulation using both video and multi-channel surface EMG recordings during spinal stimulation therapy sessions. The quality of standing under different stimulation settings was quantified manually by experienced clinicians. By correlating features of the recorded EMG activity with the expert evaluations, we show that multi-channel EMG recording can provide accurate, fast, and robust estimation for the quality of bipedal standing in spinally stimulated SCI patients. Moreover, our analysis shows that the total number of EMG channels needed to effectively predict standing quality can be reduced while maintaining high estimation accuracy, which provides more flexibility for rehabilitation robotic systems to incorporate EMG recordings

Improved Functional Electrical Stimulation (FES) systems for optimized selectivity

En el presente trabajo de Tesis se aborda el tema de selectividad en la activación muscular en las aplicaciones de estimulación eléctrica funcional en el miembro superior. Este tipo de tecnología presenta una serie de problemas, de los cuales se destaca la dificultad de estimular solo un musculo debido al reducido tamaño de ellos y la alta densidad de músculos presentes. El problema este, llamado “oveflow" en inglés, aparece debido a la dificultad de controlar el camino de la corriente eléctrica debajo de la piel hacia el musculo. Los electrodos tipo matriz han sido la apuesta de varios estudios para afrontar estas dificultades y varias soluciones se han presentado los últimos 10 años. Estos estudios se enfocan en el desarrollo de sistemas y de la tecnología electrónica necesaria. Sin embargo, faltan estudios de los parámetros que influyen en la activación selectiva de los músculos y como optimizar todos estos parámetros. El objetivo de esta tesis es el desarrollo de un sistema de estimulación eléctrica funcional superficial, basado en los electrodos tipo matriz, que optimiza la selectividad muscular. Se conoce desde la bibliografía que el camino de la corriente eléctrica debajo de la piel depende de una serie de factores. Entre ellos se encuentran la posición, la forma y el tamaño del electrodo de cátodo, la posición del electrodo de ánodo y la impedancia de la membrana de gel del electrodo. Esta tesis se enfoca en optimizar estos factores que permiten modular el campo eléctrico que se genera debajo del electrodo. El sistema que se ha desarrollado se usó con ese objetivo. El sistema se ha evaluado en dos escenarios: en pacientes con temblor y pacientes con lesión medular

Advances in selective activation of muscles for non-invasive motor neuroprostheses

Non-invasive neuroprosthetic (NP) technologies for movement compensation and rehabilitation remain with challenges for their clinical application. Two of those major challenges are selective activation of muscles and fatigue management. This review discusses how electrode arrays improve the efficiency and selectivity of functional electrical stimulation (FES) applied via transcutaneous electrodes. In this paper we review the principles and achievements during the last decade on techniques for artificial motor unit recruitment to improve the selective activation of muscles. We review the key factors affecting the outcome of muscle force production via multi-pad transcutaneous electrical stimulation and discuss how stimulation parameters can be set to optimize external activation of body segments. A detailed review of existing electrode array systems proposed by different research teams is also provided. Furthermore, a review of the targeted applications of existing electrode arrays for control of upper and lower limb NPs is provided. Eventually, last section demonstrates the potential of electrode arrays to overcome the major challenges of NPs for compensation and rehabilitation of patient-specific impairments.This work has been done with partial financial support of the Ministry of Science and Innovation, in the framework of national project HYPER(CSD 2009-00067- Hybrid Neuroprosthetic and Neurorobotic Devices for Functional Compensation and Rehabilitation of Motor Disorders) and European Union in the framework of TREMOR Project: “TREMOR: An ambulatory BCI-driven tremor suppression system based on functional electrical stimulation”, ICT-2007-224051, and “NeuroTREMOR: A novel concept for support to diagnosis and remote management of tremor”, ICT-2011.5.1-287739.Peer reviewe