Classification of grasping tasks based on EEG-EMG coherence

This work presents an innovative application of the well-known concept of cortico-muscular coherence for the classification of various motor tasks, i.e., grasps of different kinds of objects. Our approach can classify objects with different weights (motor-related features) and different surface frictions (haptics-related features) with high accuracy (over 0:8). The outcomes presented here provide information about the synchronization existing between the brain and the muscles during specific activities; thus, this may represent a new effective way to perform activity recognition

A common subcortical oscillatory network contributes to recovery after spinal cord injury

Recent studies in monkeys showed that when the direct cortico-motoneuronal connection was transected at mid-cervical segments, remaining, indirect cortico-motoneuronal pathways compensated for finger dexterity within one to three months. To elucidate the changes in dynamic properties of neural circuits during the recovery, we investigated the cortico-muscular and inter-muscular couplings of activities throughout the recovery course. Activities of antagonist muscle pairs showed co-activation during the second postoperative week, and oscillated coherently at frequencies of 30-46 Hz (gamma-band) by one month postoperatively. Such gamma-band inter-muscular coherence was not observed preoperatively, but became prominent and distributed widely over proximal and distal muscles with the recovery. Neither the gamma-band cortico-muscular coupling (14-30 Hz) observed before lesion, nor a gamma-band oscillation was observed in bilateral motor cortex after lesion. Thus, we propose that an unknown, subcortical oscillator, independent of cortical oscillation, commonly recruits hand/arm muscles and may underlie functional recovery of dexterous finger movements

Surface Electromyographic (sEMG) Transduction of Hand Joint Angles for Human Interfacing Devices (HID)

This is an investigation of the use of surface electromyography (sEMG) as a tool to improve human interfacing devices (HID) information bandwidth through the transduction of the fingertip workspace. It combines the work of Merletti et al and Jarque-Bou et al to design an open-source framework for Fingertip Workspace based Human Interfacing Devices (HID). In this framework, the fingertip workspace is defined as the system of forearm and hand muscle force through a tensor which describes hand anthropometry. The thesis discusses the electrophysiology of muscle tissue along with the anatomy and physiology of the arm in pursuit of optimizing sensor location, muscle force measurements, and viable command gestures. Algorithms for correlating sEMG to hand joint angle are investigated using MATLAB for both static and moving gestures. Seven sEMG spots and Fingertip Joint Angles recorded by Jarque Bou et al are investigated for the application of sEMG to Human Interfacing Devices (HID). Such technology is termed Gesture Computer Interfacing (GCI) and has been shown feasible through devices such as CTRL Labs interface, and models such as those of Sartori, Merletti, and Zhao. Muscles under sEMG spots in this dataset and the actions related to them are discussed, along with what muscles and hand actions are not visible within this dataset. Viable gestures for detection algorithms are discussed based on the muscles discerned to be visible in the dataset through intensity, spectral moment, power spectra, and coherence. Detection and isolation of such viable actions is fundamental to designing an EMG driven musculoskeletal model of the hand needed to facilitate GCI. Enveloping, spectral moment, power spectrum, and coherence analysis are applied to a Sollerman Hand Function Test sEMG dataset of twenty-two subjects performing 26 activities of living to differentiate pinching and grasping tasks. Pinches and grasps were found to cause very different activation patterns in sEMG spot 3 relating to flexion of digits I - V. Spectral moment was found to be less correlated with differentiation and provided information about the degree of object manipulation performed and extent of fatigue during each task. Coherence was shown to increase between flexors and extensors with intensity of task but was found corrupted by crosstalk with increasing intensity of muscular activation. Some spectral results correlated between finger flexor and extensor power spectra showed anticipatory coherence between the muscle groups at the end of object manipulation. An sEMG amplification system capable of capturing HD-sEMG with a bandwidth of 300 and 500 Hz at a sampling frequency of 2 kHz was designed for future work. The system was designed in ordinance with current IEEE research on sensor-electrode characteristics. Furthermore, discussion of solutions to open issues in HD-sEMG is provided. This work did not implement the designed wristband but serves as a literature review and open-source design using commercially available technologies

Cortico-muscular coupling to control a hybrid brain-computer interface for upper limb motor rehabilitation: A pseudo-online study on stroke patients

Brain-Computer Interface (BCI) systems for motor rehabilitation after stroke have proven their efficacy to enhance upper limb motor recovery by reinforcing motor related brain activity. Hybrid BCIs (h-BCIs) exploit both central and peripheral activation and are frequently used in assistive BCIs to improve classification performances. However, in a rehabilitative context, brain and muscular features should be extracted to promote a favorable motor outcome, reinforcing not only the volitional control in the central motor system, but also the effective projection of motor commands to target muscles, i.e., central-to-peripheral communication. For this reason, we considered cortico-muscular coupling (CMC) as a feature for a h-BCI devoted to post-stroke upper limb motor rehabilitation. In this study, we performed a pseudo-online analysis on 13 healthy participants (CTRL) and 12 stroke patients (EXP) during executed (CTRL, EXP unaffected arm) and attempted (EXP affected arm) hand grasping and extension to optimize the translation of CMC computation and CMC-based movement detection from offline to online. Results showed that updating the CMC computation every 125 ms (shift of the sliding window) and accumulating two predictions before a final classification decision were the best trade-off between accuracy and speed in movement classification, independently from the movement type. The pseudo-online analysis on stroke participants revealed that both attempted and executed grasping/extension can be classified through a CMC-based movement detection with high performances in terms of classification speed (mean delay between movement detection and EMG onset around 580 ms) and accuracy (hit rate around 85%). The results obtained by means of this analysis will ground the design of a novel non-invasive h-BCI in which the control feature is derived from a combined EEG and EMG connectivity pattern estimated during upper limb movement attempts

Neural bases of hand synergies

abstract: The human hand has so many degrees of freedom that it may seem impossible to control. A potential solution to this problem is “synergy control” which combines dimensionality reduction with great flexibility. With applicability to a wide range of tasks, this has become a very popular concept. In this review, we describe the evolution of the modern concept using studies of kinematic and force synergies in human hand control, neurophysiology of cortical and spinal neurons, and electromyographic (EMG) activity of hand muscles. We go beyond the often purely descriptive usage of synergy by reviewing the organization of the underlying neuronal circuitry in order to propose mechanistic explanations for various observed synergy phenomena. Finally, we propose a theoretical framework to reconcile important and still debated concepts such as the definitions of “fixed” vs. “flexible” synergies and mechanisms underlying the combination of synergies for hand control.View the article as published at http://journal.frontiersin.org/article/10.3389/fncom.2013.00023/ful

Corticomuscular co-activation based hybrid brain-computer interface for motor recovery monitoring

The effect of corticomuscular coactivation based hybrid brain-computer interface (h-BCI) on post-stroke neurorehabilitation has not been explored yet. A major challenge in this area is to find an appropriate corticomuscular feature which can not only drive an h-BCI but also serve as a biomarker for motor recovery monitoring. Our previous study established the feasibility of a new method of measuring corticomuscular co-activation called correlation of band-limited power time-courses (CBPT) of EEG and EMG signals, outperforming the traditional EEG-EMG coherence in terms of accurately controlling a robotic hand exoskeleton device by the stroke patients. In this paper, we have evaluated the neurophysiological significance of CBPT for motor recovery monitoring by conducting a 5-week long longitudinal pilot trial on 4 chronic hemiparetic stroke patients. Results show that the CBPT variations correlated significantly (p-value< 0.05) with the dynamic changes in motor outcome measures during the therapy for all the patients. As the bandpower based biomarkers are popular in literature, a comparison with such biomarkers has also been made to cross-verify whether the changes in CBPT are indeed neurophysiological. Thus the study concludes that CBPT can serve as a biomarker for motor recovery monitoring while serving as a corticomuscular co-activation feature for h-BCI based neurorehabilitation. Despite an observed significant positive change between pre- and post-intervention motor outcomes, the question of the clinical effectiveness of CBPT is subject to further controlled trial on a larger cohort

Neural bases of hand synergies

The human hand has so many degrees of freedom that it may seem impossible to control. A potential solution to this problem is "synergy control" which combines dimensionality reduction with great flexibility. With applicability to a wide range of tasks, this has become a very popular concept. In this review, we describe the evolution of the modern concept using studies of kinematic and force synergies in human hand control, neurophysiology of cortical and spinal neurons, and electromyographic (EMG) activity of hand muscles. We go beyond the often purely descriptive usage of synergy by reviewing the organization of the underlying neuronal circuitry in order to propose mechanistic explanations for various observed synergy phenomena. Finally, we propose a theoretical framework to reconcile important and still debated concepts such as the definitions of "fixed" vs. "flexible" synergies and mechanisms underlying the combination of synergies for hand control

A subcortical oscillatory network contributes to recovery of hand dexterity after spinal cord injury

Recent studies have shown that after partial spinal-cord lesion at the mid-cervical segment, the remaining pathways compensate for restoring finger dexterity; however, how they control hand/arm muscles has remained unclear. To elucidate the changes in dynamic properties of neural circuits connecting the motor cortex and hand/arm muscles, we investigated the cortico- and inter-muscular couplings of activities throughout the recovery period after the spinal-cord lesion. Activities of antagonist muscle pairs showed co-activation and oscillated coherently at frequencies of 30–46 Hz (γ-band) by 1-month post-lesion. Such γ-band inter-muscular coupling was not observed pre-lesion, but emerged and was strengthened and distributed over a wide range of hand/arm muscles along with the recovery. Neither the β-band (14–30 Hz) cortico-muscular coupling observed pre-lesion nor a γ-band oscillation was observed in the motor cortex post-lesion. We propose that a subcortical oscillator commonly recruits hand/arm muscles, via remaining pathways such as reticulospinal and/or propriospinal tracts, independent of cortical oscillation, and contributes to functional recovery

Inhibition and oscillatory activity in human motor cortex

Using transcranial magnetic stimulation (TMS) important information can be obtained about the function of motor cortical circuitry during performance of voluntary movements by conscious human subjects. In particular, pairs of TMS pulses can probe inhibitory pathways projecting onto corticospinal neurones, which themselves project to motoneurones innervating hand muscles. This allows investigation of inhibitory circuitry involved in the performance of specific motor tasks, such as the precision grip. Previous studies have shown that pronounced synchronous oscillatory activity within the hand motor system is present at both cortical and muscular level when subjects maintain steady grasp of an object in a precision grip. The origin of this synchronous activity is unknown. However modelling studies have suggested that inhibitory pathways are likely to play an important role in the generation of cortical oscillations, and therefore TMS was used in this Thesis to investigate the origin of synchrony present during the precision grip task. In the first study, parameters of the paired-pulse test used to measure intracortical inhibition were examined. It was found that by modifying the intensities of the stimuli, and the interval between the paired-pulses, different phases of inhibition could be measured. This enabled specific use of TMS to investigate inhibitory pathways. Both single and paired-pulse TMS were then delivered to the motor cortex of subjects performing a precision grip task. It was found that low intensity TMS could reset the phase of muscle oscillatory activity, consistent with corticospinal neurones being part of the circuitry that generates the oscillatory rhythm. When, in the paired-pulse test, a low intensity stimulus was followed a few milliseconds later with a larger TMS stimulus, in the paired-pulse test, strong intracortical inhibition could be measured. This suggested that inhibitory interneurones activated by low intensity TMS could play an important role in the rhythm-generating network. An additional study looked at the importance of cutaneous receptor feedback on synchrony, by studying the effects of local anaesthesia of the index finger and thumb. Whereas low intensity TMS was shown to enhance synchronous activity between muscle pairs, suppression of cutaneous feedback from the digits reduced it. Results in this Thesis suggest that inhibitory interneurones within the motor cortex are important in the generation of synchronous activity within the hand motor system. This synchrony is also under the influence of cutaneous afferent input