M. Coscia

Effects of early and intensive neuro-rehabilitative treatment on muscle synergies in acute post-stroke patients: a pilot study

BackgroundAfter a stroke, patients show significant modifications of neural control of movement, such as abnormal muscle co-activation, and reduced selectivity and modulation of muscle activity. Nonetheless, results reported in literature do not allow to unequivocally explain whether and, in case, how a cerebrovascular accident affects muscle synergies underlying the control of the upper limb. These discrepancies suggest that a complete understanding of the modular re-organization of muscle activity due to a stroke is still lacking. This pilot study aimed at investigating the effects of the conjunction between the natural ongoing of the pathology and the intense robot-mediated treatment on muscle synergies of the paretic upper limb of subacute post-stroke patients.MethodsSix subacute patients, homogenous with respect to the age and the time elapsed from the trauma, and ten healthy age-matched subjects were enrolled. The protocol consisted in achieving planar movement of the upper limb while handling the end-effector of a robotic platform. Patients underwent 6 weeks long treatment while clinical scores, kinematics of the end-effector and muscle activity were recorded. Then we verified whether muscle coordination underlying the motor task was significantly affected by the cerebrovascular accident and how muscle synergies were modified along the treatment.ResultsResults show that although muscle synergies in subacute stroke patients were qualitatively comparable to those of healthy subjects, those underlying the movement of the shoulder can reflect the functional deficit induced by the pathology. Moreover, the improvement of motor performance due to the treatment was achieved in conjunction with slight modifications of muscle synergies. In this regard, modifications of muscle synergies appeared to be influenced by the different recovering mechanisms across patients presumably due to the heterogeneity of lesions, sides and location of the accident.ConclusionsThe results support the hypothesis that muscle synergies reflect the injury of the cerebrovascular accident and could document the effects of the functional recovery due to a suitable and customized treatment. Therefore, they open up new possibilities for the development of more effective neuro-rehabilitation protocols.

The effect of arm weight support on upper limb muscle synergies during reaching movements

BackgroundCompensating for the effect of gravity by providing arm-weight support (WS) is a technique often utilized in the rehabilitation of patients with neurological conditions such as stroke to facilitate the performance of arm movements during therapy. Although it has been shown that, in healthy subjects as well as in stroke survivors, the use of arm WS during the performance of reaching movements leads to a general reduction, as expected, in the level of activation of upper limb muscles, the effects of different levels of WS on the characteristics of the kinematics of motion and of the activity of upper limb muscles have not been thoroughly investigated before.MethodsIn this study, we systematically assessed the characteristics of the kinematics of motion and of the activity of 14 upper limb muscles in a group of 9 healthy subjects who performed 3-D arm reaching movements while provided with different levels of arm WS. We studied the hand trajectory and the trunk, shoulder, and elbow joint angular displacement trajectories for different levels of arm WS. Besides, we analyzed the amplitude of the surface electromyographic (EMG) data collected from upper limb muscles and investigated patterns of coordination via the analysis of muscle synergies.ResultsThe characteristics of the kinematics of motion varied across WS conditions but did not show distinct trends with the level of arm WS. The level of activation of upper limb muscles generally decreased, as expected, with the increase in arm WS. The same eight muscle synergies were identified in all WS conditions. Their level of activation depended on the provided level of arm WS.ConclusionsThe analysis of muscle synergies allowed us to identify a modular organization underlying the generation of arm reaching movements that appears to be invariant to the level of arm WS. The results of this study provide a normative dataset for the assessment of the effects of the level of arm WS on muscle synergies in stroke survivors and other patients who could benefit from upper limb rehabilitation with arm WS.

Evaluation of the effects of the Arm Light Exoskeleton on movement execution and muscle activities: a pilot study on healthy subjects

BackgroundExoskeletons for lower and upper extremities have been introduced in neurorehabilitation because they can guide the patient’s limb following its anatomy, covering many degrees of freedom and most of its natural workspace, and allowing the control of the articular joints. The aims of this study were to evaluate the possible use of a novel exoskeleton, the Arm Light Exoskeleton (ALEx), for robot-aided neurorehabilitation and to investigate the effects of some rehabilitative strategies adopted in robot-assisted training.MethodsWe studied movement execution and muscle activities of 16 upper limb muscles in six healthy subjects, focusing on end-effector and joint kinematics, muscle synergies, and spinal maps. The subjects performed three dimensional point-to-point reaching movements, without and with the exoskeleton in different assistive modalities and control strategies.ResultsThe results showed that ALEx supported the upper limb in all modalities and control strategies: it reduced the muscular activity of the shoulder’s abductors and it increased the activity of the elbow flexors. The different assistive modalities favored kinematics and muscle coordination similar to natural movements, but the muscle activity during the movements assisted by the exoskeleton was reduced with respect to the movements actively performed by the subjects. Moreover, natural trajectories recorded from the movements actively performed by the subjects seemed to promote an activity of muscles and spinal circuitries more similar to the natural one.ConclusionsThe preliminary analysis on healthy subjects supported the use of ALEx for post-stroke upper limb robotic assisted rehabilitation, and it provided clues on the effects of different rehabilitative strategies on movement and muscle coordination.

Randomized trial on the effects of a combined physical/cognitive training in aged MCI subjects: the Train the Brain study

Age-related cognitive impairment and dementia are an increasing societal burden. Epidemiological studies indicate that lifestyle factors, e.g. physical, cognitive and social activities, correlate with reduced dementia risk; moreover, positive effects on cognition of physical/cognitive training have been found in cognitively unimpaired elders. Less is known about effectiveness and action mechanisms of physical/cognitive training in elders already suffering from Mild Cognitive Impairment (MCI), a population at high risk for dementia. We assessed in 113 MCI subjects aged 65–89 years, the efficacy of combined physical-cognitive training on cognitive decline, Gray Matter (GM) volume loss and Cerebral Blood Flow (CBF) in hippocampus and parahippocampal areas, and on brain-blood-oxygenation-level-dependent (BOLD) activity elicited by a cognitive task, measured by ADAS-Cog scale, Magnetic Resonance Imaging (MRI), Arterial Spin Labeling (ASL) and fMRI, respectively, before and after 7 months of training vs. usual life. Cognitive status significantly decreased in MCI-no training and significantly increased in MCI-training subjects; training increased parahippocampal CBF, but no effect on GM volume loss was evident; BOLD activity increase, indicative of neural efficiency decline, was found only in MCI-no training subjects. These results show that a non pharmacological, multicomponent intervention improves cognitive status and indicators of brain health in MCI subjects.

Cost function tuning improves muscle force estimation computed by static optimization during walking

Muscle force estimation while a dynamic motor task is carried out still presents open questions. In particular, concerning locomotion, although the inverse dynamic based static optimization has been widely accepted as a suitable method to obtain reliable results, appropriate modifications of the object function may improve results. This paper was aimed at analyzing the sensitivity of estimated muscle forces when modifications of the objective function are adopted to better fit EMG signals of healthy subjects. A 7 links and 9 degrees of freedom biomechanical model accounting for 14 lower limb muscles, grouped in 9 equivalent actuators, was developed. Muscle forces were estimated by using the inverse dynamic based static optimization in which the performance criteria was the sum of muscle stresses raised to a certain n power. This exponent was gradually changed (from 2 to 100) and the agreement between force patterns and EMG signals was estimated by both the correlation coefficient and the Coactivation Index. Results suggested that force estimation can be improved by slightly modifying the cost function. In particular, with respect to adopted data, when the exponent belong to the interval between 2.75 and 4, estimated forces better captured general features of EMG signals. Concluding, a more reliable solution can be obtained by suitably tuning the cost function in order to fit EMG signals.

Effects of an upper limb robot-mediated therapy on paretic upper limb in chronic hemiparetic subjects: A biomechanical and EEG-based approach for functional assessment

During the last decade, different robotic devices have been developed for motor rehabilitation of stroke survivors. These devices have been shown to offer therapeutic benefits and improve functional motor outcomes.

Evaluating upper limb impairments in multiple sclerosis by exposure to different mechanical environments

Multiple sclerosis is a chronic, autoimmune and neurodegenerative disease affecting multiple functional systems and resulting in motor impairments associated with muscle weakness and lack of movement coordination. We quantified upper limb motor deficits with a robot-based assessment including behavioral and muscle synergy analysis in 11 multiple sclerosis subjects with mild to moderate upper limb impairment (9 female; 50 ± 10 years) compared to 11 age- and gender- matched controls (9 female; 50 ± 9 years). All subjects performed planar reaching tasks by moving their upper limb or applying force while grasping the handle of a robotic manipulandum that generated four different environments: free space, assistive or resistive forces, and rigid constraint. We recorded the activity of 15 upper body muscles. Multiple sclerosis subjects generated irregular trajectories. While activities in isolated arm muscles appeared generally normal, shoulder muscle coordination with arm motions was impaired and there was a marked co-activation of the biceps and triceps in extension movements. Systematic differences in timing and organization of muscle synergies have also been observed. This study supports the definition of new biomarkers and rehabilitative treatments for improving upper limb motor coordination in multiple sclerosis.

EMG-based decoding of grasp gestures in reaching-to-grasping motions

Predicting the grasping function during reach-to-grasp motions is essential for controlling a prosthetic hand or a robotic assistive device. An early accurate prediction increases the usability and the comfort of a prosthetic device. This work proposes an electromyographic-based learning approach that decodes the grasping intention at an early stage of reach-to-grasp motion, i.e.before the final grasp/hand pre-shape takes place. Superficial electrodes and a Cyberglove were used to record the arm muscle activity and the finger joints during reach-to-grasp motions. Our results showed a 90% accuracy for the detection of the final grasp about 0.5 s after motion onset. This paper also examines the effect of different objects distances and different motion speeds on the detection time and accuracy of the classifier. The use of our learning approach to control a 16-degrees of freedom robotic hand confirmed the usability of our approach for the real-time control of robotic devices. Decode of the grasp type by Electromyography on the early stages of the reach-to-grasp motion.Possible to decode the grasp type during the preshaping of the hand.Possible generalization over different positions of the object near the training position.A robotic implementation showed that it possible to express accurately the intention of the grasp type through a robotic hand during the reaching motion and before grasping the object.

EEG topographies provide subject-specific correlates of motor control

Electroencephalography (EEG) of brain activity can be represented in terms of dynamically changing topographies (microstates). Notably, spontaneous brain activity recorded at rest can be characterized by four distinctive topographies. Despite their well-established role during resting state, their implication in the generation of motor behavior is debated. Evidence of such a functional role of spontaneous brain activity would provide support for the design of novel and sensitive biomarkers in neurological disorders. Here we examined whether and to what extent intrinsic brain activity contributes and plays a functional role during natural motor behaviors. For this we first extracted subject-specific EEG microstates and muscle synergies during reaching-and-grasping movements in healthy volunteers. We show that, in every subject, well-known resting-state microstates persist during movement execution with similar topographies and temporal characteristics, but are supplemented by novel task-related microstates. We then show that the subject-specific microstates’ dynamical organization correlates with the activation of muscle synergies and can be used to decode individual grasping movements with high accuracy. These findings provide first evidence that spontaneous brain activity encodes detailed information about motor control, offering as such the prospect of a novel tool for the definition of subject-specific biomarkers of brain plasticity and recovery in neuro-motor disorders.

How are Muscle Synergies Affected by Electromyography Pre-Processing?

Muscle synergies have been used for decades to explain a variety of motor behaviors, both in humans and animals and, more recently, to steer rehabilitation strategies. However, many sources of variability such as factorization algorithms, criteria for dimensionality reduction and data pre-processing constitute a major obstacle to the successful comparison of the results obtained by different research groups. Starting from the canonical EMG processing we determined how variations in filter cut-off frequencies and normalization methods, commonly found in literature, affect synergy weights and inter-subject similarity (ISS) using experimental data related to a 15-muscles upper-limb reaching task. Synergy weights were not significantly altered by either normalization (maximum voluntary contraction – MVC – or maximum amplitude of the signal - SELF) or band-pass filter ([20–500 Hz] or [50–500] Hz). Normalization did, however, alter the amount of variance explained by a set of synergies, which is a criterion often used for model order selection. Comparing different low-pass (LP) filters (0.5 Hz, 4 Hz, 10 Hz, 20 Hz cut-offs) we showed that increasing the low pass filter cut-off had the effect of decreasing the variance accounted for by a set number of synergies and affected individual muscle contributions. Extreme smoothing (i.e., LP cut-off 0.5 Hz) enhanced the contrast between active and inactive muscles but had an unpredictable effect on the ISS. The results presented here constitute a further step towards a thoughtful EMG pre-processing for the extraction of muscle synergies.